ASCL.net

Astrophysics Source Code Library

Making codes discoverable since 1999

Browsing Codes

Results 1-3127 of 3437 (3348 ASCL, 89 submitted)

Previous
12Next
Order
Title Date
 
Mode
Abstract Compact
Per Page
50100250All
[ascl:2403.003] kinematic_scaleheight: Infer the vertical distribution of clouds in the solar neighborhood

kinematic_scaleheight uses MCMC methods to kinematically estimate the vertical distribution of clouds in the Galactic plane, including the least squares analysis of Crovisier (1978), an updated least squares analysis using a modern Galactic rotation model, and a Bayesian model sampled via MCMC as described in Wenger et al. (2024).

[ascl:2403.002] DistClassiPy: Distance-based light curve classification

DistClassiPy uses different distance metrics to classify objects such as light curves. It provides state-of-the-art performance for time-domain astronomy, and offers lower computational requirements and improved interpretability over traditional methods such as Random Forests, making it suitable for large datasets. DistClassiPy allows fine-tuning based on scientific objectives by selecting appropriate distance metrics and features, which enhances its performance and improves classification interpretability.

[ascl:2403.001] Pynkowski: Minkowski functionals and other higher order statistics

Pynkowski computes Minkowski Functionals and other higher order statistics of input fields, as well as their expected values for different kinds of fields. This package supports Minkowski functionals, and maxima and minima distributions. Supported input formats include scalar HEALPix maps such as those used by healpy (ascl:2008.022) and polarization HEALPix maps in the SO(3) formalism. Pynkowski also supports various theoretical fields, including Gaussian (e.g., CMB Temperature or the initial density field), Chi squared (e.g., CMB polarization intensity), and spin 2 maps in the SO(3) formalism.

[submitted] MINDS: a hybrid pipeline for the reduction of JWST/MIRI-MRS data

The MINDS package contains a hybrid pipeline based on the jwst pipeline and routines from the VIP package for the reduction of JWST MIRI-MRS data. The pipeline was developed by the MINDS - MIRI mid-INfrared Disk Survey - GTO team in an attempt to compensate for some of the known weaknesses of the official jwst pipeline to improve the quality of spectrum extracted from MIRI-MRS data. This is done by leveraging the capabilities of VIP, another large data reduction package used in the field of high-contrast imaging.
The front end of the pipeline is a highly automated Jupyter notebook. Parameters are typically set in one cell at the beginning of the notebook, and the rest of the notebook can be run without any further modification. The Jupyter notebook format provides flexibility, enhanced visibility of intermediate and final results, more straightforward troubleshooting, and the possibility to easily incorporate additional codes by the user to further analyse or exploit their results.

[submitted] fkpt: code to compute LCDM and modified gravity perturbation theory using fk-kernels

Perturbation theory for LCDM and Modified Gravity theories using "fk"-Kernels. fkpt is a code that computes the 1-loop redshift space power spectrum for tracers. Hu-Sawicky f(R) is the only modified gravity model implemented so far. It is straightforward to do it for other models.

[submitted] Poke: An open-source ray-based physical optics platform

Integrated optical models allow for accurate prediction of the as-built performance of an optical instrument. Optical models are typically composed of a separate ray trace and diffraction model to capture both the geometrical and physical regimes of light. These models are typically separated across both open-source and commercial software that don't interface with each other directly. To bridge the gap between ray trace models and diffraction models, we have built an open-source optical analysis platform in Python called Poke that uses commercial ray tracing APIs and open-source physical optics engines to simultaneously model scalar wavefront error, diffraction, and polarization. Poke operates by storing ray data from a commercial ray tracing engine into a Python object, from which physical optics calculations can be made. We present an introduction to using Poke, and highlight the capabilities of two new propagation physics modules that add to the utility of existing scalar diffraction models. Gaussian Beamlet Decomposition is a ray-based approach to diffraction modeling that allows us to integrate physical optics models with ray trace models to directly capture the influence of ray aberrations in diffraction simulations. Polarization Ray Tracing is a ray-based method of vector field propagation that can diagnose the polarization aberrations in optical systems.

[submitted] BTSbot: Automated Identification and Follow-up of Bright Transients with Deep Learning

BTSbot is a multi-modal convolutional neural network designed for real-time identification bright extragalactic transients in Zwicky Transient Facility (ZTF) data. BTSbot provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. BTSbot is able to eliminate the need for daily visual inspection of new transients by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. BTSbot recovers all bright transients in our test split and performs on par with human experts in terms of identification speed (on average, ∼1 hour quicker than scanners).

[submitted] KCWIKit: KCWI Post-Processing and Improvements

KCWIKit extends the official KCWI DRP (ascl:2301.019) with a variety of stacking tools and DRP improvements. The software offers masking and median filtering scripts to be used while running the KCWI DRP, and a step-by-step KCWI_DRP implementation for finer control over the reduction process. Once the DRP has finished, KCWIKit can be used to stack the output cubes via the Montage package. Various functions cross-correlate and mosaic the constituent cubes and the final stacked cubes are WCS corrected. Helper functions can then be used to deproject the stacked cube into lower-dimensional representations should the user desire.

[submitted] cbeam: a coupled-mode propagator for slowly-varying waveguides

cbeam is a Python/Julia package which models the propagation of guided light through slowly-varying few-mode waveguides using the coupled-mode theory (CMT). When compared with more general numerical methods for waveguide simulation, such as the finite-differences beam propagation method (FD-BPM), numerical implementations of the CMT can be much more computationally efficient. cbeam also provides a Pythonic class structure to define waveguides, with simple classes for directional couplers and photonic lanterns already provided. Finally, cbeam doubles as a finite-element eigenmode solver.

[ascl:2402.010] 2cosmos: Monte Python modification for two independent instances of CLASS

2cosmos is a modification of Monte Python (ascl:1307.002) and allows the user to write likelihood modules that can request two independent instances of CLASS (ascl:1106.020) and separate dictionaries and structures for all cosmological and nuisance parameters. The intention is to be able to evaluate two independent cosmological calculations and their respective parameters within the same likelihood. This is useful for evaluating a likelihood using correlated datasets (e.g. mutually exclusive subsets of the same dataset for which one wants to take into account all correlations between the subsets).

[ascl:2402.009] SkyLine: Generate mock line-intensity maps

SkyLine generates mock line-intensity maps (both in 3D and 2D) in a lightcone from a halo catalog, accounting for the evolution of clustering and astrophysical properties, and observational effects such as spectral and angular resolutions, line-interlopers, and galactic foregrounds. Using a given astrophysical model for the luminosity of each line, the code paints the signal for each emitter and generates the map, adding coherently all contributions of interest. In addition, SkyLine can generate maps with the distribution of Luminous Red Galaxies and Emitting Line Galaxies.

[ascl:2402.008] star_shadow: Analyze eclipsing binary light curves, find eccentricity, and more

star_shadow automatically analyzes space based light curves of eclipsing binaries and provide a measurement of eccentricity, among other parameters. It measures the timings of eclipses using the time derivatives of the light curves, using a model of orbital harmonics obtained from an initial iterative prewhitening of sinusoids. Since the algorithm extracts the harmonics from the rest of the sinusoidal variability eclipse timings can be measured even in the presence of other (astrophysical) signals, thus determining the orbital eccentricity automatically from the light curve along with information about the other variability present in the light curve. The output includes, but is not limited to, a sinusoid plus linear model of the light curve, the orbital period, the eccentricity, argument of periastron, and inclination.

[ascl:2402.007] ECLIPSR: Automatically find individual eclipses in light curves, determine ephemerides, and more

ECLIPSR fully and automatically analyzes space based light curves to find eclipsing binaries and provide some first order measurements, such as the binary star period and eclipse depths. It provides a recipe to find individual eclipses using the time derivatives of the light curves, including eclipses in light curves of stars where the dominating variability is, for example, pulsations. Since the algorithm detects each eclipse individually, even light curves containing only one eclipse can (in principle) be successfully analyzed and classified. ECLIPSR can find eclipsing binaries among both pulsating and non-pulsating stars in a homogeneous and quick manner and process large amounts of light curves in reasonable amounts of time. The output includes, among other things, the individual eclipse markers, the period and time of first (primary) eclipse, and a score between 0 and 1 indicating the likelihood that the analyzed light curve is that of an eclipsing binary.

[ascl:2402.006] polarizationtools: Polarization analysis and simulation tools in python

polarizationtools converts, analyzes, and simulates polarization data. The different python scripts (1) convert Stokes parameters into linear polarization parameters with proper treatment of the uncertainties and vice versa; (2) shift electric vector position angle (EVPA) data points in time series to account for the 180 degrees ambiguity; (3) identify rotations of the EVPA e.g. in blazar polarization monitoring data according to various rotation definitions; and (4) simulate polarization time series as a random walk in the Stokes Q-U plane.

[submitted] TAT: Timing Analysis Toolkit for high-energy pulsar astrophysics

The TAT-pulsar (Timing Analysis Toolkit for Pulsars) package is a specialized toolkit designed for handling the scientific intricacies of pulsar timing. It provides a suite of Python-based utilities and scripts that facilitate the analysis, processing, and visualization of pulsar data. By leveraging observational data from pulsars, along with the associated physical processes and statistical characteristics, TAT-pulsar integrates a series of useful tools and data analysis scripts specifically developed for both isolated pulsars and binary systems. This enables swift analysis and the detailed presentation of timing properties in the high-energy pulsar field. Developed and implemented completely independently from other pulsar timing software such as Stingray (ascl:1608.001) and PINT (ascl:1902.007), TAT-pulsar serves as a valuable cross-checking and supplementary tool for data analysis.

[submitted] GalMOSS: A package for GPU-accelerated Galaxy Profile Fitting

We introduce GalMOSS, a Python-based, Torch-powered tool for two-dimensional fitting of galaxy profiles. By seamlessly enabling GPU parallelization, GalMOSS meets the high computational demands of large-scale galaxy surveys, placing galaxy profile fitting in the LSST-era. It incorporates widely used profiles such as the Sérsic, Exponential disk, Ferrer, King, Gaussian, and Moffat profiles, and allows for the easy integration of more complex models. Tested on 8,289 galaxies from the Sloan Digital Sky Survey (SDSS) g-band with a single NVIDIA A100 GPU, GalMOSS completed classical Sérsic profile fitting in about 10 minutes. Benchmark tests show that GalMOSS achieves computational speeds that are 6 $\times$ faster than those of default implementations.

[ascl:2402.005] MGPT: Modified Gravity Perturbation Theory code

MGPT (Modified Gravity Perturbation Theory) computes 2-point statistics for LCDM model, DGP and Hu-Sawicky f(R) gravity. Written in C, the code can be easily modified to include other models. Specifically, it computes the SPT matter power spectrum, SPT Lagrangian-biased tracers power spectrum, and the CLPT matter correlation function. MGPT also computes the CLPT Lagrangian-biased tracers correlation function and a set of Q and R functionsfrom which other statistics, as leading order bispectrum, can be constructed.

[ascl:2402.004] CCBH-Numerics: Cosmologically-coupled-black-holes formation mass numerics

CCBH-Numerics (previously called CCBH-PLPP) computes the probability of the existence of a single cosmologically coupled black hole (BH) with a formation mass below a specified threshold for given observational data of binary black holes (BBHs) from gravitational waves. The code uses the unbiased population of BBHs, as given by the power-law-plus-peak (PLPP) profile, as the observational input, and assumes that the detected BBHs are formed from stellar evolution, not primordial BHs. CCBH-Numerics also works with individual data from BBHs and for NSBH pairs as well.

[ascl:2402.003] Rwcs: World coordinate system transforms in R

Rwcs offers access to all the projection and distortion systems of WCSLIB (ascl:1108.003) in R. This can be used directly for, for example, pixel lookups, or for higher level general distortion and projection.

[ascl:2402.002] Rfits: FITS file manipulation in R

Rfits reads and writes FITS images, tables, and headers. Written in R, Rfits works with all types of compressed images, and both ASCII and binary tables. It uses CFITSIO (ascl:1010.001) for all low level FITS IO, so in general should be as fast as other CFITSIO-based software. For images, Rfits offers fully featured memory mapping and on-the-fly subsetting (by pixel and coordinate) and sparse pixel sampling, allowing for efficient inspection of very large (larger than memory) images.

[ascl:2402.001] NMMA: Nuclear Multi Messenger Astronomy framework

NMMA probes nuclear physics and cosmology with multimessenger analysis. This fully featured, Bayesian multi-messenger pipeline targets joint analyses of gravitational-wave and electromagnetic data (focusing on the optical). Using bilby (ascl:1901.011) as the back-end, the software uses a variety of samplers to sampling these data sets. NMMA uses chiral effective field theory based neutron star equation of states when performing inference, and is also capable of estimating the Hubble Constant.

[ascl:2401.020] escatter: Electron scattering in Python

escatter.py performs Monte Carlo simulations of electron scattering events. The code was developed to better understand the emission lines from the interacting supernova SN 2021adxl, specifically the blue excess seen in the Hα 6563A emission line. escatter follows a photon that was formed in a thin interface between the supernova ejecta and surrounding material as it travels radially outwards through the dense material, scattering electrons outwards until it reaches an optically thin region, and plots a histogram of the emergent photons.

[ascl:2401.019] StructureFunction: Bayesian estimation of the AGN structure function for Poisson data

StructureFunction determines the X-ray Structure Function of a population of Active Galactic Nuclei (AGN) for which two epoch X-ray observations are available and are separated by rest frame time interval. The calculation of the X-ray structure function is Bayesian. The sampling of the likelihood uses Stan (ascl:1801.003) for statistical modeling and high-performance statistical computation.

[ascl:2401.018] tidalspin: Constrain black hole spins using relativistic tidal forces properties

tidalspin uses a Bayesian approach to infer posterior distributions of a black hole's parameters (mass and spin) in an observed tidal disruption event, given a prior estimate of the black hole’s mass (e.g., from a galactic scaling relationship, or the tidal disruption event’s observed properties). These posterior distributions will only utilize the properties of tidal forces in their inference. tidalspin can be applied to the population of tidal disruption events already discovered.

[ascl:2401.017] QuantifAI: Radio interferometric imaging reconstruction with scalable Bayesian uncertainty quantification

QuantifAI reconstructs radio interferometric images using scalable Bayesian uncertainty quantification relying on data-driven (learned) priors. It relies on the convex accelerated optimization algorithms in CRR (ascl:2401.016) and is built on top of PyTorch. QuantifAI also includes MCMC algorithms for posterior sampling.

[ascl:2401.016] CRR: Convex Ridge Regularizer

CRR (Convex Ridge Regularizer) takes the gradient of regularizers that are the sum of convex-ridge functions and parameterizes them using a neural network that has a single hidden layer with increasing and learnable activation functions. The neural network is trained within a few minutes as a multistep Gaussian denoiser, and offers improvements for denoising and image reconstruction over other methods with similar reliability.

[ascl:2401.015] maskfill: Fill in masked values in an image

maskfill inward extrapolates edge pixels just outside masked regions, using iterative median filtering and the full information contained in the edge pixels. This provides seamless transitions between masked pixels and good pixels, and allows high fidelity reconstruction of gaps in continuous narrow features. An image and a mask the only required inputs.

[ascl:2401.014] LoRD: Locate Reconnection Distribution

LoRD (Locate Reconnection Distribution) identifies the locations and structures of 3D magnetic reconnection within discrete magnetic field data. The toolkit contains three main functions; the first, ARD (Analyze Reconnection Distribution) locates the grids undergoing reconnection without null points and also recognizes the local configurations of reconnection sites. ANP (Analyze Null Points) locates and classifies the 3D null points, and APNP (Analyze Projected Null Points) analyzes the 2D neutral points projected on a plane near a cell. LoRD is written in Matlab and the toolkit contains demo scripts.

[ascl:2401.013] SolarKAT: Solar imaging pipeline for MeerKAT

SolarKAT mitigates solar interference in MeerKAT data and recovers the visibilities rather than discarding them; this solar imaging pipeline takes 1GC calibrated data in Measurement Set format as input. Written in Python, the pipeline employs solar tracking, subtraction, and peeling techniques to enhance data quality by significantly reducing solar radio interference. This is achieved while preserving the flux measurements in the main field. SolarKAT is versatile and can be applied to general radio astronomy observations and solar radio astronomy; additionally, generated solar images can be used for weather forecasting. SolarKAT is deployed in Stimela (ascl:2305.007). It is based on existing radio astronomy software, including CASA (ascl:1107.013), breizorro (ascl:2305.009), WSclean (ascl:1408.023), Quartical (ascl:2305.006), and Astropy (ascl:1304.002).

[ascl:2401.012] baryon-sweep: Outlier rejection algorithm for JWST/NIRSpec IFS data

baryon-sweep produces a robust outlier rejection while simultaneously preserving the signal of the science target. The code works as a standalone solution or as a supplement to the current pipeline software. baryon-sweep creates the 2D pixel mask and mask layers, processes the sky (non-science target) spaxels, and creates a post-processed cube ready for use.

[ascl:2401.011] ostrich: Surrogate modeling using PCA and Gaussian process interpolation

Ostrich emulates surrogate models for complex and expensive functions using Principal Component Analysis (PCA) to decompose a signal, then interpolate the PCA weights over the parameters θ using a Gaussian Process interpolator. The code is trained on samples from the expensive functions, recreating and interpolating between those training samples with reduced computational cost, and recalculating for each use.

[ascl:2401.010] SYSNet: Neural Network modeling of imaging systematics in galaxy surveys

The Feed Forward Neural Network SYSNet models the relationship between the imaging maps, such as stellar density and the observed galaxy density field, in order to mitigate the systematic effects and to make a robust galaxy clustering measurements. The cost function is Mean Squared Error and a L2 regularization term, and the optimization algorithm is Adaptive Moment (ADAM).

[ascl:2401.009] Harmonic: Learnt harmonic mean estimator

harmonic learns an approximate harmonic mean estimator (referred to as a "learnt harmonic mean estimator") from posterior distribution samples to compute the marginal likelihood required for Bayesian model selection. Using a large number of independent Markov chain Monte Carlo (MCMC) chains from another package such as emcee (ascl:1303.002), harmonic uses importance sampling to learn a new target distribution in order to optimize an approximate harmonic estimator while minimizing its variance.

[ascl:2401.008] DARC: Dirac Atomic R-matrix Codes

DARC (Dirac Atomic R-matrix Codes) enables the study of continuum processes for a general atomic system. The suite of programs calculate electron-atom or electron-ion collision cross-sections. In addition, the programs include code for bound-state and photoionization calculations.

[ascl:2401.007] deal.II: Finite element library

deal.II computes solutions to partial differential equations (PDEs) using adaptive finite elements. The code provides an interface for processing PDEs accessible to both laptops and supercomputers, and has been used to investigate the local and global waveform effects of gravitational waves by numerical simulation. deal.II supports massively parallel computing of very large linear systems of equations and provides access to triangulation of various geometries of the simulation domain.

[ascl:2401.006] LoSoTo: LOFAR solutions tool

LoSoTo (LOFAR Solution Tool) performs a variety of operations on H5parm data, which is based on the HDF5 format; it isolates direction independent systematic effects and can therefore be transferred to the target field. Subsets of data can be selected for each operation using lists of axes values, regular expressions, or intervals. The LoSoTo package stores solutions in arrays organized in a hierarchical fashion; this provides flexibility and preserves performance. The code can, for example, extract Faraday rotation from RR/LL phase solutions or a rotation matrix, clip solutions around the median, and calculate the ionospheric structure function. LoSoTo includes an outlier flagging procedure, normalizes solutions to a given value, and offers an advanced plotting routine, and many other operations.

[ascl:2401.005] CosmosCanvas: Useful color maps for different astrophysical properties

CosmosCanvas creates perception-based color maps for different astrophysical properties such as spectral index and velocity fields. Three tutorials demonstrate how to use python code to exploit and adjust the boundaries in these divergent colour schemes. Intended to work with human physiology, each tutorial offers at least one default scheme that is monotonic in value both as a redundancy for supporting data information and an aid for colour blind viewers. This library relies on Gilles Ferrand's colourspace library.

[ascl:2401.004] pyPETaL: A Pipeline for Estimating AGN Time Lags

pyPETAL produces cross-correlation functions, discrete correlation functions, and mean time lags from multi-band AGN time-series data, combining multiple different codes (including pyCCF (ascl:1805.032), pyZDCF, PyROA (ascl:2107.012), and JAVELIN (ascl:1010.007)) used for active galactic nuclei (AGN) reverberation mapping (RM) analysis into a unified pipeline. This pipeline also implements outlier rejection using Damped Random Walk Gaussian process fitting, and detrending through the LinMix algorithm. pyPETAL implements a weighting scheme for all lag-producing modules, mitigating aliasing in peaks of time lag distributions between light curves. pyPETAL scales to any combination of internal code modules, supporting a variety of computational workflows.

[ascl:2401.003] LUNA: Forward model luna simulator

LUNA generates dynamically accurate lightcurves from a planet-moon pair, analytically accounting for shadow overlaps, stellar limb darkening, and planet-moon dynamical motion. The code takes transit timing/duration variations and ingress/egress asymmetries into consideration not only for the planet, but also the moon. LUNA was designed to be analytical and dynamical and to incorporate limb darkening (including non-linear laws) and account for all orbital elements, including eccentricity and longitude of the ascending node. Because the software is precise and analytic, LUNA is a highly potent tool for exomoon detection.

[ascl:2401.002] Rayleigh: Pseudo-spectral MHD

The 3-D convection code Rayleigh enables study of dynamo behavior in spherical geometry. It evolves the incompressible and anelastic MHD equations in spherical geometry using a pseudo-spectral approach. Rayleigh employs spherical harmonics in the horizontal direction and Chebyshev polynomials in the radial direction and has undergone extensive accuracy testing.

[ascl:2401.001] tomso: TOols for Models of Stars and their Oscillations

tomso loads and saves input and output files for and from stellar evolution and oscillation codes. The functions are bundled together in modules that correspond with a specific stellar evolution code, stellar oscillation code, or file format. tomso supports the FGONG format and various input/output files for ADIPLS (ascl:1109.002), GYRE (ascl:1308.010), MESA (ascl:1010.083), and STARS (ascl:1107.008). tomso's main purpose is to provide a compact interface for manipulating input and output data in these formats and simplify research that uses them.

[submitted] BSAVI: Bayesian Sample Visualizer for Cosmological Likelihoods

BSAVI (Bayesian Sample Visualizer) is a tool to aid likelihood analysis of model parameters where samples from a distribution in the parameter space are used as inputs to calculate a given observable. For example, selecting a range of samples will allow you to easily see how the observables change as you traverse the sample distribution. At the core of BSAVI is the Observable object, which contains the data for a given observable and instructions for plotting it. It is modular, so you can write your own function that takes the parameter values as inputs, and BSAVI will use it to compute observables on the fly. It also accepts tabular data, so if you have pre-computed observables, simply import them alongside the dataset containing the sample distribution to start visualizing.

[submitted] NE2001p: A Native Python Implementation of the NE2001 Galactic Electron Density Model

NE2001p is a fully Python implementation of the NE2001 Galactic electron density model. NE2001p forward models the dispersion and scattering of compact radio sources, including pulsars, fast radio bursts, AGNs, and masers, and the model predicts the distances of radio sources that lack independent distance measures.

[ascl:2312.036] SubGen2: Subhalo population generator

The SubGen2 subhalo population generator works for both CDM and WDM of arbitrary DM particle mass. It can be used to generate a population of subhaloes according to the joint distribution of subhalo bound mass, infall mass and halo-centric distance in a halo of a given mass. SubGen2 is an extension to SubGen (ascl:2312.035), which works only for CDM subhaloes.

[ascl:2312.035] SubGen: Fast subhalo sampler

SubGen generates Monte-Carlo samples of dark matter subhaloes. It fully describes the joint distribution of subhaloes in final mass, infall mass, and radius; it can be used to predict derived distributions involving combinations of these quantities, including the universal subhalo mass function, the subhalo spatial distribution, the gravitational lensing profile, the dark matter annihilation radiation profile and boost factor. SubGen works only for CDM subhaloes; for an extension of the code to also work with WDM subhaloes, see SubGen2 (ascl:2312.036).

[ascl:2312.033] RADIS: Fast line-by-line code for high-resolution infrared molecular spectra

RADIS resolves spectra with millions of lines within seconds on a single-CPU and can be GPU-accelerated. It supports HITRAN, HITEMP and ExoMol out-of-the-box (auto-download), and therefore is particularly suitable to compute cross-sections or transmission spectra at high-temperature. RADIS includes equilibrium calculations for all species, and non-LTE for CO2 and CO.

[ascl:2312.032] gaia_tools: Tools for working with Gaia and related data sets

gaia_tools contains codes for working with the ESA/Gaia data and related data sets (APOGEE, GALAH, LAMOST DR2, and RAVE). Written in Python, it includes tools to read catalogs, perform cross-matching, read RVS or XP spectra, and query the Gaia archive. gaia_tools also contains various matching recipes, such as matching APOGEE or APOGEE-RC to Gaia DR2, and RAVE to TGAS (taking into account the epoch difference).

[ascl:2312.031] AM3: Astrophysical Multi-Messenger Modeling

AM3 simulates lepto-hadronic interactions in astrophysical environments. It solves the time-dependent partial differential equations for the energy spectra of electrons, positrons, protons, neutrons, photons, neutrinos as well as charged secondaries (pions and muons), immersed in an isotropic magnetic field. The code accounts for the emission of photons and charged secondaries in electromagnetic and hadronic interactions feed back into the interaction rates in a time-dependent manner, therefore grasping non-linear effects including electromagnetic cascades. AM3 is computationally efficient, making it possible to scan vast source parameter scans and fit the observational data, and has been deployed to explain multi-wavelength observations from blazars, gamma-ray bursts and tidal disruption events.

[ascl:2312.030] matvis: Fast matrix-based visibility simulator
Kittiwisit, Piyanat; Murray, Steven G.; Garsden, Hugh; Bull, Philip; Cain, Christopher; Parsons, Aaron R.; Sipple, Jackson; Abdurashidova, Zara; Adams, Tyrone; Aguirre, James E.; Alexander, Paul; Ali, Zaki S.; Baartman, Rushelle; Balfour, Yanga; Beardsley, Adam P.; Berkhout, Lindsay M.; Bernardi, Gianni; Billings, Tashalee S.; Bowman, Judd D.; Bradley, Richard F.; Burba, Jacob; Carey, Steven; Carilli, Chris L.; Chen, Kai-Feng; Cheng, Carina; Choudhuri, Samir; DeBoer, David R.; de Lera Acedo, Eloy; Dexter, Matt; Dillon, Joshua S.; Dynes, Scott; Eksteen, Nico; Ely, John; Ewall-Wice, Aaron; Fagnoni, Nicolas; Fritz, Randall; Furlanetto, Steven R.; Gale-Sides, Kingsley; Gehlot, Bharat Kumar; Ghosh, Abhik; Glendenning, Brian; Gorce, Adelie; Gorthi, Deepthi; Greig, Bradley; Grobbelaar, Jasper; Halday, Ziyaad; Hazelton, Bryna J.; Hewitt, Jacqueline N.; Hickish, Jack; Huang, Tian; Jacobs, Daniel C.; Josaitis, Alec; Julius, Austin; Kariseb, MacCalvin; Kern, Nicholas S.; Kerrigan, Joshua; Kim, Honggeun; Kohn, Saul A.; Kolopanis, Matthew; Lanman, Adam; La Plante, Paul; Liu, Adrian; Loots, Anita; Ma, Yin-Zhe; MacMahon, David H. E.; Malan, Lourence; Malgas, Cresshim; Malgas, Keith; Marero, Bradley; Martinot, Zachary E.; Mesinger, Andrei; Molewa, Mathakane; Morales, Miguel F.; Mosiane, Tshegofalang; Neben, Abraham R.; Nikolic, Bojan; Devi Nunhokee, Chuneeta; Nuwegeld, Hans; Pascua, Robert; Patra, Nipanjana; Pieterse, Samantha; Qin, Yuxiang; Rath, Eleanor; Razavi-Ghods, Nima; Riley, Daniel; Robnett, James; Rosie, Kathryn; Santos, Mario G.; Sims, Peter; Singh, Saurabh; Storer, Dara; Swarts, Hilton; Tan, Jianrong; Thyagarajan, Nithyanandan; van Wyngaarden, Pieter; Williams, Peter K. G.; Xu, Zhilei; Zheng, Haoxuan

matvis simulates radio interferometric visibilities at the necessary scale with both CPU and GPU implementations. It is matrix-based and applicable to wide field-of-view instruments such as the Hydrogen Epoch of Reionization Array (HERA) and the Square Kilometre Array (SKA), as it does not make any approximations of the visibility integral (such as the flat-sky approximation). The only approximation made is that the sky is a collection of point sources, which is valid for sky models that intrinsically consist of point-sources, but is an approximation for diffuse sky models. The matvix matrix-based algorithm is fast and scales well to large numbers of antennas. The code supports both CPU and GPU implementations as drop-in replacements for each other and also supports both dense and sparse sky models.

[ascl:2312.029] RRLFE: Metallicity calibrations for RR Lyrae variable stars

RRLFE generates and applies calibrations for retrieving [Fe/H] from low-res spectra of RR Lyrae variable stars. The code can generate a metallicity calibration anew, from real or synthetic spectra; it can also apply a metallicity calibration to low-resolution (R ~2000) RR Lyrae spectra spanning 3911 to 4950 angstroms.

[ascl:2312.028] SAGE: Stellar Activity Grid for Exoplanets

SAGE corrects the time-dependent impact of stellar activity on transmission spectra. It uses a pixelation approach to model the stellar surface with spots and faculae, while accounting for limb-darkening and rotational line-broadening. The code can be used to evaluate stellar contamination for F to M-type hosts, test various spot sizes and locations, and quantify the impact of limb-darkening. SAGE can also retrieve the properties and distribution of active regions on the stellar surface from photometric monitoring, and connect the photometric variability to the stellar contamination of transmission spectra.

[ascl:2312.027] galclaim: GALaxy Chance of Local Alignment algorIthM

galclaim identifies association between astrophysical transient sources and host galaxy. This association is made by estimating the chance alignment between a given transient sky localization and nearby galaxies. The code can be used with various catalogs, including Pan-STARRS, HSC, AllWISE and GLADE. galclaim also pre-checks for nearby bright galaxy using the RC3 catalog (https://heasarc.gsfc.nasa.gov/w3browse/all/rc3.html). When a nearby galaxy is found, a warning is raised and the properties of the galaxy are saved in a dedicated output file. The package can create plots displaying the computed pval for the found objects for each transient and each catalog; plots are stored in the result/plots directory.

[ascl:2312.026] CloudFlex: Small-scale structure observational signatures modeling

CloudFlex models observational signatures associated with the small-scale structure of the circumgalactic medium. It populates cool gas structures in the CGM as a complex of cloudlets using a Monte Carlo method. Various parameters can be set to describe the structure of the cloudlet complexes, including cloudlet mass, density, velocity, and size. Functionality exists for generating the observational signatures of sightlines piercing these cloudlet complexes, borrowing heavily from the Trident code (ascl:1612.019).

[ascl:2312.025] pyC2Ray: Python interface to C2Ray with GPU acceleration

pyC2Ray updates C2-Ray (ascl:2312.022), an astrophysical radiative transfer code used to simulate the Epoch of Reionization (EoR). pyC2Ray includes a new raytracing method, ASORA, developed for GPUs, and provides a Python interface for customizable use of the code. The core features of C2-Ray, written in Fortran90, are wrapped using f2py as a Python extension module, while the raytracing library ASORA is implemented in C++ using CUDA. Both are native Python C-extensions and can be directly accessed from any Python script.

[ascl:2312.024] C2-Ray3Dm1D_Helium: Hydrogen + helium version of C2-Ray

C2-Ray3Dm1D_Helium is the hydrogen + helium version of the radiative transfer photo-ionization code C2-Ray. It combines the 1D and 3D versions of the code.

[ascl:2312.023] C2-Ray3Dm: 3D version of C2-Ray for multiple sources, hydrogen only

C2-Ray3Dm performs time-dependent photo-ionization calculations for 3D multiple sources, and for hydrogen only. Based on C2-Ray (ascl:2312.022), it runs under both MPI and OpenMP. The length of subroutines has been reduced to make the code more manageable and easier to read.

[ascl:2312.022] C2-Ray: Time-dependent photo-ionization calculations

C2-Ray calculates spherical symmetric time-dependent photo-ionization in 1D with the source at the origin for hydrogen only. The code is explicitly photon-conserving and uses an analytical relaxation solution for the ionization rate equations for each time step, thus enabling integration of the equation of transfer along a ray with fewer cells and time steps than previous methods. It is suitable for coupling radiative transfer to gas and N-body dynamics methods on fixed or adaptive grids. C2-Ray is not parallelized but contains an MPI module for compatibility with the 3D version (C2-Ray3Dm).

[ascl:2312.021] PyRaTE: Non-LTE spectral lines simulations

PyRaTE (Python Radiative Transfer Emission) post-processes astrochemical simulations. This multilevel radiative transfer code uses the escape probablity method to calculate the population densities of the species under consideration. The code can handle all projection angles and geometries and can also be used to produce mock observations of the Goldreich-Kylafis effect. PyRaTE is written in Python; it uses a parallel strategy and relies on the YT analysis toolkit (ascl:1011.022), mpi4py and numba.

[ascl:2312.020] ProPane: Image warping and stacking utilities

The ProPane package comes with key utilities for warping between different WCS systems: propaneWarp (for warping individual frames once). ProPane also contains the various functions for creating large stacks of many warped frames (which is of class ProPane, which is roughly meant to suggest the idea of many panes of glass being stacked together). It uses the wcslib C library (ascl:1108.003) for projections (all legal ones are supported) via the Rwcs package, and uses the threaded Cimg C++ library via the imager library to do image warping. ProPane also contains functions converted from older (deprecated) Rwcs and ProFound (ascl:1804.006) related functions.

[ascl:2312.019] Rainbow: Simultaneous multi-band light curve fitting

Rainbow is a black-body parametric model for transient light curves. It uses Bazin function as a model for bolometric flux evolution and a logistic function for the temperature evolution; it provides seven fit parameters and goodness of fit (reduced χ2) and is well-suited for transient objects. Also included is RainbowRisingFit, suitable for rising transient objects, which offers six fit parameters. It is based on a rising sigmoid bolometric flux and a sigmoid temperature evolution. These implementations are implemented in the light-curve processing toolbox (ascl:2107.001) for Python.

[ascl:2312.018] PyMsOfa: Python package for the Standards of Fundamental Astronomy (SOFA) service

PyMsOfa accesses the International Astronomical Union’s SOFA library (ascl:1403.026) from Python. It offers a wrapper package based on a foreign function library for Python (ctypes), a wrapper with the foreign function interface for Python calling C code (cffi), and a package directly written in pure Python codes from SOFA subroutines. PyMsOfa is suitable for the astrometric detection of habitable planets of the Closeby Habitable Exoplanet Survey (CHES) mission and for the frontier themes of black holes and dark matter related to astrometric calculations and other fields.

[ascl:2312.017] LimberJack.jl: Auto-differentiable methods for cosmology

LimberJack.jl performs cosmological analyses of 2 point auto- and cross-correlation measurements from galaxy clustering, CMB lensing and weak lensing data. Written in Julia, it obtains gradients for its outputs faster than traditional finite difference methods, making the code greatly synergistic with gradient-based sampling methods such as Hamiltonian Monte Carlo. LimberJack.jl can efficiently exploring parameter spaces with hundreds of dimensions.

[ascl:2312.016] The Farmer: Photometry routines for deep multi-wavelength galaxy surveys

The Farmer contains photometry routines geared towards deep, multi-wavelength galaxy surveys. It fits simple parametric surface brightness profiles provided by The Tractor (ascl:1604.008) to measure precision photometry even in deeply crowded fields when provided with a suitable high resolution detection image. The Farmer has been used to build a number of galaxy survey catalogs including COSMOS202, SHELA, and H20.

[ascl:2312.015] SUNBIRD: Neural-network-based models for galaxy clustering

SUNBIRD trains neural-network-based models for galaxy clustering. It also incorporates pre-trained emulators for different summary statistics, including galaxy two-point correlation function, density-split clustering statistics, and old-galaxy cross-correlation function. These models have been trained on mock galaxy catalogs, and were calibrated to work for specific samples of galaxies. SUNBIRD implements routines with PyTorch to train new neural-network emulators.

[ascl:2312.014] GRFolres: Extension to GRChombo for modified gravity simulations

GRFolres performs simulations in modified theories of gravity. It is based on GRChombo (ascl:2306.039) and inherits all of the capabilities of the main GRChombo code, which makes use of the Chombo library (ascl:1202.008) for adaptive mesh refinement. The code implements the 4∂ST theory of modified gravity and the cubic Horndeski theory in (3+1)-dimensional numerical relativity. GRFolres can be used for stable gauge evolution, solving the modified energy and momentum constraints for initial conditions, and monitoring the constraint violation and calculating the energy densities associated with the different scalar terms in the action. It can also extract data for the tensor and scalar gravitational waveforms.

[ascl:2312.013] 21cmEMU: 21cmFAST summaries emulator

21cmEMU emulates 21cmFAST (ascl:1102.023) summary statistics, among them the 21-cm power spectrum, 21-cm global brightness temperature, IGM spin temperature, and neutral fraction. It also emulates the Thomson scattering optical depth and UV luminosity functions. With 21cmFAST installed, parameters can be supplied direction to 21cmEMU, and 21cmEMU can be used for, for example, analytic calculations of taue and UV luminosity functions. The code is included as an alternative simulator in 21cmMC (ascl:1608.017).

[ascl:2312.012] PulsarX: Pulsar searching

The folding pipeline PulsarX searches for pulsars. The code includes radio frequency interference mitigation, de-dispersion, folding, and parameter optimization, and supports both psrfits and filterbank data formats. The toolset has two implementations of the folding pipelines; one uses a brute-force de-dispersion algorithm, and the other an algorithm that becomes more efficient than the brute-force de-dispersion algorithm as the number of candidates increases. PulsarX is appropriate for large-scale pulsar surveys.

[ascl:2312.011] PhotochemPy: 1-D photochemical model of rocky planet atmospheres

PhotochemPy finds the steady-state chemical composition of an atmosphere or evolves atmospheres through time. Given inputs such as the stellar UV flux and atmospheric temperature structure, the code creates a photochemical model of a planet's atmosphere. PhotochemPy is a distant fork of Atmos (ascl:2106.039). It provides a Python wrapper to Fortran source code but can also be used exclusively in Fortran.

[ascl:2312.010] FORECAST: Realistic astronomical image and galaxy survey generator

FORECAST generates realistic astronomical images and galaxy surveys by forward modeling the output snapshot of any hydrodynamical cosmological simulation. It exploits the snapshot by constructing a lightcone centered on the observer's position; the code computes the observed fluxes of each simulated stellar element, modeled as a Single Stellar Population (SSP), in any chosen set of pass-band filters, including k-correction, IGM absorption, and dust attenuation. These fluxes are then used to create an image on a grid of pixels, to which observational features such as background noise and PSF blurring can be added. FORECAST provides customizable options for filters, size of the field of view, and survey parameters, thus allowing the synthetic images to be tailored for specific research requirements.

[ascl:2312.009] GravSphere: Jeans modeling code

The non-parametric Jeans code GravSphere models discrete data and can be used to model dark matter distributions in galaxies. It can also recover the density ρ(r) and velocity anisotropy β(r) of spherical stellar systems, assuming only that they are in a steady state. Real or mock data are prepared by using the included binulator.py code; the repository also includes many examples for exploring the GravSphere's capabilities.

[ascl:2312.008] CompressedFisher: Library for testing Fisher forecasts

The CompressedFisher library tests whether Fisher forecasts using simulated components are converged. The library contains tools to compute standard Fisher estimates, estimate the level of bias due to the finite number of simulations, and compute the compressed Fisher information. Typical usage of CompressedFisher requires two ensembles of simulations: one set of simulations is given at the fiducial parameters (𝜃) to estimate the covariance matrix. The second is a set of simulated derivatives; these can either be in the form of realizations of the derivatives themselves or simulations evaluate at a set of point in the neighborhood of the fiducial point that the code can use to estimate the derivatives.

[ascl:2312.007] CosmoLED: Cosmo code for Large Extra Dimension (LED) black holes

CosmoLED computes Hawking evaporation from black holes and set constraints on the fraction of black holes in dark matter. Based on ExoCLASS (ascl:1106.020), the code provides a DarkAges_LED module and C codes in class_LED to compute the evolution and energy deposition functions from LED black holes. Though CosmoLED is designed for large extra dimension black holes, it can also be used to study 4D black holes.

[ascl:2312.006] SolarAxionFlux: Solar axion flux calculator for different solar models and opacity codes

SolarAxionFlux quantifies systematic differences and statistical uncertainties in the calculation of the solar axion flux from axion-photon and axion-electron interactions. Determining the limitations of these calculations can be used to identify potential improvements and help determine axion model parameters more accurately.

[ascl:2312.005] LyaCoLoRe: Generate simulated Lyman alpha forest spectra

LyaCoLoRe uses CoLoRe (ascl:2111.009) simulations to generate simulated Lyman alpha forest spectra. The code takes the output files from CoLoRe as an input, carries out several stages of processing, and produces realistic skewers of transmitted flux fraction as an output. The repository includes tools to tune the parameters within LyaCoLoRe's transformation, and to measure the 1D power spectrum of output skewers quickly.

[ascl:2312.004] DENSe: Bayesian density estimation for Poisson data

DENSe enables Bayesian non-parametric inferences of densities of Poisson data counts. Its framework of stateless methods is written in Python, although it relies on NIFTy (ascl:1302.013, ascl:1903.008) for the heavy lifting. DENSe utilizes all available information in the data by modeling the inherent correlation structure using a Matérn kernel. The inference of the density from count data can be written in a single line of python code. The fitting method takes a multidimensional numpy array as input and returns multidimensional arrays of the same dimensions encoding the density field.

[ascl:2312.003] BUQO: Bayesian Uncertainty Quantification by Optimization

BUQO solves large-scale imaging inverse problems. It leverages probability concentration phenomena and the underlying convex geometry to formulate the Bayesian hypothesis test as a convex problem that is then efficiently solved by using scalable optimization algorithms. This allows scaling to high-resolution and high-sensitivity imaging problems that are computationally unaffordable for other Bayesian computation approaches.

[ascl:2312.002] PROSPECT: Profile likelihood for frequentist cosmological inference

PROSPECT infers cosmological parameters using profile likelihoods. It constructs an approximate profile likelihood from an MCMC and optimizes it using simulated annealing, a gradient-free stochastic optimization algorithm. It employs an automatic tuning of the step size parameter and binned covariance matrices from the MCMC to achieve efficient optimizations of the profile likelihood.

[ascl:2312.001] smops: A sub-band model FITS image interpolator

smops interpolates input sub-band model FITS images, such as those produced by WSClean (ascl:1408.023), into more finely channelized sub-band model FITS images, thus generating model images at a higher frequency resolution. It is a Python-based command line tool. For example, given input model FITS images initially created from sub-dividing a given bandwidth into four, smops can subdivide that bandwidth further, resulting in more finely channelized model images, to a specified frequency resolution. This smooths out the stepwise behavior of models across frequency, which can improve the results of self-calibration with such models.

[submitted] prodimopy: Python tools for the radiation thermo-chemical code ProDiMo.

prodimopy is an open-source Python package to read, analyze and plot modelling results of the radiation thermo-chemical disk code ProDiMo (PROtoplanetary DIsk MOdel, https://prodimo.iwf.oeaw.ac.at). It also includes tools to run ProDiMo in 1D slap model mode, to run simple ProDimo model grids and to interface ProDiMo with 1D and 2D disk codes (i.e. use input structure from hydrodynamic models).

prodimopy can also be used independently of ProDiMo (no ProDiMo installation is required) and hence is also useful to extract information from already available ProDiMo models (e.g. as input for other codes) or for model comparison.

[ascl:2311.016] RoSSBi3D: Finite volume code for protoplanetary disk evolution study

The numerical code RoSSBi3D (Rotating Systems Simulation Code for Bi-fluids) is designed for protoplanetary discs study at 2D and 3D. It is a finite volume code which is second order in time, features self-gravity (2D), and uses an exact Riemann solver to account for discontinuities. This FORTRAN 90 code solves the fully compressible inviscid Euler, continuity and energy conservation equations in polar coordinates for an ideal gas orbiting a central object. Solid particles are treated as a pressureless fluid and interact with the gas through aerodynamic forces. The code works on high performance computers thanks to the MPI standard (CPU).

[ascl:2311.015] nemiss: Neutrino emission from hydrocode data

nemiss calculates neutrino emission from an astrophysical jet. nemiss works as part of the PLUTO-nemiss-rlos pipeline. PLUTO (ascl:1010.045) produces a hydrodynamical jet. Then, nemiss calculates beamed neutrino emission at each eligible cell along a given direction in space. Finally, rlos (ascl:1811.009) produces a synthetic neutrino image of the jet along the given direction, taking into consideration the finite nature of the speed of light.

[ascl:2311.014] FASMA: Stellar spectral analysis package

FASMA delivers the atmospheric stellar parameters (effective temperature, surface gravity, metallicity, microturbulence, macroturbulence, and rotational velocity) based on the spectral synthesis technique. This technique relies on the comparison of synthetic spectra with observations to yield the best-fit parameters under a χ2 minimization process. FASMA also delivers chemical abundances of 13 elements. Written in Python, the code is wrapped around MOOG (ascl:1202.009) which calculates the synthetic spectra. FASMA includes two grids of models in MOOG readable format, Kurucz and marcs, that cover the parameter space for both dwarf and giant stars with metallicity limit of -5.0 dex.

[ascl:2311.013] pygwb: Lighweight python stochastic GWB analysis pipeline

pygwb analyzes laser interferometer data and designs a gravitational wave background (GWB) search pipeline. Its modular and flexible codebase is tailored to current ground-based interferometers such as LIGO Hanford, LIGO Livingston, and Virgo, but can be generalized to other configurations. It is based on GWpy (ascl:1912.016) and bilby (ascl:1901.011) for optimal integration with widely-used gravitational wave data analysis tools. pygwb also includes a set of scripts to analyze data and perform large-scale searches on a high-performance computing cluster efficiently.

[ascl:2311.012] CosmoLattice: Lattice simulator of scalar and gauge field dynamics in an expanding universe

CosmoLattice performs lattice simulations of field dynamics in an expanding universe. The code can simulate the dynamics of interacting scalar field theories, Abelian U(1) gauge theories, and non-Abelian SU(2) gauge theories, either in flat spacetime or an expanding FLRW background, including the case of self-consistent expansion sourced by the fields themselves. It can also compute gravitational waves sourced by U(1) Abelian Gauge fields. The CosmoLattice platform can implement any system of dynamical equations suitable for discretization on a lattice, as it introduces its own language describing fields and operations between them, and hence can implement new libraries to solve arbitrary field problems (related or not to cosmology).

[ascl:2311.011] PIPPIN: Polarimetric Differential Imaging (PDI) pipeline for NACO data

PIPPIN (PDI pipeline for NACO data) reduces the polarimetric observations made with the VLT/NACO instrument. It applies the Polarimetric Differential Imaging (PDI) technique to distinguish the polarized, scattered light from the (largely) un-polarized, stellar light. As a result, circumstellar dust can be uncovered. PIPPIN appropriately handles various instrument configurations, including half-wave plate and de-rotator usage, Wollaston beam-splitter, and wiregrid observations. As part of the PDI reduction, PIPPIN performs various levels of corrections for instrumental polarization and crosstalk.

[ascl:2311.010] FPFS: Fourier Power Function Shaplets

FPFS (Fourier Power Function Shaplets) is a fast, accurate shear estimator for the shear responses of galaxy shape, flux, and detection. Utilizing leading-order perturbations of shear (a vector perturbation) and image noise (a tensor perturbation), the code determines shear and noise responses for both measurements and detections. Unlike methods that distort each observed galaxy repeatedly, the software employs analytical shear responses of select basis functions, including Shapelets basis and peak basis. FPFS is efficient and can process approximately 1,000 galaxies within a single CPU second, and maintains a multiplicative shear estimation bias below 0.5% even amidst blending challenges.

[ascl:2311.009] Hi-COLA: Cosmological large-scale structure simulator for Horndeski theories

Hi-COLA runs fast approximate N-body simulations of non-linear structure formation in reduced Horndeski gravity (Horndeski theories with luminal gravitational waves). It is generic with respect to the reduced Horndeski class. Given an input Lagrangian, Hi-COLA's front-end dynamically constructs the appropriate field equations and consistently solves for the cosmological background, linear growth, and screened fifth force of that theory. This is passed to the back-end, which runs a hybrid N-body simulation at significantly reduced computational and temporal cost compared to traditional N-body codes. By analyzing the particle snapshots, one can study the formation of structure through statistics such as the matter power spectrum.

[ascl:2311.008] IQRM: IQRM interference flagging algorithm for radio pulsar and transient searches

IQRM implements the Inter-Quartile Range Mitigation (IQRM) interference flagging algorithm for radio pulsar and transient searches. This module provides only the algorithm that infers a channel mask from some spectral statistic that measures the level of RFI contamination in a time-frequency data block. It should be useful as a reference implementation to developers who wish to integrate IQRM into an existing pipeline or search code.

[ascl:2311.007] tensiometer: Test a model until it breaks

Tensiometer provides non-Gaussian tension estimators that extend GetDist (ascl:1910.018) capabilities to test the level of agreement or disagreement between different posterior distributions by using kernel density estimates. The code has been used to study the level of internal agreement between different measurements of the clustering of cosmological structures from the Dark Energy Survey and the Planck satellite.

[ascl:2311.006] MONDPMesh: Particle-mesh code for Milgromian dynamics

MONDPMesh provides a particle-mesh method to calculate the time evolution of an system of point masses under modified gravity, namely the AQUAL formalism. This is done by transforming the Poisson equation for the potential into a system of four linear PDEs, and solving these using fast Fourier transforms. The accelerations on the point masses are calculated from this potential, and the system is propagated using Leapfrog integration. The time complexity of the code is O(N⋅p⋅log(p)) for p pixels and N particles, which is the same as for a Newtonian particle-mesh code.

[ascl:2311.005] NEOexchange: Target and Observation Manager for the Solar System

The NEOexchange web portal and Target and Observation Manager ingests solar system objects, including Near-Earth Object (NEO) candidates from the Minor Planet Center, schedules observations on the Las Cumbres Observatory global telescope network and reduces, displays, and analyzes the resulting data. NEOexchange produces calibrated photometry from the imaging data and uses Source Extractor (ascl:1010.064) and SCAMP (ascl:1010.063) to perform object detection and astrometric fitting and calviacat (ascl:2207.015) to perform photometric calibration against photometric catalogs. It also has the ability to perform image registration and subtraction using SWARP (ascl:1010.068) and HOTPANTS (ascl:1504.004) and image stacking, alignment, and faint feature detection using gnuastro (ascl:1801.009).

[ascl:2311.004] KvW: Modified Kwee–Van Woerden method for eclipse minimum timing with reliable error estimates

The KvW code applies the Kwee Van Woerden (KvW) method for eclipse or transit minimum timing, with an improved error calculation that avoids underestimated errors in minimum times that may appear in the original method. This is particularly the case for low-noise eclipse or transit lightcurves from space or from modern ground instrumentation. The code requires an input light curve of near-equidistant points that contains only the eclipse, without any off-eclipse points, and is available in python and IDL. Both implementaitons return an eclipse minimum time with its error and provide optional text output and plots, as well as several levels of debug information.

[submitted] atlas-fit

atlas-fit is a python tool to amend the results of [spectroflat] with calibration against a solar atlas. I.e., data for wavelength calibration and continuum-correction is genereted from flat field information and selected solar atlantes

[submitted] spectroflat

Spectroflat is a generic python calibration library for spectro-polarimetric data. It can be plugged into existing python based data reduction pipelines or used as a standalone calibration and performance ananlzsis tool.
It includes smile distortion correction and flat field extraction.

[submitted] CRPropa 3.2

The landscape of high- and ultra-high-energy astrophysics has changed in the last decade, largely due to the inflow of data collected by large-scale cosmic-ray, gamma-ray, and neutrino observatories. At the dawn of the multimessenger era, the interpretation of these observations within a consistent framework is important to elucidate the open questions in this field. CRPropa 3.2 is a Monte Carlo code for simulating the propagation of high-energy particles in the Universe. This version represents a major leap forward, significantly expanding the simulation framework and opening up the possibility for many more astrophysical applications. This includes, among others: efficient simulation of high-energy particles in diffusion-dominated domains, self-consistent and fast modelling of electromagnetic cascades with an extended set of channels for photon production, and studies of cosmic-ray diffusion tensors based on updated coherent and turbulent magnetic-field models. Furthermore, several technical updates and improvements are introduced with the new version, such as: enhanced interpolation, targeted emission of sources, and a new propagation algorithm (Boris push). The detailed description of all novel features is accompanied by a discussion and a selected number of example applications.

[ascl:2311.003] Special-Blurring: Compare quantum-spacetime foam models to GRB localizations

The IDL code Special-Blurring compares models of quantum-foam-induced blurring with the full dataset of gamma-ray burst localizations available from the NASA High Energy Astrophysics Science Research Archive (as of 1 November 2022). This includes GRB221009A, which was especially bright and detected in extremely high energy TeV gamma-rays. An upper limit of the parameter alpha (giving the maximal strength of quantum blurring) can be entered, which is scaled in the model of blurring (called "Phi") operating much like "seeing" from the ground in the optical, and those calculations are plotted against the observations.

[ascl:2311.002] VCAL-SPHERE: Hybrid pipeline for reduction of VLT/SPHERE data

VCAL-SPHERE, for VIP-based Calibration of VLT/SPHERE data, is a versatile pipeline for high-contrast imaging of exoplanets and circumstellar disks. The pipeline covers all steps of data reduction, including raw calibration, pre-processing and post-processing (i.e., modeling and subtraction of the stellar halo), for the IFS, IRDIS-DBI and IRDIS-CI modes (and combinations thereof) of the VLT instrument SPHERE. The three main steps of the reduction correspond to different modules, where the first follows the recommended EsoRex (ascl:1504.003) workflow and associated recipes with occasional inclusion of VIP (ascl:1603.003) routines (e.g., for PCA-based sky subtraction), while the other two stages fully rely on the VIP toolbox. Although the default parameters of the pipeline should yield a good reduction in most cases, these can be tuned using JSON parameter files for each stage of the pipeline for optimal reduction of specific datasets.

[ascl:2311.001] wcpy: Wavelength Calibrator

The graphical user interface Wavelength Calibrator facilitates wavelength calibration. Although developed for astronomical data reduction, it can also be used in any place where wavelength calibration is needed.

[ascl:2310.012] GRIZZLY: 1D radiative transfer code

GRIZZLY simulates reionization using a 1D radiative transfer scheme. The code enables the efficient exploration of the parameter space for evaluating 21cm brightness temperature fluctuations near the cosmic dawn. GRIZZLY builds upon the BEARS algorithm for generating simulated reionization maps with density and velocity fields, which are useful for profiling dark matter halos and cosmological density fields.

[ascl:2310.011] AI-Feynman: Symbolic regression algorithm

AI-Feynman fits analytical expressions to data sets via symbolic regression, mapping the target variable to different features supplied in the data array. Using a neural network with constraints in the number of parameters utilized, the code provides the ability to obtain analytical expressions for normalized features that are used to predict a Pareto-optimal target. AI-Feynman is robust in handling noisy data, recursively generating multidimensional symbolic expressions that match data from an unknown functions.

[ascl:2310.010] riptide: Pulsar searching with the Fast Folding Algorithm

riptide implements the Fast Folding Algorithm (FFA) to identify periodic signals from time series data. In order to identify faint pulsars, the code provides access to a library of functions and classes for processing dedispersed radio signals. The FFA approaches the theoretical optimum for sensitivity to periodic signals regardless of pulse period and duty cycle.

[ascl:2310.009] IQRM-APOLLO: Clean narrow-band RFI using Inter-Quartile Range Mitigation (IQRM) algorithm

IQRM-APOLLO cleans narrow-band radio frequency interference (RFI) using the Inter-Quartile Range Mitigation (IQRM) algorithm. By masking this interference, the code reduces the number of false positive pulsar candidates and increases sensitivity for pulsar detection. The IQRM algorithm is an outlier detection algorithm that is both non-parametric and robust to the presences of trends in time series data. Using short-duration data blocks, IQRM-APOLLO computes a spectral statistic that correlates with the presence of RFI, removing high outliers from the input signal.

[ascl:2310.008] clfd: Clean folded data

clfd (clean folded data) implements GPU-accelerated smart interference removal algorithms to be used on folded pulsar search and pulsar timing data. The code converts each source profile to a small set of representative features, flagging outliers in the resulting feature space. clfd further visualizes the outlier flagging process, as well as the resulting two-dimensional time-frequency mask that is applied to the clean archive. The code provides access to cleaning algorithms that were initially developed for the High Time Resolution Universe (HTRU) survey which found several pulsars.

[ascl:2310.007] zCluster: Measure photometric redshifts for galaxy clusters

zCluster measures galaxy cluster photometric redshifts using data from broadband photometry in large public surveys, given a priori knowledge of the cluster position. The code retrieves and uses redshift probability distributions in order to create a projected two-dimensional density map of a targeted galaxy cluster, which is later convolved with a Gaussian kernel to smooth the map. zCluster also produces photometric redshift estimates and galaxy density maps for any point in the sky using the included zField tool.

[ascl:2310.006] MAGPy-RV: Gaussian Process regression pipeline with MCMC parameter searching

MAGPy-RV (Modelling stellar Activity with Gaussian Processes in Radial Velocity) models data with Gaussian Process regression and affine invariant Monte Carlo Markov Chain parameter searching. Developed to model intrinsic, quasi-periodic variations induced by the host star in radial velocity (RV) surveys for the detection of exoplanets and the accurate measurements of their orbital parameters and masses, it now includes a variety of kernels and models and can be applied to any timeseries analysis. MAGPy-RV includes publication level plotting, efficient posterior extraction, and export-ready LaTeX results tables. It also handles multiple datasets at once and can model offsets and systematics from multiple instruments. MAGPy-RV requires no external dependencies besides basic python libraries and corner (ascl:1702.002).

[ascl:2310.005] DustPyLib: A library of DustPy extensions

The DustPyLib library contains auxiliary modules for the dust evolution software DustPy (ascl:2207.016), which simulates the evolution of dust and gas in protoplanetary disks. DustPyLib includes interfaces to radiative transfer codes and modules with extensions to the DustPy defaults.

[ascl:2310.004] q3dfit: PSF decomposition and spectral analysis for JWST-IFU spectroscopy

q3dfit performs PSF decomposition and spectral analysis for high dynamic range JWST IFU observations, allowing the user to create science-ready maps of relevant spectral features. The software takes advantage of the spectral differences between quasars and their host galaxies for maximal-contrast subtraction of the quasar point-spread function (PSF) to reveal and characterize the faint extended emission of the host galaxy. Host galaxy emission is carefully fit with a combination of stellar continuum, emission and absorption of dust and ices, and ionic and molecular emission lines.

[ascl:2310.003] wwz: Weighted wavelet z-transform code

wwz provides a python3 implementation of the Foster weighted wavelet z-transform, a wavelet-based method for periodicity analysis of unevenly sampled data.

[ascl:2310.002] lcsim: Light curve simulation code

lcsim creates artificial light curves using two algorithms. The first simulates Gaussian distributed light curves following a specific power spectral density (PSD) freely selectable by the user. The second algorithm simulates light curves following a specific PSD and matching a specific probability density function (PDF). The package provides methods to resample the simulated light curves and add "observational" noise. Furthermore, the package provides an interface to a SQLite3-based database to store and access the simulations.

[ascl:2310.001] celerite2: Fast and scalable Gaussian Processes in one dimension

celerite2 is a re-write of celerite (ascl:1709.008), an algorithm for fast and scalable Gaussian Process (GP) Regression in one dimension. celerite2 improves numerical stability and integration with various machine learning frameworks. The implementation includes interfaces in Python and C++, with full support for PyMC (ascl:1610.016) and JAX (ascl:2111.002).

[ascl:2309.020] PlanetSlicer: Orange-slice algorithm for fitting brightness maps to phase curves

PlanetSlicer fits brightness maps to phase curves using the "orange-slice" method and works both for self-luminous objects and those that diffuse reflected light assuming Lambertian reflectance. In both cases, the model supposes that a spherical object can be divided into slices of constant brightness (or albedo) which may be integrated to yield the total flux observed, given the angles of observation. The package contains two key functions: toPhaseCurve and fromPhaseCurve; the former integrates the brightness for each slice to calculate the observed total flux from the object, given the longitude of observation. The latter does the opposite, estimating the brightness of the slices from a set of observed total flux (the phase curve).

[ascl:2309.019] FRISBHEE: FRIedmann Solver for Black Hole Evaporation in the Early-universe

FRISBHEE (FRIedmann Solver for Black Hole Evaporation in the Early-universe solves the Friedmann - Boltzmann equations for Primordial Black Holes + SM radiation + BSM Models. Considering the collapse of density fluctuations as the PBH formation mechanism, the code handles monochromatic and extended mass and spin distributions. FRISBHEE can return the full evolution of the PBH, SM and Dark Radiation comoving energy densities, together with the evolution of the PBH mass and spin as a function of the log10 at scale factor, and can determine the relic abundance in the case of Dark Matter produced from BH evaporation for monochromatic and extended distributions.

[ascl:2309.018] Sprout: Moving mesh finite volume hydro code

The finite volume hydro code Sprout uses a simple expanding Cartesian grid to track outflows for several orders of magnitudes in expansion. It captures shocks whether they are aligned or misaligned with the grid, and provides second-order convergence for smooth flows. The code's expanding mesh capability reduces numerical diffusion drastically for outflows, especially when the analytic nature of the bulk flow is known beforehand. Sprout can be used to study fluid instabilities in expanding flows, such as in SN explosions and jets; it resolves fine fluid structures at small length scales and expand the mesh gradually as the structures grow.

[ascl:2309.017] ChEAP: Chemical Evolution Analytic Package

ChEAP (Chemical Evolution Analytic Package) implements an analytic solution for the chemical evolution model of the Galaxy that extends the instantaneous recycling approximation with the contribution of Type Ia SNe. The code works for different prescriptions of the delay time distributions (DTDs), including the single and double degenerate scenarios, and allows the inclusion of an arbitrary number of pristine gas infalls. The required functions are contained in the CheapTools.py file, which is imported as a Python library. ChEAP also includes code to illustrate, with a random-parameter chemical evolution model, the accuracy of this analytic solution compared to one using numerical integration.

[ascl:2309.016] PEREGRINE: Gravitational wave parameter inference with neural ration estimation

PEREGRINE performs full parameter estimation on gravitational wave signals. Using an internal Truncated Marginal Neural Ratio Estimation (TMNRE) algorithm and building upon the swyft (ascl:2302.016) code to efficiently access marginal posteriors, PEREGRINE conducts a sequential simulation-based inference approach to support the analysis of both transient and continuous gravitational wave sources. The code can fully reconstruct the posterior distributions for all parameters of spinning, precessing compact binary mergers using waveform approximants.

[ascl:2309.015] bskit: Bispectra from cosmological simulation snapshots

bskit, built upon the nbodykit (ascl:1904.027) simulation analysis package, measures density bispectra from snapshots of cosmological N-body or hydrodynamical simulations. It can measure auto or cross bispectra in a user-specified set of triangle bins (that is, triplets of 3-vector wavenumbers). Several common sets of bins are also implemented, including all triangle bins for specified k_min and k_max, equilateral triangles between specified k_min and k_max, isosceles triangles, and squeezed isosceles triangles.

[ascl:2309.014] fitScalingRelation: Fit galaxy cluster scaling relations using MCMC

fitScalingRelation fits galaxy cluster scaling relations using orthogonal or bisector regression and MCMC. It takes into account errors on both variables and intrinsic scatter. Although it geared for fitting galaxy cluster scaling relations of all kinds, it can be used for any kind of regression problem with errors on both variables and intrinsic scatter.

[ascl:2309.013] maszcal: Mass calibrations for thermal-SZ clusters

maszcal calibrates the observable-mass relation for galaxy clusters, with a focus on the thermal Sunyaev-Zeldovich signal's relation to mass. maszcal explicitly models baryonic matter density profiles, differing from most previous approaches that treat galaxy clusters as purely dark matter. To do this, it uses a generalized Nararro-Frenk-White (GNFW) density to represent the baryons, while using the more typical NFW profile to represent dark matter.

[ascl:2309.012] StarbugII: JWST PSF photometry for crowded fields

The python photometry suite StarbugII provides accurate photometry on point-like sources embedded in complex diffuse emissions. The tool has a simple modular interface with a wide range of photometric routines including embedded source detection, aperture and PSF photometry, diffuse background emission estimation, catalog matching and artificial star testing. The core is built around Photutils (ascl:1609.011).

[ascl:2309.011] PCOSTPD: Periodogram Comparison for Optimizing Small Transiting Planet Detection

The Periodogram Comparison for Optimizing Small Transiting Planet Detection R code compares two periodogram algorithms for detecting transiting exoplanets: the Box-fitting Least Squares (BLS) and the Transit Comb Filter (TCF). It calculates the False Alarm Probability (FAP) based on extreme value theory and signal-to-noise ratio (SNR) metrics to quantify periodogram peak significance. The comparison approach is aimed at optimizing the detection of small transiting planets in future transiting exoplanet surveys. The code can be extended for comparing any set of periodograms.

[ascl:2309.010] pymccorrelation: Correlation coefficients with uncertainties

pymccorrelation calculates correlation coefficients for data, using bootstrapping and/or perturbation to estimate the uncertainties on the correlation coefficient and p-value. The code supports Pearson's r, Spearman's rho, and Kendall's tau. Calculations of Kendall's tau additionally support censored data. This code supercedes and expands the deprecated code pymcspearman (ascl:2309.009).

[ascl:2309.009] pymcspearman: Monte carlo calculation of Spearman's rank correlation coefficient with uncertainties

pymcspearman is a python implementation of MCSpearman (ascl:1504.008) and calculates Spearman's rank correlation coefficient for data, using bootstrapping and/or perturbation to estimate the uncertainties on the correlation coefficient. This software project has migrated (and expanded) to pymccorrelation (ascl:2309.010).

[submitted] INSPECTA: INtegrated SDHDF Processing Engine in C for Telescope data Analysis

INSPECTA (formerly sdhdfProc) is a software package to read, manipulate and process radio astronomy data in Spectral-Domain Hierarchical Data Format (SDHDF). It is available as part of the 'sdhdf_tools' repository.

[submitted] A pseudo GUI with pyplot

Working with a GUI, or adding interaction in plotting, will help a lot in data analysis. However, the common GUI of Python is OS-dependent, while manually adding interactive codes is too complex. A pseudo-GUI tool is introduced in this work. It will help to add buttons/checkers in the graph and assign callback functions to them. The remaining problem is that the documents in this package are in Chinese and will be in English in the next version. This program is published to the PyPI, and can be installed by 'pip install pltgui'.

[submitted] qmatch: Some astronomical image matching programs

Matching stars in astronomical images is an essential step in data reduction. This work includes some matching programs implemented by Python: simple matching, fast matching, and triangle matching. For two catalogs with m and n objects, the simple method has a time and space complexity of O(m*n) but is fast for fewer n or m. The time complexity of the fast method is O(mlogm+nlogn). The triangle method will work between rotated and scaled images. All methods are applied in pipelines and work well. This package is published to the PyPI with the name 'qmatch'.

[submitted] LOFAR H5plot

Calibration solutions for the LOFAR radio telescope are stored in a 5-dimensional (time, frequency, station, polarisation and direction in the sky) HDF5 table. H5plot is a GUI application focussing on interactive visual inspection of these calibration solutions.

[ascl:2309.008] PI: Plages Identification

Plages Identification identifies solar plages from Ca II K photographic observations irrespective of noise level, brightness, and other image properties. The code provides an efficient, reliable method for identifying solar plages. The output of the algorithm is an image highlighting the plages and the calculated plage index. Plages Identification is also deployed as a webapp, allowing users to experiment with different hyperparameters and visualize their impact on the output image in real time.

[ascl:2309.007] MATRIX: Multi-phAse Transits Recovery from Injected eXoplanets toolkit

The injection-recovery MATRIX (Multi-phAse Transits Recovery from Injected eXoplanets) Toolkit creates grids of scenarios with a set of periods, radii, and epochs of synthetic transiting exoplanet signals in a provided light curve. Typical injection-recovery executions consist of 2-dimensional scenarios, where only one epoch (random or hardcoded) was used for each period and radius, which may reduce accuracy. MATRIX performs multi-phase analyses needing only a few parameters in a configuration file and running one line of code.

[ascl:2309.006] CoLFI: Cosmological Likelihood-Free Inference

CoLFI (Cosmological Likelihood-Free Inference) estimates parameters directly from the observational data sets using neural density estimators (NDEs); it is a fully ANN-based framework that differs from the Bayesian inference. The package contains three NDEs that are used to estimate parameters: an artificial neural network (ANN), a mixture density network (MDN), and a mixture neural network (MNN). CoLFI can learn the conditional probability density using samples generated by models, and the posterior distribution can be obtained for given observational data.

[ascl:2309.005] DeepGlow: Neural network emulator for BOXFIT

The feed-forward neural network DeepGlow emulates BOXFIT (ascl:2306.059) simulation data of gamma-ray burst (GRB) afterglows. The package provides an easy interface to generate GRB afterglow spectra and light curves mimicking those generated through BOXFIT with high accuracy. The code used to generate the training data and to train the neural networks is also included.

[ascl:2309.004] GWSim: Mock gravitational waves event generator

GWSim generates mock gravitational waves (GW) events corresponding to different binary black holes (BBHs) population models. It can incorporate scenarios of GW mass models, GW spin distributions, the merger rate, and the cosmological parameters. GWSim generates samples of binary compact objects for a fixed amount of observation time, duty cycle, and configurations of the detector network; the universe created by the code is uniform in comobile volume.

[ascl:2309.003] Swiftbat: Utilities for handing BAT instrument data from the Neil Gehrels Swift Observatory

Swiftbat retrieves, analyzes, and displays data from NASA's Swift spacecraft, especially data from the Swift Burst Alert Telescope (BAT). All BAT data are available from the Swift data archive; however, a few routines in this library use data access methods not available to the general public and thus are useful only to Swift team members. The package also installs a command-line program 'swinfo' that provides Swift Information such as what the MET (onboard-clock) time is, where Swift was pointing, and whether a specific source was above the horizon and/or in the field of view.

[ascl:2309.002] UBHM: Uncertainty quantification of black hole mass estimation

Uncertain_blackholemass predicts virial black hole masses using a neural network model and quantifies their uncertainties. The scripts retrieve data and run feature extraction and uncertainty quantification for regression. They can be used separately or deployed to existing machine learning methods to generate prediction intervals for the black hole mass predictions.

[ascl:2309.001] TRES: TRiple Evolution Simulation package

TRES simulates hierarchical triple systems with stellar and planetary components, including stellar evolution, stellar winds, tides, general relativistic effects, mass transfer, and three-body dynamics. It combines stellar evolution and interactions with three-body dynamics in a self-consistent way. The code includes the effects of common-envelope evolution, circularized stable mass transfer, tides, gravitational wave emission and up-to-date stellar evolution through SeBa (ascl:1201.003). Other stellar evolution codes, such as SSE (ascl:1303.015), can also be used. TRES is written in the AMUSE (ascl:1107.007) software framework.

[ascl:2308.015] FishLSS: Fisher forecasting for Large Scale Structure surveys

FishLSS computes the Fisher information matrix for a set of observables and model parameters. It can model the redshift-space power spectrum of any biased tracer of the CDM+baryon field and the post-reconstruction galaxy power spectrum. The code also models the projected cross-correlation of galaxies with the CMB lensing convergence, the projected galaxy power spectrum, and the CMB lensing convergence power spectrum. FishLSS requires pyFFTW (ascl:2109.009), velocileptors (ascl:2308.014), and CLASS (ascl:1106.020).

[ascl:2308.014] velocileptors: Velocity-based Lagrangian and Eulerian PT expansions of redshift-space distortions

velocileptors computes the real- and redshift-space power spectra and correlation functions of biased tracers using 1-loop perturbation theory (with effective field theory counter terms and up to cubic biasing) as well as the real-space pairwise velocity moments. It provides simple computation of the power spectrum wedges or multipoles, and uses a reduced set of parameters for computing the most common case of the redshift-space power spectrum. In addition, velocileptors offers two "direct expansion" modules available in LPT and EPT.

[ascl:2308.013] Driftscan: Drift scan telescope analysis

Driftscan simulates and analyzes transit radio interferometers, with a particular focus on 21cm cosmology. Given a design of a telescope, it generates a set of products used to analyze data from it and simulate timestreams. Driftscan also constructs a filter to extract cosmological 21 cm emission from astrophysical foregrounds, such as our galaxy and radio point sources, and estimates the 21cm power spectrum using an optimal quadratic estimator.

[ascl:2308.012] KeplerFit: Keplerian velocity distribution model fitter

KeplerFit fits a Keplerian velocity distribution model to position-velocity (PV) data to obtain an estimate of the enclosed mass. The code extracts the scales of the pixels in both directions, spatial and spectral, then extracts the most extreme velocity at each position; this returns two arrays of positions and velocities. KeplerFit then models the extracted PV data and returns a set of the best-fit parameters, the standard deviations in each of the parameters, and the total residual of the fit.

[ascl:2308.011] glmnet: Lasso and elastic-net regularized generalized linear models

glmnet efficiently fits the entire lasso or elastic-net regularization path for linear regression (gaussian), multi-task gaussian, logistic and multinomial regression models (grouped or not), Poisson regression and the Cox model. The algorithm uses cyclical coordinate descent in a path-wise fashion.

[ascl:2308.010] BCemu: Model baryonic effects in cosmological simulations

BCMemu provides emulators to model the suppression in the power spectrum due to baryonic feedback processes. These emulators are based on the baryonification model, where gravity-only N-body simulation results are manipulated to include the impact of baryonic feedback processes. The package also has a three parameter barynification model; the first assumes all the three parameters to be independent of redshift while the second assumes the parameters to be redshift dependent.

[ascl:2308.009] caput: Utilities for building radio astronomy data analysis pipelines

Caput (Cluster Astronomical Python Utilities) contains utilities for handling large datasets on computer clusters. Written with radio astronomy in mind, the package provides an infrastructure for building, managing and configuring pipelines for data processing. It includes modules for dynamically importing and utilizing mpi4py, in-memory mock-ups of h5py objects, and infrastructure for running data analysis pipelines on computer clusters. Caput features a generic container for holding self-documenting datasets in memory with straightforward syncing to h5py files, and offers specialization for holding time stream data. Caput also includes tools for MPI-parallel analysis and routines for converting between different time representations, dealing with leap seconds, and calculating celestial times.

[ascl:2308.008] Rapster: Rapid population synthesis for binary black hole mergers in dynamical environments

Rapster (RAPid cluSTER evolution) models binary black hole population synthesis and the evolution of star clusters based on simple, yet realistic prescriptions. The code can generate large populations of dynamically formed binary black holes. Rapster uses SEVN (ascl:2206.019) to model the initial black hole mass spectrum and PRECESSION (ascl:1611.004) to model the mass, spin, and gravitational recoil of merger remnants.

[ascl:2308.007] DiskMINT: Disk Model For INdividual Targets

DiskMINT (Disk Model for INdividual Targets) models individual disks and derives robust disk mass estimates. Built on RADMC-3D (ascl:1202.015) for continuum (and gas line) radiative transfer, the code includes a reduced chemical network to determine the C18O emission. DiskMINT has a Python3 module that generates a self-consistent 2D disk structure to satisfy VHSE (Vertical Hydrostatic Equilibrium). It also contains a Fortran code of the reduced chemical network that contains the main chemical processes necessary for C18O modeling: the isotopologue-selective photodissociation, and the grain-surface chemistry where the CO converting to CO2 ice is the main reaction.

[ascl:2308.006] Nemo: Millimeter-wave map filtering and Sunyaev-Zel'dovich galaxy cluster and source detection

Nemo detects millimeter-wave Sunyaev-Zel'dovich galaxy clusters and compact sources. Originally developed for the Atacama Cosmology Telescope project, the code is capable of analyzing the next generation of deep, wide multifrequency millimeter-wave maps that will be produced by experiments such as the Simons Observatory. Nemo provides several modules for analyzing ACT/SO data in addition to the command-line programs provided in the package.

[ascl:2308.005] FastSpecFit: Fast spectral synthesis and emission-line fitting of DESI spectra

FastSpecFit models the observed-frame optical spectroscopy and broadband photometry of extragalactic targets using physically grounded stellar continuum and emission-line templates. The code handles data from the Dark Energy Spectroscopic Instrument (DESI) Survey, which is amassing spectrophotometry for an unprecedented 40 million extragalactic targets, although the algorithms are general enough to accommodate other upcoming, massively multiplexed spectroscopic surveys. FastSpecFit extracts nearly 800 observed- and rest-frame quantities from each target, including light-weighted ages and stellar velocity dispersions based on the underlying stellar continuum; line-widths, velocity shifts, integrated fluxes, and equivalent widths for nearly 40 rest-frame ultraviolet, optical, and near-infrared emission lines arising from both star formation and active galactic nuclear activity; and K-corrections and rest-frame absolute magnitudes and colors. Moreover, FastSpecFit is designed with speed and parallelism in mind, enabling it to deliver robust model fits to tens of millions of targets.

[ascl:2308.004] AstroPhot: Fitting everything everywhere all at once in astronomical images

AstroPhot quickly extracts detailed information from complex astronomical data for individual images or large survey programs. It fits models for sky, stars, galaxies, PSFs, and more in a principled chi^2 forward optimization, recovering Bayesian posterior information and covariance of all parameters. The code optimizes forward models on CPU or GPU, across images that are large, multi-band, multi-epoch, rotated, dithered, and more. Models are optimized together, thus handling overlapping objects and including the covariance between parameters (including PSF and galaxy parameters). AstroPhot includes several optimization algorithms, including Levenberg-Marquardt, Gradient descent, and No-U-Turn MCMC sampling.

[ascl:2308.003] SIMBI: 3D relativistic gas dynamics code

SIMBI simulates heterogeneous relativistic gas dynamics up to 3d for special relativistic hydrodynamics and up to 2D Newtonian hydrodynamics. It supports user-defined mesh expansion and contraction, density, momentum, and energy density terms outside of grid; the code also supports source terms in the Euler equations and source terms at the boundaries. Boundary conditions, which include periodic, reflecting, outflow, and inflow boundaries, are given as an array of strings. If an inflow boundary condition is set but no inflow boundary source terms are given, SIMBI switches to outflow boundary conditions to prevent crashes. The code can track a single passive scalar, insert an immersed boundary, and is impermeable by default. SIMBI USES the Cython framework to blend together C++, CUDA, HIP, and Python.

[ascl:2308.002] FLATW'RM: Finding flares in Kepler data using machine-learning tools

FLATW'RM (FLAre deTection With Ransac Method) detects stellar flares in light curves using a classical machine-learning method. The code tries to find a rotation period in the light curve and splits the data to detection windows. The light curve sections are fit with the robust fitting algorithm RANSAC (Random sample consensus); outlier points (flare candidates) above the pre-set detection level are marked for each section. For the given detection window, only those flare candidates that have at least a given number of consecutive points (three by default) are kept and marked as flares. When using FLATW’RM, the code's output should be checked to determine whether changes to the default settings are needed to account for light curve noise, data sampling frequency, and scientific needs.

[ascl:2308.001] MOOG_SCAT: Scattering version of the MOOG Line Transfer Code

MOOG_SCAT, a redevelopment of the LTE radiative transfer code MOOG (ascl:1202.009), contains modifications that allow for the treatment of isotropic, coherent scattering in stars. MOOG_SCAT employs a modified form of the source function and solves radiative transfer with a short charactersitics approach and an acclerated lambda iteration scheme.

[ascl:2307.062] FABADA: Non-parametric noise reduction using Bayesian inference

FABADA (Fully Adaptive Bayesian Algorithm for Data Analysis) performs non-parametric noise reduction using Bayesian inference. It iteratively evaluates possible smoothed models of the data to estimate the underlying signal that is statistically compatible with the noisy measurements. Iterations stop based on the evidence E and the χ2 statistic of the last smooth model, and the expected value of the signal is computed as a weighted average of the smooth models. Though FABADA was written for astronomical data, such as spectra (1D) or images (2D), it can be used as a general noise reduction algorithm for any one- or two-dimensional data; the only requisite of the input data is an estimation of its associated variance.

[ascl:2307.061] connect: COsmological Neural Network Emulator of CLASS using TensorFlow

connect (COsmological Neural Network Emulator of CLASS using TensorFlow) emulates cosmological parameters using neural networks. This includes both sampling of training data and training of the actual networks using the TensorFlow library. connect aids in cosmological parameter inference by immensely speeding up the process, which is achieved by substituting the cosmological Einstein-Boltzmann solver codes, needed for every evaluation of the likelihood, with a neural network with a 102 to 103 times faster evaluation time. The code requires CLASS (ascl:1106.020) and Monte Python (ascl:1307.002) if iterative sampling is used.

[ascl:2307.060] MBASC: Multi-Band AGN-SFG Classifier

MBASC (Multi-Band AGN-SFG Classifier) classifies sources as Active Galactic Nuclei (AGNs) and Star Forming Galaxies (SFGs). The algorithm is based on the light gradient-boosting machine ML technique. MBASC can use a wide range of multi-wavelength data and redshifts to predict a classification for sources.

[ascl:2307.059] orbitN: Symplectic integrator for near-Keplerian planetary systems

orbitN generates accurate and reproducible long-term orbital solutions for near-Keplerian planetary systems with a dominant mass M0. The code focuses on hierarchical systems without close encounters but can be extended to include additional features. Among other features, the package includes M0's quadrupole moment, a lunar contribution, and post-Newtonian corrections (1PN) due to M0 (fast symplectic implementation). To reduce numerical roundoff errors, orbitN features Kahan compensated summation.

[ascl:2307.058] APOLLO: Radiative transfer and atmosphere spectroscopic retrieval for exoplanets

APOLLO forward models the radiative transfer of light through a planetary (or brown dwarf) atmosphere; it also forward models transit and emission spectra and retrieves atmospheric properties of extrasolar planets. The code has two operational modes: one to compute a planetary spectrum given a set of parameters, and one to retrieve those parameters based on an observed spectrum. The package uses emcee (ascl:1303.002) to find the best fit to a spectrum for a given parameter set. APOLLO is modular and offers many options that may be turned on and off, including the type of observations, a flexible molecular composition, multiple cloud prescriptions, multiple temperature-pressure profile prescriptions, multiple priors, and continuum normalization.

[ascl:2307.057] species: Atmospheric characterization of directly imaged exoplanets

species (spectral characterization and inference for exoplanet science) provides a coherent framework for spectral and photometric analysis of directly imaged exoplanets and brown dwarfs which builds on publicly-available data and models from various resources. species contains tools for grid and free retrievals using Bayesian inference, synthetic photometry, interpolating a variety atmospheric and evolutionary model grids (including the possibility to add a custom grid), color-magnitude and color-color diagrams, empirical spectral analysis, spectral and photometric calibration, and analysis of emission lines.

[ascl:2307.056] HELA: Random Forest retrieval for exoplanet atmospheres

HELA performs atmospheric retrieval on exoplanet atmospheres using a Random Forest algorithm. The code has two stages: training (which includes testing), and predicting. It requires a training set that matches the format of the data to be analyzed, with the same number of points and a sample spectrum for each parameter. The number of trees used and the number of jobs are editable. The HELA package includes a training set and data as examples.

[ascl:2307.055] plan-net: Bayesian neural networks for exoplanetary atmospheric retrieval

plan-net uses machine learning with an ensemble of Bayesian neural networks for atmospheric retrieval; this approach yields greater accuracy and more robust uncertainties than a single model. A new loss function for BNNs learns correlations between the model outputs. Performance is improved by incorporating domain-specific knowledge into the machine learning models and provides additional insight by inferring the covariance of the retrieved atmospheric parameters.

[ascl:2307.054] LEFTfield: Forward modeling of cosmological density fields

LEFTfield forward models cosmological matter density fields and biased tracers of large-scale structure. The model, written in C++ code, is centered around classes encapsulating scalar, vector, and tensor grids. It includes the complete bias expansion at any order in perturbations and captures general expansion histories without relying on the EdS approximation; however, the latter is also implemented and results in substantially smaller computational demands. LEFTfield includes a subset of the nonlinear higher-derivative terms in the bias expansion of general tracers.

[submitted] backtrack: fit relative motion of candidate direct imaging sources with background proper motion and parallax

Directly imaged planet candidates (high contrast point sources near bright stars) are often validated, among other supporting lines of evidence, by comparing their observed motion against the projected motion of a background source due to the proper motion of the bright star and the parallax motion due to the Earth's orbit. Often, the "background track" is constructed assuming an interloping point source is at infinity and has no proper motion itself, but this assumption can fail, producing false positive results, for crowded fields or insufficient observing time-baselines (e.g. Nielsen et al. 2017). `backtrack` is a tool for constructing background proper motion and parallax tracks for validation of high contrast candidates. It can produce classical infinite distance, stationary background tracks, but was constructed in order to fit finite distance, non-stationary tracks using nested sampling (and can be used on clusters). The code sets priors on parallax based on the relations in Bailer-Jones et al. 2021 that are fit to Gaia eDR3 data, and are therefore representative of the galactic stellar density. The public example currently reproduces the results of Nielsen et al. 2017 and Wagner et al. 2022, demonstrating that the motion of HD 131399A "b" is fit by a finite distance, non-stationary background star, but the code has been tested and validated on proprietary datasets. The code is open source, available on github, and additional contributions are welcome.

[ascl:2307.053] EVolve: Growth and evolution of volcanically-derived atmospheres

EVolve calculates the chemical composition and surface pressure of a ID atmosphere on a rocky planet that is being produced by volcanic activity, as it grows over time. Once the initial volatile content of the planet's mantle and the composition and resultant surface pressure of any pre-existing atmosphere is set, the volcanic degassing model EVo (ascl:2307.052) calculates the amount and speciation of any volcanic gases released into the atmosphere over each time step. Atmospheric processing is calculated using FastChem (ascl:1804.025); thermochemical equilibrium is assumed so the final chemical composition of the atmosphere is calculated according to the pre-set surface temperature.

[ascl:2307.052] EVo: Thermodynamic magma degassing model

EVo calculates the speciation and volume of a volcanic gas phase erupting in equilibrium with its parent magma. Models can be run to calculate the gas phase in equilibrium with a melt at a single pressure, or the melt can be decompressed from depth rising to the surface as a closed-system case. Single pressure and decompression can be run for OH, COH, SOH, COHS and COHSN systems. EVo can calculate gas phase weight and volume fraction within the system, gas phase speciation as mole fraction or weight fraction across numerous compounds, and the volatile content of the melt at each pressure. It also calculates melt density, f02 of the system, and more. EVo can be set up using either melt volatile contents, or for a set amount of atomic volatile which is preferable for conducting experiments over a wide range of fO2 values.

[ascl:2307.051] WeakLensingQML: Quadratic Maximum Likelihood estimator applied to Weak Lensing

WeakLensingQML implements the Quadratic Maximum Likelihood (QML) estimator and applies it to simulated cosmic shear data and compares the results to a Pseudo-Cl implementation. The package computes and saves relevant data files for later processes, such as the fiduciary cosmic shear power spectrum used in the analysis, the sky mask, and computing an analytic version of the QML's covariance matrix. The core of the package implements a conjugate-gradient approach for the quadratic estimator, and is parallelized for maximum performance. The code relies on the Eigen linear algebra package and the HealPix spherical harmonic transform library. A post-processing script analyzes the results and compares the QML's estimates with those from the Pseudo-Cl estimator; it then produces an array of plots highlighting the results.

[ascl:2307.050] νHawkHunter: Forecasting of PBH neutrinos

νHawkHunter explores the prospects of detecting neutrinos produced by the evaporation of primordial black holes in ground-based experiments. It makes use of neutrino fluxes from Hawking radiation computed with BlackHawk (ascl:2012.020). νHawkHunter is also be used for Diffuse Supernova Neutrino Background or similar studies by replacing the signal fluxes by the proper ones.

[ascl:2307.049] reMASTERed: Calculate contributions to pseudo-Cl for maps with correlated masks

reMASTERed reconstructs ensemble-averaged pseudo-$C_\ell$ to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. The code can compute the results given an arbitrary map and mask; it can also compute the results in the ensemble average for certain types of threshold masks.

[ascl:2307.048] NaMaster: Unified pseudo-Cl framework

NaMaster computes full-sky angular cross-power spectra of masked, spin-0 and spin-2 fields with an arbitrary number of known contaminants using a pseudo-Cl (aka MASTER) approach. The code also implements E/B-mode purification and offers both full-sky and flat-sky modes. NaMaster is available as a C library, Python module, and standalone program.

[ascl:2307.047] GWDALI: Gravitational wave parameter estimation

GWDALI focuses on parameter estimations of gravitational waves generated by compact object coalescence (CBC). This software employs both Gaussian (Fisher Matrix) and Beyond-Gaussian methods to approximate the likelihood of gravitational wave events. GWDALI also addresses the challenges posed by Fisher Matrices with zero determinants. Additionally, the Beyond-Gaussian approach incorporates the Derivative Approximation for Likelihoods (DALI) algorithm, enabling a more reliable estimation process.

[ascl:2307.046] HAYASHI: Halo-level AnalYsis of the Absorption Signal in HI

HAYASHI (Halo-level AnalYsis of the Absorption Signal in HI) computes the number of absorption features of the 21cm forest using a semianalytic formalism. It includes the enhancement of the signal due to the presence of substructures within minihalos and supports non-standard cosmologies with impact in the large scale structure, such as warm dark matter and primordial black holes. HAYASHI is written in Python3 and uses the cosmological computations package Colossus (ascl:1501.016).

[ascl:2307.045] NAVanalysis: Normalized Additional Velocity analysis

NAVanalysis studies the non-baryonic, or non-Newtonian, contribution to galaxy rotation curves straight from a given data sample. Conclusions on the radial profile of a given model can be drawn without individual galaxy fits to provide an efficient sample comparison. The method can be used to eliminate model parameter regions, find the most probable parameter regions, and uncover trends not easy to find from standard fits. Further, NAVanalysis can compare different approaches and models.

[ascl:2307.044] RUBIS: Fast centrifugal deformation program for stellar and planetary models

The centrifugal deformation program RUBIS (Rotation code Using Barotropy conservation over Isopotential Surfaces) takes an input 1D model (with spherical symmetry) and returns its deformed version by applying a conservative rotation profile specified by the user. The code needs only the density as a function of radial distance from the reference model in addition to the surface pressure to be imposed to perform the deformation; preserving the relation between density and pressure when going from the 1D to the 2D structure makes this lightness possible. By solving Poisson's equation in spheroidal rather than spherical coordinates whenever a discontinuity is present, RUBIS can deform both stellar and planetary models, thereby dealing with potential discontinuities in the density profile.

[ascl:2307.043] EAGLES: Estimating AGes from Lithium Equivalent widthS

EAGLES (Estimating AGes from Lithium Equivalent widthS) implements an empirical model that predicts the lithium equivalent width (EW) of a star as a function of its age and effective temperature. The code computes the age probability distribution for a star with a given EW and Teff, subject to an age probability prior that may be flat in age or flat in log age. Data for more than one star can be entered; EAGLES then treats these as a cluster and determines the age probability distribution for the ensemble. The code produces estimates of the most probable age, uncertainties and the median age; output files consisting of probability plots, best-fit isochrone plots, and tables of the posterior age probability distribution(s).

[ascl:2307.042] LIMpy: Line Intensity Mapping in Python

LIMpy models and analyzes multi-line intensity maps of CII (158 µ), OIII (88 µ), and CO (1-0) to CO (13-12) transitions. It can be used as an analytic model for star formation rate, to simulate line intensity maps based on halo catalogs, and to calculate the power spectrum from simulated maps and the cross-correlated signal between two separate lines. Among other things, LIMpy can also create multi-line luminosity models and determine the multi-line intensity power spectrum.

[ascl:2307.041] EFTCAMB: Effective Field Theory with CAMB

EFTCAMB patches the public Einstein-Boltzmann solver CAMB (ascl:1102.026) to implement the Effective Field Theory approach to cosmic acceleration. It can be used to investigate the effect of different EFT operators on linear perturbations and to study perturbations in any specific DE/MG model that can be cast into EFT framework. To interface EFTCAMB with cosmological data sets, it is equipped with a modified version of CosmoMC (ascl:1106.025), EFTCosmoMC, to create a bridge between the EFT parametrization of the dynamics of perturbations and observations.

[ascl:2307.040] pycrires: Data reduction pipeline for VLT/CRIRES+

pycrires runs the CRIRES+ recipes of EsoRex. The pipeline organizes the raw data, creates SOF and configuration files, runs the calibration and science recipes, and creates plots of the images and extracted spectra. Additionally, it corrects remaining inaccuracies in the wavelength solution and the spectrum curvature. pycrires also provides dedicated routines for the extraction, calibration, and detection of spatially-resolved objects such as directly imaged planets.

[ascl:2307.039] adiabatic-tides: Tidal stripping of dark matter (sub)haloes

adiabatic-tides evaluates the tidal stripping of dark matter (sub)haloes in the adiabatic limit. It exactly reproduces the remnant of an NFW halo that is exposed to a slowly increasing isotropic tidal field and approximately reproduces the remnant for an anisotropic tidal field. adiabatic-tides also predicts the asymptotic mass loss limit for orbiting subhaloes and differently concentrated host-haloes with and without baryonic components, and can be used to improve predictions of dark matter annihilation.

[ascl:2307.038] WarpX: Time-based electromagnetic and electrostatic Particle-In-Cell code

WarpX is an advanced electromagnetic & electrostatic Particle-In-Cell code. It supports many features including Perfectly-Matched Layers (PML), mesh refinement, and the boosted-frame technique. A highly-parallel and highly-optimized code, WarpX can run on GPUs and multi-core CPUs, includes load balancing capabilities, and scales to the largest supercomputers.

[ascl:2307.037] WDMWaveletTransforms: Fast forward and inverse WDM wavelet transforms

WDMWaveletTransforms implements the fast forward and inverse WDM wavelet transforms in Python from both the time and frequency domains. The frequency domain transforms are inherently faster and more accurate. The wavelet domain->frequency domain and frequency domain->wavelet domain transforms are nearly exact numerical inverses of each other for a variety of inputs tested, including Gaussian random noise. WDMWaveletTransforms has both command line and Python interfaces.

[ascl:2307.036] binary_c-python: Stellar population synthesis tool and interface to binary_c

binary_c-python provides a manager for and interface to the binary_c framework (ascl:2307.035), and rapidly evolves individual systems and populations of stars. It provides functions such as data processing tools and initial distribution functions for stellar properties. binary_c-python also includes tools to run large grids of (binary) stellar systems on servers or distributed systems.

[ascl:2307.035] binary_c: Stellar population synthesis software framework

The binary_c software framework models the evolution of single, binary and multiple stars, including stellar evolution and nucleosynthesis. Stellar evolution includes wind mass loss, rotation, thermal pulses, magnetic braking, pre-main sequence evolution, supernovae and kicks, and neutron stars; binary-star evolution includes mass transfer, gravitational-wave losses, tides, novae, circumbinary discs, and merging stars. binary_c natively includes nucleosynthesis, and, as it is designed for stellar population calculations, it is lightweight and versatile. binary_c works in standalone, virtual and HPC environments, and its support software contains tools for development and data analysis. A version in Python, binary_c-python (ascl:2307.036), is also available.

[ascl:2307.034] Guacho: 3D uniform mesh parallel HD/MHD code for astrophysics

Guacho is a 3D hydrodynamical/magnetohydrodynamical code suited for astrophysical fluids. The hydrodynamic equations are evolved with a number of approximate Riemann solvers. Gaucho includes various modules to deal with different cooling regimes, and a radiation transfer module based on a Monte Carlo ray tracing method. The code can run sequentially or in parallel with MPI.

[ascl:2307.033] Imber: Doppler imaging tool for modeling stellar and substellar surfaces

Imber simulates spectroscopic and photometric observations with both a gridded numerical simulation and analytical model. Written in Python, it is specifically designed to predict Extremely Large Telescope instrument (such as ELT/METIS and TMT/MODHIS) Doppler imaging performance, and has also been applied to existing, archival observations of spectroscopy and photometry.

[ascl:2307.032] AmpF: Amplification factor for solar lensing

AmpF numerically calculates the amplification factor for solar lensing. The import parameters are the gravitational-wave frequency and the source angular position with respect to the solar center; the code outputs are the amplification factor and its geometrical-optics limit. AmpF accepts variables for several attributes and the overall amplitude of the lensing potential can be changed as needed. The method has been implemented in both C and Python.

[ascl:2307.031] HilalPy: Analysis tool for lunar crescent visibility criterion

HilalPy analyzes lunar crescent visibility criteria. Written in Python, the code uses more than 8000 lunar crescent visibility records extracted from literature and websites of lunar crescent observation, descriptive statistics, contradiction rate percentage, and regression analysis in its analysis to predict the visibility of a lunar crescent.

[ascl:2307.030] SAMUS: Simulator of Asteroid Malformation Under Stress

SAMUS (Simulator of Asteroid Malformation Under Stress) simulates the deformation of minor bodies, assuming that they are homogenous incompressible fluid masses. They are initialized as ellipsoids and the Navier-Stokes equations are interatively solved to investigate the deformation of the body over time. The software is modular and allows for user-defined output functions, size, and trajectories. Structured as a single large class, SAMUS can store variables and handle arbitrary function calls, which eases debugging and investigation, especially for lengthy high-fidelity simulation runs.

[ascl:2307.029] SIMPLE: Intensity map generator

SIMPLE (Simple Intensity Map Producer for Line Emission) generates intensity maps that include observational effects such as noise, anisotropic smoothing, sky subtraction, and masking. Written in Python, it is based on a lognormal simulation of galaxies and random assignment of luminosities to these galaxies and generates mock intensity maps that can be used to study survey systematics and calculate covariance matrices of power spectra. The code is modular, allowing its components to be used independently.

[ascl:2307.028] TidalPy: Moon and exoplanet tidal heating and dynamics estimator

TidalPy performs semi-analytic calculations of tidal dissipation and subsequent orbit-spin evolution for rocky and icy worlds. It can be used as a black box, in which an Object-Oriented Programming (OOP) scheme performs many calculations with very little user input from the user, making it easy to get started with the package, or as a toolbox, as it contains many efficient functions to perform calculations relevant to tides and thermal-orbital coupling, which can be quickly imported and used in a custom scripts. In general, TidelPy's toolbox (functional) scheme provides much higher performance, flexibility, and extensibility than the OOP scheme. It also makes assumptions more visible to the user. The downside is the user may need to be more familiar with the underlying physics.

[ascl:2307.027] CosmicFish: Cosmology forecasting tool

CosmicFish obtains expected bounds on cosmological parameters for a wide range of models and observables for cosmological forecasting. The package includes a Fortran library to produce Fisher matrices, a Python library that performs operations on the produced Fisher matrices, and a full set of plotting utilities. It works with many models, including CAMB (ascl:1102.026) and MGCAMB (ascl:1106.013), and can interface with any Boltzmann solver. The user can choose within a wide range of possible cosmological observables, including cosmic microwave background, weak lensing tomography, galaxy clustering, and redshift drift. CosmicFish is easy to customize; it provides a flexible package system and users can produce their own analyses and plotting pipelines following the default Python apps.

[ascl:2307.026] gyrointerp: Gyrochronology via interpolation of open cluster rotation sequences

gyrointerp calculates gyrochronal ages by interpolating between open cluster rotation sequences. The framework, written in Python, can be used to find the gyrochronological age posterior of single or many stars. It can also produce a visual interpolation for a star’s age to determine where the star falls in the rotation-temperature plane in comparison to known reference clusters. gyrointerp models the ensemble evolution of rotation periods for main-sequence stars with temperatures of 3800-6200 K (masses of 0.5-1.2 solar) and is not applicable for subgiant or giant stars, and should be used cautiously with binary stars, as they can observationally bias temperature and rotation period measurements.

[ascl:2307.025] pyhalomodel: Halo-model implementation for power spectra

pyhalomodel computes halo-model power spectra for any desired tracer combination. The software requires only halo profiles for the tracers to be specified; these could be matter profiles, galaxy profiles, or something else, such as electron-pressure or HI profiles. pyhalomodel makes it easier to perform basic calculations using the halo model by reducing the changes of variables required to integrate halo profiles against halo mass functions, which can be confusing and tedious.

[ascl:2307.024] SHARK: Gas and dust hydrodynamics with dust coagulation/fragmentation

SHARK solves the hydrodynamic equations for gas and dust mixtures accounting for dust coagulation and fragmentation (among other things). The code is written in Fortran and is capable of handling both 1D and 2D Cartesian geometries; 1D simulations with spherical geometry are also possible. SHARK is versatile and can be used to model various astrophysical environments.

[ascl:2307.023] PyIMRPhenomD: Stellar origin black hole binaries population estimator

PyIMRPhenomD estimates the population of stellar origin black hole binaries for LISA observations using a Bayesian parameter estimation algorithm. The code reimplements IMRPhenomD (ascl:2307.019) in a pure Python code, compiled with the Numba just-in-time compiler. The module implements the analytic first and second derivatives necessary to compute t(f) and t'(f) rather than computing them numerically. Using the analytic derivatives increases the code complexity but produces faster and more numerically accurate results; the improvement in numerical accuracy is particularly significant for t'(f).

[ascl:2307.022] TOAST: Time Ordered Astrophysics Scalable Tools

The TOAST software framework simulates and processes timestream data collected by telescopes. The framework can distribute data among many processes and perform operations on the local pieces of the data, and has generic operators for common processing tasks such as filtering, pointing expansion, and map-making. In addition to offering I/O for a limited set of formats, it provides well-defined interfaces for adding custom I/O classes and processing operators. TOAST is written in C++ with a public Python interface, and contains utilities for controlling the runtime environment, logging, timing, streamed random number generation, quaternion operations, FFTs, and special function evaluation.

[ascl:2307.021] FGBuster: Parametric component separation for Cosmic Microwave Background observations

FGBuster (ForeGroundBuster) separates frequency maps into component maps and forecasts component separation both when the model is correct and when it is incorrect. FGBuster can be used for SED evaluation, intermediate component separation, multi-resolution separation, and forecasting, among other tasks.

[ascl:2307.020] PolyBin: Binned polyspectrum estimation on the full sky

PolyBin estimates the binned power spectrum, bispectrum, and trispectrum for full-sky HEALPix maps such as the CMB. This can include both spin-0 and spin-2 fields, such as the CMB temperature and polarization, or galaxy positions and galaxy shear. Alternatively, one can use only scalar maps. For each statistic, two estimators are available: the standard (ideal) estimators, which do not take into account the mask, and window-deconvolved estimators. For the second case, a Fisher matrix must be computed; this depends on binning and the mask, but does not need to be recomputed for each new simulation. PolyBin can compute both the parity-even and parity-odd components, accounting for any leakage between the two, for the bispectrum and trispectrum.

[ascl:2307.019] IMRPhenomD: Phenomenological waveform model

The IMRPhenomD model generates gravitational wave signals for merging black hole binaries with non-precessing spins. The waveforms are produced in the frequency domain and include the inspiral, merger and ringdown parts for the dominant spherical harmonic mode of the signal. Part of LALSuite (ascl:2012.021) and also available as an independent code, IMRPhenomD is written in C and is calibrated against data from numerical relativity simulations. A re-implementation of IMRPhenomD in Python, PyIMRPhenomD (ascl:2307.023), is available.

[ascl:2307.018] IMRIpy: Intermediate Mass Ratio Inspirals simulator

IMRIpy simulates an Intermediate Mass Ratio Inspiral (IMRI) by gravitational wave emission with a Dark Matter(DM) halo or a (baryonic) Accretion Disk around the central Intermediate Mass Black Hole(IMBH). It can use different density profiles (such as DM spikes), and different interactions, such as dynamical friction with and without HaloFeedback models or accretion, to produce the simulation.

[ascl:2307.017] Veusz: Scientific plotting package

Veusz produces a wide variety of publication-ready 2D and 3D plots. Plots are created by building up plotting widgets with a consistent object-based interface, and the package provides many options for customizing plots. Veusz can import data from text, CSV, HDF5 and FITS files; datasets can also be entered within the program and new datasets created via the manipulation of existing datasets using mathematical expressions and more. The program can also be extended, by adding plugins supporting importing new data formats, different types of data manipulation or for automating tasks, and it supports vector and bitmap output, including PDF, Postscript, SVG and EMF.

[ascl:2307.016] DataComb: Combining data for better images

DataComb combines radio interferometric and single dish observations and obtains quantitative measures of how different techniques perform to obtain better fidelity images. The package relies on CASA (ascl:1107.013) for the combinations and on AstroPy (ascl:1304.002) for making quantitative
comparisons between different images produced by different methods. Model images and simulations are also used to assess the different combination methods.

[ascl:2307.015] BOWIE: Gravitational wave binary signal analysis

BOWIE (Binary Observability With Illustrative Exploration) performs graphical analysis of binary signals from gravitational waves. It takes gridded data sets and produces different types of plots in customized arrangements for detailed analysis of gravitational wave sensitivity curves and/or binary signals. BOWIE offers three main tools: a gridded data generator, a plotting tool, and a waveform generator for general use. The waveform generator creates PhenomD waveforms for binary black hole inspiral, merger, and ringdown. Gridded data sets are created using the PhenomD generator for signal-to-noise (SNR) analysis. Using the gridded data sets, customized configurations of plots are created with the plotting package.

[ascl:2307.014] Synthetic LISA: Simulator for LISA-like gravitational-wave observatories

Synthetic LISA simulates the LISA science process at the level of scientific and technical requirements. The code generates synthetic time series of the LISA fundamental noises, as filtered through all the TDI observables, and provides a streamlined module to compute the TDI responses to gravitational waves, according to a full model of TDI, including the motion of the LISA array, and the temporal and directional dependence of the armlengths.

[ascl:2307.013] SIRENA: Energy reconstruction of X-ray photons for Athena X-IFU

SIRENA (Software Ifca for Reconstruction of EveNts for Athena X-IFU) reconstructs the energy of incoming X-ray photons after their detection in the X-IFU TES detector. It is integrated in the SIXTE (ascl:1903.002) end-to-end simulations environment where it currently runs over SIXTE simulated data. This is done by means of a tool called tesreconstruction, which is mainly a wrapper to pass a data file to the SIRENA tasks.

[ascl:2307.012] mnms: Map-based Noise ModelS

mnms (Map-based Noise ModelS) creates map-based models of Simons Observatory Atacama Cosmology Telescope (ACT) data. Each model supports drawing map-based simulations from data splits with independent realizations of the noise or equivalent, similar to an independent set of time-domain sims. In addition to the ability to create on-the-fly simulations, mnms also includes ready-made scripts for writing a large batch of products to disk in a dedicated SLURM job.

[ascl:2307.011] DiscVerSt: Vertical structure calculator for accretion discs around neutron stars and black holes

DiscVerSt calculates the vertical structure of accretion discs around neutron stars and black holes. Different classes represent the vertical structure for different types of EoS and opacity, temperature gradient and irradiation scheme; the code includes an interface for initializing the chosen structure type. DiscVerSt also contains functions to calculate S-curves and the vertical and radial profile of a stationary disc.

[submitted] Coniferest: Python package for active anomaly detection

Coniferest is a Python package designed for implementing anomaly detection algorithms and interactive active learning tools. The centerpiece of the package is an Isolation Forest algorithm, known for its superior scoring performance and multi-threading evaluation. This robust anomaly detection algorithm operates by constructing random decision trees.

In addition to the Isolation Forest algorithm, Coniferest also offers two modified versions for active learning: AAD Forest and Pineforest. The AAD Forest modifies the Isolation Forest by reweighting its leaves based on responses from human experts, providing a faster alternative to the ad_examples package.

On the other hand, Pineforest, developed by the SNAD team, employs a filtering algorithm that builds and dismantles trees with each new human-machine iteration step.

Coniferest provides a user-friendly interface for conducting interactive human-machine sessions, facilitating the use of these active anomaly detection algorithms. The SNAD team maintains and utilizes this package primarily for anomaly detection in the field of astronomy, with a particular focus on light-curve data from large time-domain surveys.

[ascl:2307.010] baccoemu: Cosmological emulators for large-scale structure statistics

baccoemu provides a collection of emulators for large-scale structure statistics over a wide range of cosmologies. The emulators provide fast predictions for the linear cold- and total-matter power spectrum, the nonlinear cold-matter power spectrum, and the modifications to the cold-matter power spectrum caused by baryonic physics in a wide cosmological parameter space, including dynamical dark energy and massive neutrinos.

[ascl:2307.009] pnautilus: Three-phase chemical code

The three-phase pnautilus chemical code finds the abundance of each species by solving rate equations for gas-phase and grain surface chemistries. It performs gas–grain simulations in which both the icy mantle and the surface are considered active, taking into account mantle photodissociation, diffusion, and reactions; the code also considers the competition among reaction, diffusion and evaporation.

[ascl:2307.008] 21cmvFAST: Adding dark matter-baryon relative velocities to 21cmFAST

21cmvFAST demonstrates that including dark matter (DM)-baryon relative velocities produces velocity-induced acoustic oscillations (VAOs) in the 21-cm power spectrum. Based on 21cmFAST (ascl:1102.023) and 21CMMC (ascl:1608.017), 21cmvFAST accounts for molecular-cooling haloes, which are expected to drive star formation during cosmic dawn, as both relative velocities and Lyman-Werner feedback suppress halo formation. This yields accurate 21-cm predictions all the way to reionization (z>~10).

[ascl:2307.007] AGNvar: Model spectral timing properties in active galactic nuclei

AGNvar calculates the expected reverberation signal in any given energy band, for a given spectral energy distribution (SED), assuming variable X-ray emission. The code predicts the shape of the re-processed continuum by modeling the time-averaged SED according to input parameters, which include geometry, mass, and mass accretion rate; generally the input parameters are based off typical XSPEC (ascl:9910.005) models. It evaluates the SED response to an input driving light-curve (assumed to originate in the X-ray corona) and creates a set of time-dependent SEDs. It then takes the results from the set of time-dependent SEDs and extracts the light-curve in a given band pass.

[ascl:2307.006] pyPplusS: Modeling exoplanets with rings

pyPplusS calculates the light curves for ringed, oblate or spherical exoplanets in both the uniform and limb darkened cases. It can constrain the oblateness of planets using photometric data only. This code can be used to model light curves of more complicated configurations, including multiple planets, oblate planets, moons, rings, and combinations of these, while properly and efficiently taking into account overlapping areas and limb darkening.

[ascl:2307.005] axionHMcode: Non-linear power spectrum calculator

axionHMcode computes the non-linear matter power spectrum in a mixed dark matter cosmology with ultra-light axion (ULA) component of the dark matter. This model uses some of the fitting parameters and is inspired by HMcode (ascl:1508.001). axionHMcode uses the full expanded power spectrum to calculate the non-linear power spectrum; it splits the axion overdensity into a clustered and linear component to take the non clustering of axions on small scales due to free-streaming into account.

[ascl:2307.004] ALF: Absorption line fitter

alf fits the absorption line optical—NIR spectrum. Initially written to constrain the stellar IMF in old massive galaxies, the code now also offers theoretical age and metallicity-dependent response functions covering 19 elements, nuisance parameters to capture uncertainties in stellar evolution, and parameters to capture uncertainties in the data, including modeling telluric absorption and sky line residuals. alf can fit stellar populations with metallicities from approximately -2.0 to +0.3 and performs well when fitting stellar populations ranging from metal-poor globular clusters to brightest cluster galaxies. The software works in continuum-normalized space and so does not make any use of the shape of the continuum (nor of corresponding photometry). Fitting is handled with emcee (ascl:1303.002); the code is MPI parallelized and runs efficiently on many processors, though fitting data with alf is time intensive.

[ascl:2307.003] RelicFast: Fast scale-dependent halo bias

RelicFast computes the scale-dependent bias induced by relics of different masses, spins, and temperatures, through spherical collapse and the peak-background split. The code determines halo bias in under a second, making it possible to include this effect for different cosmologies, and light relics, at little computational cost.

[ascl:2307.002] BE-HaPPY: Bias emulator for halo power spectrum

BE-HaPPY (Bias Emulator for Halo Power spectrum Python) facilitates future large scale surveys analysis by providing an accurate, easy to use and computationally inexpensive method to compute the halo bias in the presence of massive neutrinos. Provided with a linear power spectrum, the package will compute a new power spectrum according to the chosen configuration. BE-HaPPY handles linear, polynomial, and perturbation theory bias models. The code also handles Kaiser and Scoccimarro redshifts; other available options include real or redshift space, the total neutrino mass, and a choice of mass bin or scale array, among others.

[ascl:2307.001] Jdaviz: JWST astronomical data analysis tools in the Jupyter platform

Jdaviz provides data viewers and analysis plugins that can be flexibly combined as desired to create interactive applications. It offers Specviz (ascl:1902.011) for visualization and quick-look analysis of 1D astronomical spectra; Mosviz for visualization of astronomical spectra, including 1D and 2D spectra as well as contextual information, and Cubeviz for visualization of spectroscopic data cubes (such as those produced by JWST MIRI). Imviz, which provides visualization and quick-look analysis for 2D astronomical images, is also included. Jdaviz is designed with instrument modes from the James Webb Space Telescope (JWST) in mind, but the tool is flexible enough to read in data from many astronomical telescopes, and the documentation provides a complete table of all supported modes.

[ascl:2306.060] SCF-FDPS: Disk-halo systems simulator

The fast N-body code SCF-FDPS (Self-Consistent Field-Framework for Developing Particle Simulators) simulates disk-halo systems. It combines a self-consistent field (SCF) code, which provides scalability, and a tree code that is parallelized using the Framework for Developing Particle Simulators (FDPS) (ascl:1604.011). SCF-FDPS handles a wide variety of halo profiles and can be used to study extensive dynamical problems of disk-halo systems.

[ascl:2306.059] BOXFIT: Gamma-ray burst afterglow light curve generator

BOXFIT calculates light curves and spectra for arbitrary observer times and frequencies and of performing (broadband) data fits using the downhill simplex method combined with simulated annealing. The flux value for a given observer time and frequency is a function of various variables that set the explosion physics (energy of the explosion, circumburst number density and jet collimation angle), the radiative process (magnetic field generation efficiency, electron shock-acceleration efficiency and synchrotron power slope for the electron energy distribution) and observer position (distance, redshift and angle). The code can be run both in parallel and on a single core. Because a data fit takes many iterations, this is best done in parallel. Single light curves and spectra can readily be done on a single core.

[ascl:2306.058] GER: Global Extinction Reduction

The Global Extinction Reduction IDL codes compare optical photometry from the twin Gemini North and South Multi-Object Spectrographs (GMOS-N and GMOS-S) against the expected worsening of atmospheric transparency due to global climate change. Data from the Gemini instruments are first reduced by DRAGONS (ascl:1811.002). GER then calibrates them against the Sloan Digital Sky Survey (SDSS) and Gaia G-band catalogs; image rotation and alignment is accomplished via identification of sufficiently-bright stars in Gaia. A simple model of Gemini and their site characteristics is generated, including meteorology, cloudy-fractions, number of reflections, dates of re-coatings modulated by rate of efficiency decay, together with response of detectors and associated zeropoints, and can be compared with the decline of transparency due to rising temperature and associated humidity increase.

[ascl:2306.057] pybranch: Calculate experimental branching fractions and transition probabilities from atomic spectra

pybranch calculates experimental branching fractions and transition probabilities from measurements of atomic spectra. Though the program is usually used with spectral line lists from intensity-calibrated spectra from Fourier transform spectrometers, it can in principle be used with any calibrated spectra that meet the input requirements. pybranch takes a set of linelists, computes a weighted average branching fraction (Fki) for each line, combines these branching fractions with the level lifetime to obtain the transition probability, and then prints the calibrated intensities and S/N ratios for all the lines observed from a particular upper level in each spectrum. One line can be chosen to use as a reference to put all of the intensities on the same scale. pybranch can use calculated transition probabilities to calculate a residual from lines that have not been observed.

[ascl:2306.056] PSFMachine: Toolkit for doing PSF photometry

PSFMachine creates models of instrument effective Point Spread Functions (ePSFs), also called Pixel Response Functions (PRFs). These models are then used to fit a scene in a stack of astronomical images. PSFMachine is able to quickly derive photometry from stacks of Kepler and TESS images and separate crowded sources.

[ascl:2306.055] ESSENCE: Evaluate spatially correlated noise in interferometric images

ESSENCE (Evaluating Statistical Significance undEr Noise CorrElation) evaluates the statistical significance of image analysis and signal detection under correlated noise in interferometric images (e.g., ALMA, NOEMA). It measures the noise autocorrelation function (ACF) to fully characterize the statistical properties of spatially correlated noise in the interferometric image, computes the noise in the spatially integrated quantities (e.g., flux, spectrum) with a given aperture, and simulates noise maps with the same correlation property. ESSENSE can also construct a covariance matrix from noise ACF, which can be used for a 2d image or 3d cube model fitting.

[ascl:2306.054] threepoint: Covariance of third-order aperture statistics

threepoint models the third-order aperture statistics, the natural components of the shear three-point correlation function and the covariance of third-order aperture statistics. Third-order weak lensing statistics extract cosmological information in the non-Gaussianity of the cosmic large-scale structure, making them a promising tool for cosmological analyses.

[ascl:2306.053] TiDE: Light curves and spectra of tidal disruption events

TiDE (TIdal Disruption Event) computes the light curves or spectrum of tidal disruption events. Written in C++, it can compute the monochromatic light curve without diffusion, including the total luminosity, wind luminosity and disk luminosity, and the monochromatic light curve with diffusion. TiDE can also model the bolometric luminosity and calculate the spectrum at a given time, including the wind luminosity and disk luminosity. This code can be used to explore the possible parameter space and reveal potential biases caused by the model assumptions, and can be extended with new models, allowing one to compare and test different prescriptions and model assumptions under the same circumstances.

[ascl:2306.052] kilopop: Binary neutron star population of optical kilonovae

kilopop produces binary neutron star kilonovae in the grey-body approximation. It can also create populations of these objects useful for forecasting detection and testing observing scenarios. Additionally, it uses an emulator for the grey-opacity of the material calibrated against a suite of numerical radiation transport simulations with the code SuperNu (ascl:2103.019).

[ascl:2306.051] Hitomi: Cosmological analysis of anisotropic galaxy distributions

Hitomi provides a comprehensive set of codes for cosmological analysis of anisotropic galaxy distributions using two- and three-point statistics: two-point correlation function (2PCF), power spectrum, three-point correlation function (3PCF), and bispectrum. The code can measure the Legendre-expanded 2PCF and power spectrum from an observed sample of galaxies, and can measure the 3PCF and bispectrum expanded using the Tripolar spherical harmonic (TripoSH) function. Hitomi is basically a serial code, but can also implement MPI parallelization. Hitomi uses MPI to read multiple different input parameters simultaneously.

[ascl:2306.050] SubgridClumping: Clumping factor for large low-resolution N-body simulations

SubgridClumping derives the parameters for the global, in-homogeneous and stochastic clumping model and then computes the clumping factor for large low-resolution N-body simulations smoothed on a regular grid. Written for the CUBEP3M simulation, the package contains two main modules. The first derives the three clumping model parameters for a given small high-resolution simulation; the second computes a clumping factor cube (same mesh-size as input) for the three models for the given density field of a large low-resolution simulation.

[ascl:2306.049] ARPACK-NG: Large scale eigenvalue problem solver

ARPACK-NG provides a common repository with maintained versions and a test suite for the ARPACK (ascl:1311.010) code, which is no longer updated; it is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. ARPACK-NG offers routines for banded matrices, singular value decomposition, single and double precision real arithmetic versions for symmetric, non-symmetric standard or generalized problems, and a reverse communication interface (RCI). It also provides example driver routines that may be used as templates to implement numerous shift-invert strategies for all problem types, data types and precision, in addition to other tools. The ARPACK-NG project, started by Debian, Octave, and Scilab, is now a community project maintained by volunteers.

[ascl:2306.048] MG-PICOLA: Simulating cosmological structure formation

MG-PICOLA is a modified version of L-PICOLA (ascl:1507.004) that extends the COLA approach for simulating cosmological structure formation to theories that exhibit scale-dependent growth. It can compute matter power-spectra (CDM and total), redshift-space multipole power-spectra P0,P2,P4 and do halofinding on the fly.

[ascl:2306.047] COLASolver: Particle-Mesh N-body code

COLASolver creates Particle-Mesh (PM) N-body simulations; the code is fast and very flexible, and can compute a wide range of models. For models with complex dynamics (screened models), it provides several options from doing it exactly to approximate but fast to just simulating linear theory equations. Every time-consuming operation is parallelized over MPI and OpenMP. It uses a slab-based parallelization that works well for fast approximate (COLA) simulations but does not perform as well for high resolution simulations. COLASolver can also be used as an analysis code for results from other simulations.

[ascl:2306.046] CHIPS: Circumstellar matter and light curves of interaction-powered transients simulator

CHIPS (Complete History of Interaction-Powered Supernovae) simulates the circumstellar matter and light curves of interaction-powered transients. Coupled with MESA (ascl:1010.083), the combined codes can obtain the circumstellar matter profile and light curves of the interaction-powered supernovae. CHIPS generates a realistic CSM from a model-agnostic mass eruption calculation, which can serve as a reference for observers to compare with various observations of the CSM. The code can also generate bolometric light curves from CSM interaction, which can be compared with observed light curves. The calculation of mass eruption and light curve typically takes respectively half a day and half an hour on modern CPUs.

[ascl:2306.045] nuPyProp: Propagate neutrinos through the earth

nuPyProp simulates tau neutrino and muon neutrino interactions in the Earth and predicts the spectrum of the τ-leptons and muons that emerge. The code produces tables of charged lepton exit probabilities and energies that can be used directly or as inputs to nuSpaceSim (ascl:2306.043), which is designed to simulate optical and radio signals from extensive air showers induced by the emerging charged leptons.

[ascl:2306.044] nuSpaceSim: Cosmic neutrino simulation

nuSpaceSim simulates upward-going extensive air showers caused by neutrino interactions with the atmosphere. It is an end-to-end, neutrino flux to space-based signal detection, modeling tool for the design of sub-orbital and space-based neutrino detection experiments. This comprehensive suite of modeling packages accepts an experimental design input and then models the experiment's sensitivity to both the diffuse, cosmogenic neutrino flux as well as astrophysical neutrino transient events, such as that postulated from binary neutron star (BNS) mergers. nuSpaceSim calculates the tau neutrino acceptance for the Optical Cherenkov technique; tau propagation is interpolated using included data tables from nupyprop (ascl:2306.044). The simulation is parameterized by an input XML configuration file, with settings for detector characteristics and global parameters; nuSpaceSim also provides a python API for programmatic access.

[ascl:2306.043] SHERLOCK: Explore Kepler, K2, and TESS data

The end-to-end SHERLOCK (Searching for Hints of Exoplanets fRom Lightcurves Of spaCe-based seeKers) pipeline allows users to explore data from space-based missions to search for planetary candidates. It can recover alerted candidates by the automatic pipelines such as SPOC and the QLP, Kepler objects of interest (KOIs) and TESS objects of interest (TOIs), and can search for candidates that remain unnoticed due to detection thresholds, lack of data exploration, or poor photometric quality. SHERLOCK has six different modules to perform its tasks; these modules can be executed by filling in an initial YAML file with some basic information and using a few lines of code sequentially to pass from one step to the next. Alternatively, the user may provide with the light curve in a csv file, where the time, normalized flux, and flux error are provided in columns in comma-separated format.

[ascl:2306.042] CONDUCT: Electron transport coefficients of magnetized stellar plasmas

CONDUCT calculates all components of kinetic tensors in fully ionized electron-ion plasmas at arbitrary magnetic field. It employs a thermal averaging with the Fermi distribution function and can be used when electrons are partially degenerate; it provides, along with the electrical and thermal conductivities, also thermopower (thermoelectric coefficient). CONDUCT takes into account collisions of the electrons with ions and (in solid phase) charged impurities as well as quantum effects on ionic motion in the solid phase. The code's outputs are the longitudinal, transverse, and off-diagonal (Hall) components of electrical and thermal conductivity tensors as well as the components of thermoelectric tensor.

[ascl:2306.041] COFFE: COrrelation Function Full-sky Estimator

COFFE (COrrelation Function Full-sky Estimator) computes quantities in linear perturbation theory. It computes the full-sky and flat-sky 2-point correlation function (2PCF) of galaxy number counts, taking into account all of the effects, including density, RSD, and lensing. It also determines the full-sky, flat-sky, and redshift-averaged multipoles of the 2PCF, and the flat-sky Gaussian covariance matrix of the multipoles of the 2PCF.

[ascl:2306.040] PEPITA: Prediction of Exoplanet Precisions using Information in Transit Analysis

PEPITA (Prediction of Exoplanet Precisions using Information in Transit Analysis) makes predictions for the precision of exoplanet parameters using transit light-curves. The code uses information analysis techniques to predict the best precision that can be obtained by fitting a light-curve without actually needing to perform the fit, thus allowing more efficient planning of observations or re-observations.

[ascl:2306.039] GRChombo: Numerical relativity simulator

GRChombo performs numerical relativity simulations. It uses Chombo (ascl:1202.008) for adaptive mesh refinement and can evolve standard spacetimes such as binary black hole mergers and scalar collapses into black holes. The code supports non-trivial many-boxes-in-many-boxes mesh hierarchies and massive parallelism and evolves the Einstein equation using the standard BSSN formalism. GRChombo is written in C++14 and uses hybrid MPI/OpenMP parallelism and vector intrinsics to achieve good performance.

[ascl:2306.038] FacetClumps: Molecular clump detection algorithm based on Facet model

FacetClumps extracts and analyses clumpy structure in molecular clouds. Written in Python and based on the Gaussian Facet model, FacetClumps extracts signal regions using morphology, and segments the signal regions into local regions with a gradient-based method. It then applies a connectivity-based minimum distance clustering method to cluster the local regions to the clump centers. FacetClumps automatically adjusts its parameters to local situations to improve adaptability, and is optimized to detect faint and overlapping clumps.

[ascl:2306.037] CADET: X-ray cavity detection tool

The machine learning pipeline CADET (CAvity DEtection Tool) finds and size-estimates arbitrary surface brightness depressions (X-ray cavities) on noisy Chandra images of galaxies. The pipeline is a self-standing Python script and inputs either raw Chandra images in units of counts (numbers of captured photons) or normalized background-subtracted and/or exposure-corrected images. CADET saves corresponding pixel-wise as well as decomposed cavity predictions in FITS format and also preserves the WCS coordinates; it also outputs a PNG file showing decomposed predictions for individual scales.

[ascl:2306.036] IDEFIX: Astrophysical fluid dynamics

Idefix solves non-relativistic HD and MHD equations on various grid geometries. Based on a Godunov finite-volume method, this astrophysical flows code includes a wide choice of solvers and several modules, including constrained transport, orbital advection, and non-ideal MHD, to address complex astrophysical and fluid dynamics applications. Written in C++, Idefix relies on the Kokkos meta-programming library to guarantee performance portability on a wide variety of architectures.

[ascl:2306.035] CONCEPT: COsmological N-body CodE in PyThon

CONCEPT (COsmological N-body CodE in PyThon) simulates cosmological structure formation. It can simulate matter particles evolving under self-gravity in an expanding background. The code offers multiple gravitational solvers and has adaptive time integration built in. In addition to particles, CONCEPT also evolves fluids at various levels of non-linearity, providing the means for the inclusion of more exotic species such as massive neutrinos, as well as for simulations consistent with general relativistic perturbation theory. Various non-standard species, such as decaying cold dark matter, are fully supported. CONCEPT includes a sophisticated initial condition generator and can output snapshots, power spectra, bispectra ,and several kinds of renders.

[ascl:2306.034] COLT: Monte Carlo radiative transfer and simulation analysis toolkit

COLT (Cosmic Lyman-alpha Transfer) is a Monte Carlo radiative transfer (MCRT) solver for post-processing hydrodynamical simulations on arbitrary grids. These include a plane parallel slabs, spherical geometry, 3D Cartesian grids, adaptive resolution octrees, unstructured Voronoi tessellations, and secondary outputs. COLT also includes several visualization and analysis tools that exploit the underlying ray-tracing algorithms or otherwise benefit from an efficient hybrid MPI + OpenMP parallelization strategy within a flexible C++ framework.

[ascl:2306.033] lasso_spectra: Predict properties from galaxy spectra using Lasso regression

lasso_spectra fits Lasso regression models to data, specifically galaxy spectra. It contains two classes for performing the actual model fitting. GeneralizedLasso is a tensorflow implementation of Lasso regression, which includes the ability to use link functions. SKLasso is a wrapper around the scikit-learn Lasso implementation intended to give the same syntax as GeneralizedLasso. It is much faster and more reliable, but does not support generalized linear models.

[ascl:2306.032] CosmoGraphNet: Cosmological parameters and galaxy power spectrum from galaxy catalogs

CosmoGraphNet infers cosmological parameters or the galaxy power spectrum. It creates a graph from a galaxy catalog with information the 3D position and intrinsic galactic properties. A Graph Neural Network is then applied to predict the cosmological parameters or the galaxy power spectrum.

[ascl:2306.031] ECLIPSE: Efficient Cmb poLarization and Intensity Power Spectra Estimator

ECLIPSE (Efficient Cmb poLarization and Intensity Power Spectra Estimator) implements an optimized version of the Quadratic Maximum Likelihood (QML) method for the estimation of the power spectra of the Cosmic Microwave Background (CMB) from masked skies. Written in Fortran, ECLIPSE can be used in a personal computer but also benefits from the capabilities of a supercomputer to tackle large scale problems; it is designed to run parallel on many MPI tasks. ECLIPSE analyzes masked CMB maps in which the signal can be affected by the beam and pixel window functions. The masks of intensity and polarization can be different and the noise can be isotropic or anisotropic. The program can estimate auto and cross-correlation power spectrum, that can be binned or unbinned.

[ascl:2306.030] Butterpy: Stellar butterfly diagram and rotational light curve simulator

Butterpy simulates star spot emergence, evolution, decay, and stellar rotational light curves. It tests the recovery of stellar rotation periods using different frequency analysis techniques. Butterpy can simulate light curves of stars with variable activity level, rotation period, spot lifetime, magnetic cycle duration and overlap, spot emergence latitudes, and latitudinal differential rotation shear.

[ascl:2306.029] Mixclask: Mixing Cloudy and SKIRT

Mixclask combines Cloudy (ascl:9910.001) and SKIRT (ascl:1109.003) to predict spectra and gas properties in astrophysical contexts, such as galaxies and HII regions. The main output is the mean intensity of a region filled with stars, gas and dust at different positions, assuming axial symmetry. The inputs for Mixclask are the stellar and ISM data for each region and an file for the positions (x,y,z) that will be output.

[ascl:2306.028] rfast: Planetary spectral forward and inverse modeling tool

rfast ingests tables of opacities and generates synthetic spectra of worlds and retrieves real or simulated spectral observations. It can add noise, perform inverse modeling, and plot results. The tool can be applied to simulated and real observations spanning reflected-light, thermal emission, and transit transmission. Retrieval parameters can be toggled and parameters can be retrieved in log or linear space and adopt a Gaussian or flat prior.

[ascl:2306.027] PEP: Planetary Ephemeris Program

Planetary Ephemeris Program (PEP) computes numerical ephemerides and simultaneously analyzes a heterogeneous collection of astrometric data. Written in Fortran, it is a general-purpose astrometric data-analysis program and models orbital motion in the solar system, determines orbital initial conditions and planetary masses, and has been used to, for example, measure general relativistic effects and test physics theories beyond the standard model. PEP also models pulsar motions and distant radio sources, and can solve for sky coordinates for radio sources, plasma densities, and the second harmonic of the Sun's gravitational field.

[ascl:2306.026] Parthenon: Portable block-structured adaptive mesh refinement framework

The Parthenon framework, derived from Athena++ (ascl:1912.005), handles massively-parallel, device-accelerated adaptive mesh refinement. It provides a device first/device resident approach, transparent packing of data across blocks (to reduce/hide kernel launch latency), and direct device-to-device communication via asynchronous, one-sided MPI communication to enable high performance. Parthenon uses an intermediate abstraction layer to hide complexity of device kernel launches, offers support for particles and abstract variable control via metadata tags, and has a flexible plug-in package system.

[ascl:2306.025] ALminer: ALMA archive mining and visualization toolkit

ALminer queries, analyzes, and visualizes the ALMA Science Archive. Users can programmatically query the archive for positions, target names, or other keywords in the archive metadata (such as proposal title, abstract, or scientific category). ALminer's plotting routines allow the query results to be visualized, and its analysis functions allow users to filter the results and check whether certain frequencies of interest are covered in the queried observations. The code also allows users to directly download ALMA data products in FITS format and/or the raw data that can be used for manual image processing. ALminer has been designed to make mining the ALMA archive as simple as possible, while being flexible to be customized according to the user's scientific interests. The code is released with a detailed tutorial Jupyter notebook, introducing ALminer's common functions as well as some of its more advanced options.

[ascl:2306.024] COpops: Compute CO sizes and fluxes

COpops computes semi-analytically the CO flux of a disc (given initial conditions and age) under the assumption of LTE and optically thick emission. It then runs disc population synthesis using observationally-informed initial conditions. CO fluxes is one of the most easily accessible observables for studying disc evolution; COpops is a faster alternative to running computationally-expensive thermochemical models for hundreds of discs and is accurate, recovering agreement within a factor of three.

[ascl:2306.023] RELAGN: AGN SEDs with full GR ray tracing

RELAGN creates spectral models for the calculation of AGN SEDs, ranging from the Optical/UV (outer accretion disc) to the Hard X-ray (Innermost X-ray Corona). The code is available in two languages, Python and Fortran. The Fortran version is written to be used with the spectral fitting software XSPEC (ascl:9910.005), and is the preferred version for analyzing X-ray spectral data. The Python version provides more flexibility for modeling. Whereas the Fortran version produces only a spectrum, the Python implementation can extract the physical properties of the system (such as the physical mass accretion rate, disc size, and efficiency parameters) since these are all stored as attributes within the model. Both versions require a working installation of HEASOFT (ascl:1408.004).

[ascl:2306.022] apollinaire: Helioseismic and asteroseismic peakbagging frameworks

apollinaire provides functions and a framework for helioseismic and asteroseismic instruments data managing and analysis, and includes all the tools necessary to analyze the acoustic oscillations of solar-like stars. The core of the package is the peakbagging library, which provides a full framework to extract oscillation modes parameters from solar and stellar power spectra.

[ascl:2306.021] pipes_vis: Interactive GUI and visualizer tool for SPS spectra

pipes_vis is an interactive graphical user interface for visualizing SPS spectra. Powered by Bagpipes (ascl:2104.017), it provides real-time manipulation of a model galaxy's star formation history, dust, and other relevant properties through sliders and text boxes.

[ascl:2306.020] mockFRBhosts: Limiting the visibility and follow-up of FRB host galaxies

mockFRBhosts estimates the fraction of FRB hosts that can be cataloged with redshifts by existing and future optical surveys. The package uses frbpoppy (ascl:1911.009) to generate a population of FRBs for a given radio telescope. For each FRB, a host galaxy is drawn from a data base generated by GALFORM (ascl:1510.005). The galaxies' magnitudes in different photometric surveys are calculated as are the number of bands in which they are detected. mockFRBhosts also calculates the follow-up time in a 10-m optical telescope required to do photometry or spectroscopy and provides a simple interface to Bayesian inference methods via MCMC simulations provided in the FRB package (ascl:2306.018).

[ascl:2306.019] realfast: Real-time interferometric data analysis for the VLA

The transient search pipeline realfast integrates with the real-time environment at the Very Large Array (VLA) to look for fast radio bursts, pulsars, and other rare astrophysical transients. The software monitors multicast messages, catches visibility data, and defines a fast transient search pipeline with rfpipe (ascl:1710.002). It indexes candidate transients and other metadata for the search interface, and writes and archives new visibility files for candidate transients. realfast provides support for GPU algorithms, manages distributed futures, and performs blind injection and management of mock transients, among other tasks, and rapidly distributes data products and transient alerts to the public.

[ascl:2306.018] FRB: Fast Radio Burst calculations, estimations, and analysis

FRB performs calculations, estimations, analysis, and Bayesian inferences for Fast Radio Bursts, including dispersion measure and emission measure calculations, derived properties and spectrums, and Galactic RM.

[ascl:2306.017] Zeus21: Simulations of 21-cm at cosmic dawn

Zeus21 (Zippy Early-Universe Solver for 21-cm) captures the nonlocal and nonlinear physics of cosmic dawn to create an effective model for the 21-cm power spectrum and global signal. The code takes advantage of the approximate log-normality of the star-formation rate density (SFRD) during cosmic dawn to compute the 21-cm power spectrum analytically. It agrees with more expensive semi-numerical simulations to roughly 10% precision, but has comparably negligible computational cost (~ s) and memory requirements. Zeus21 pairs well with data from HERA, but can be used for any 21-cm inference or prediction. Its capabilities include finding the 21-cm power spectrum (at a broad range of k and z), the global signal, IGM temperatures (Tk, Ts, Tcolor), neutral fraction xHI, Lyman-alpha fluxes, and the evolution of the SFRD; all across cosmic dawn z=5-35. It can also predict UVLFs for HST and JWST. Zeus21 can use three different astrophysical models, one of which emulates 21cmFAST (ascl:1102.023), and can vary the cosmology through CLASS (ascl:1106.020).

[ascl:2306.016] SuperRad: Black hole superradiance gravitational waveform modeler

SuperRad models ultralight boson clouds that arise through black hole superradiance. It uses numerical results in the relativistic regime combined with analytic estimates to describe the dynamics and gravitational wave signals of ultralight scalar or vector clouds. Written in Python, SuperRad includes a set of testing routines that check the internal consistency of the package; these tests mainly serve the purpose of ensuring functionality of the waveform model but can also be utilized to check that SuperRad works as intended.

[ascl:2306.015] Mangrove: Infer galaxy properties using dark matter merger trees

Mangrove uses Graph Neural Networks to regress baryonic properties directly from full dark matter merger trees to infer galaxy properties. The package includes code for preprocessing the merger tree, and training the model can be done either as single experiments or as a sweep. Mangrove provides loss functions, learning rate schedulers, models, and a script for doing the training on a GPU.

[ascl:2306.014] AIOLOS: Planetary atmosphere accretion and escape simulations

AIOLOS solves differential equations for hydrodynamics, friction, (thermal) radiation transport and (photo)chemistry for simulating accretion onto, and hydrodynamic escape from, planetary atmospheres. The 1-D multispecies, multiphysics hydrodynamics code, written in C++, compiles in a flexible mode that runs problems with any number of input species, and can be sped up by setting the number of species at compile time, and allows the user to provide initial conditions or boundary conditions if desired. AIOLOS provides output and diagnostic files that give snapshots in time of the state of the simulation. Output files are specific to each species, and diagnostic files contain summary as well as detailed information for, for example, the radiation transport, opacities for all species, and optical cell depths per band, in addition to other information.

[ascl:2306.013] SCONCE-SCMS: Spherical and conic cosmic web finders with extended SCMS algorithms

SCONCE-SCMS detects cosmic web structures, primarily cosmic filaments and the associated cosmic nodes, from a collection of discrete observations with the extended subspace constrained mean shift (SCMS) algorithms on the unit (hyper)sphere (in most cases, the 2D (RA,DEC) celestial sphere), and the directional-linear products space (most commonly, the 3D (RA,DEC,redshift) light cone).

The subspace constrained mean shift (SCMS) algorithm is a gradient ascent typed method dealing with the estimation of local principal curves, more widely known as density ridges. The one-dimensional density ridge traces over the curves where observational data are highly concentrated and thus serves as a natural model for cosmic filaments in our Universe. Modeling cosmic filaments as density ridges enables efficient estimation by the kernel density estimator (KDE) and the subsequent SCMS algorithm in a statistically consistent way. While the standard SCMS algorithm can identify the density ridges in any "flat" Euclidean space, it exhibits large bias in estimating the density ridges on the data space with a non-linear curvature. The extended SCMS algorithms used in SCONCE-SCMS are adaptive to the spherical and conic geometries and resolve the estimation bias of the standard SCMS algorithm on a 2D (RA,DEC) celestial sphere or 3D (RA,DEC,redshift) light cone.

[ascl:2306.012] ZodiPy: Zodiacal emission simulations in timestreams or HEALPix for solar system observers

ZodiPy simulates the zodiacal emission in intensity that an arbitrary solar system observer is predicted to see given an interplanetary dust model, either in the form of timestreams or full-sky HEALPix maps. Written in Python, the code makes zodiacal emission simulations more accessible by providing a simple interface to existing models.

[ascl:2306.011] margarine: Posterior sampling and marginal Bayesian statistics

Margarine computes marginal bayesian statistics given a set of samples from an MCMC or nested sampling run. Specifically, the code calculates marginal Kullback-Leibler divergences and Bayesian dimensionalities using Masked Autoregressive Flows and Kernel Density Estimators to learn and sample posterior distributions of signal subspaces in high dimensional data models, and determines the properties of cosmological subspaces, such as their log-probability densities and how well constrained they are, independent of nuisance parameters. Margarine thus allows for direct and specific comparison of the constraining ability of different experimental approaches, which can in turn lead to improvements in experimental design.

[ascl:2306.010] MOBSE: Massive Objects in Binary Stellar Evolution

MOBSE investigates the demography of merging BHBs. A customized version of the binary stellar evolution code BSE (ascl:1303.014), MOBSE includes metallicity-dependent prescriptions for mass-loss of massive hot stars and upgrades for the evolution of single and binary massive stars.

[ascl:2306.009] Albatross: Stellar stream parameter inference with neural ratio estimation

Albatross analyzes Milky Way stellar streams. This Simulation-Based Inference (SBI) library is built on top of swyft (ascl:2302.016), which implements neural ratio estimation to efficiently access marginal posteriors for all parameters of interest. Using swyft for its internal Truncated Marginal Neural Ratio Estimation (TMNRE) algorithm and sstrax (ascl:2306.008) for fast simulation and modeling, Albatross provides a modular inference pipeline to support parameter inference on all relevant parts of stellar stream models.

[ascl:2306.008] sstrax: Fast stellar stream modelling in JAX

sstrax provides fast simulations of Milky Way stellar stream formation. Using JAX (ascl:2111.002) acceleration to support code compilation, sstrax forward models all aspects of stream formation, including evolution in gravitational potentials, tidal disruption and observational models, in a fully modular way. Although sstrax is a standalone python package, it was also developed to integrate directly with the Albatross (ascl:2306.009) inference pipeline, which performs inference on all relevant aspects of the stream model.

[ascl:2306.007] PhotoParallax: Data-driven photometric parallaxes built with Gaia and 2MASS

PhotoParallax calculates photometric parallaxes for distant stars in the Gaia TGAS catalog without any use of physical stellar models or stellar density models of the Milky Way. It uses the geometric parallaxes to calibrate a photometric model that is purely statistical, which is a model of the data rather than a model of stars per se.

[ascl:2306.006] β-SGP: Scaled Gradient Projection algorithm using β-divergence

β-SGP deconvolves an astronomical image with a known Point Spread Function, providing a means for restoration of telescopic images due to issues ranging from atmospheric turbulence to instrumental aberrations. The code supports improved astrometry, deblending of overlapping sources, faint source detection, and identification of point sources near bright extended objects, and other tasks. β-SGP generalizes the Scaled Gradient Projection (SGP) image deconvolution algorithm using β-divergence as a loss function to restore distorted stellar shapes.

[ascl:2306.005] Delight: Photometric redshift via Gaussian processes with physical kernels

Delight infers photometric redshifts in deep galaxy and quasar surveys. It uses a data-driven model of latent spectral energy distributions (SEDs) and a physical model of photometric fluxes as a function of redshift, thus leveraging the advantages of both machine- learning and template-fitting methods by building template SEDs directly from the training data. Delight obtains accurate redshift point estimates and probability distributions and can also be used to predict missing photometric fluxes or to simulate populations of galaxies with realistic fluxes and redshifts.

[submitted] Turbospectrum_NLTE

Latest version of TS (Turbospectrum), with NLTE capabilities.
Computation of stellar spectra (flux and intensities) in 1D or average stellar atmosphere models.
In order to compute NLTE stellar spectra, additional data is needed, downloadable outside GitHub.
See documentation in DOC folder

Python wrappers are available at https://github.com/EkaterinaSe/TurboSpectrum-Wrapper/ and https://github.com/JGerbs13/TSFitPy
They allow interpolation between models and fitting of spectra to derive stellar parameters.

[ascl:2306.004] TIDYMESS: TIdal DYnamics of Multi-body ExtraSolar Systems

The N-body code TIDYMESS (TIdal DYnamics of Multi-body ExtraSolar Systems) can describe the mass distribution of each body its inertia tensor and directly and self-consistently integrates orbit, spin, and inertia tensors. It manages the deformation of a body follows the tidal Creep model and includes the centrifugal force and tidal force. Written in C++, TIDYMESS is available as a standalone package and also through the AMUSE framework (ascl:1107.007).

[ascl:2306.003] SAVED21cm: Global 21cm signal extraction pipeline

SAVED21cm extracts the 21cm signal from the simulated mock observation for the Radio Experiment for the Analysis of Cosmic Hydrogen (REACH). Though built for the REACH experiment, this 21cm signal extraction pipeline can in principle can be utilized for any global 21cm experiment. The toolkit is based on a pattern recognition framework using the Singular Value Decomposition (SVD) of the 21cm and foreground training set. SAVED21cm finds the patterns in the training sets and properly models the chromatic distortions with a better basis than the polynomials.

[ascl:2306.002] sbi: Simulation-based inference toolkit

Simulation-based inference is the process of finding parameters of a simulator from observations. The PyTorch package sbi performs simulation-based inference by taking a Bayesian approach to return a full posterior distribution over the parameters, conditional on the observations. This posterior can be amortized (i.e. useful for any observation) or focused (i.e.tailored to a particular observation), with different computational trade-offs. The code offers a simple interface for one-line posterior inference.

[ascl:2306.001] HAFFET: Supernovae photometric and spectroscopic data analyzer

HAFFET (Hybrid Analytic Flux FittEr for Transients) analyzes supernovae photometric and spectroscopic data. It handles observational data for a set of targets, estimates their physical parameters, and visualizes the population of inferred parameters. HAFFET defines two classes, snobject for data and fittings for one specific object, and snelist to organize the overall running for a list of objects. The HAFFET package includes utilities for downloading SN data from online sources, intepolating multi band lightcurves, characterizing the first light and rising of SNe with power law fits, and matching epochs of different bands. It can also calculate colors, and/or construct the spectral energy distribution (SED), estimate bolometric LCs and host galaxy extinction, fit the constructed bolometric lightcurves to different models, and identify and fit the absorption minima of spectral lines, in addition to performing other tasks. In addition to utilizing the built-in models, users can add their own models or import models from other python packages.

[ascl:2305.025] CELEBI: Precision localizations and polarimetric data for fast radio bursts

The Australian Square Kilometre Array Pathfinder (ASKAP) has been enabled by the Commensal Real-time ASKAP Fast Transients Collaboration (CRAFT) to detect Fast Radio Bursts (FRBs) in real-time and save raw antenna voltages containing FRB detections. CELEBI, the CRAFT Effortless Localization and Enhanced Burst Inspection pipeline, extends CRAFT’s existing software to process ASKAP voltages to produce sub-arcsecond precision localizations and polarimetric data at time resolutions as fine as 3 ns of FRB events. CELEBI uses Nextflow (ascl:2305.024) to link together Bash and Python code to perform software correlation, interferometric imaging, and beamforming, thereby making use of common astronomical software packages.

[ascl:2305.024] Nextflow: DSL for data-driven computational pipelines

Nextflow enables scalable and reproducible scientific workflows using software containers. It allows the adaptation of pipelines written in the most common scripting languages. Its fluent DSL simplifies the implementation and the deployment of complex parallel and reactive workflows on clouds and clusters. Nextflow supports deploying workflows on a variety of execution platforms including local, HPC schedulers, AWS Batch, Google Cloud Life Sciences, and Kubernetes. Additionally, it provides support for workflow dependencies through built-in support for, for example, Conda, Spack, Docker, Podman, Singularity, and Modules.

[ascl:2305.023] GLASS: Cosmological simulations on the sphere

GLASS (Generator for Large Scale Structure) produces cosmological simulations on the sphere. The full, three-dimensional past light cone of the observer is discretized into a sequence of nested shells, which are further discretized in the angular dimensions into maps of the sphere. GLASS was originally designed to simulate cosmic matter, weak gravitational lensing, and galaxy positions, but its flexible design and open architecture allows it to be used for a wide range of cosmological and astrophysical simulations on the sphere.

[ascl:2305.022] GrGadget: Evolve metric perturbations in the weak field limit

GrGadget merges the Particle-Mesh (PM) relativistic GEVOLUTION code (ascl:1608.014) with the TreePM GADGET-4 code (ascl:2204.014) to create a TreePM simulation code that represents metric perturbations at the scales where they are relevant while resolving non-linear structures. The better resolution of the highly non-linear regime improves the representation of the relativistic fields sampled on the mesh with respect to PM-only simulations.

[ascl:2305.021] COLIBRI: Cosmological libraries in Python

COLIBRÌ (which roughly stands for “Cosmological Libraries”) computes cosmological quantities such as ages, distances, power spectra, and correlation functions. It supports Lambda-CDM cosmologies plus extensions including massive neutrinos, non-flat geometries, evolving dark energy (w0-wa) models, and numerical recipes for f(R) gravity. COLIBRÌ is built especially for large-scale structure purposes and can interact with the Boltzmann solvers CAMB (ascl:1102.026) and CLASS (ascl:1106.020).

[ascl:2305.020] JEDI: James's EVE Dimming Index

JEDI searches for and characterizes coronal dimming in light curves produced from the Solar Dynamics Observatory (SDO) Extreme Ultraviolet (EUV) Variability Experiment (EVE). The suite has a wrapper script that calls other functions, which can also be run independently assuming needed inputs from prior functions are provided. JEDI's functions fit light curves and return the best fit, compute precision for iron light curves, and find the biggest dimming depth and its time in a given light curve. JEDI also includes functions for finding the duration of the dimming, minimum, maximum, and mean slope of dimming of a light curve, and for identifying the biggest peak in two light curves, time shifting them so the peaks are concurrent, scaling them so the peaks are the same magnitude, and then subtracting them, among other useful functions.

[ascl:2305.019] sterile-dm: Sterile neutrino production

The sterile neutrino production code sterile-dm incorporates new elements to the calculations of the neutrino opacity at temperatures 10 MeV ≤ T ≤ 10 GeV and folds the asymmetry redistribution and opacity calculations into the sterile neutrino production computation, providing updated PSDs for the range of parameters relevant to the X-ray excess. The code requires several data files, which are included. With each run, sterile-dm creates a new output sub-directory that contains a parameter file listing the mass, mixing angle, initial lepton asymmetry and other information, a state file, which includes, among other states, the temperature and FRW coordinate time, and a set of snapshot files, one for each line in the state file.

[ascl:2305.018] GWSurrogate: Gravitational wave surrogate models

GWSurrogate provides an easy to use interface to gravitational wave surrogate models. Surrogates provide a fast and accurate evaluation mechanism for gravitational waveforms which would otherwise be found through solving differential equations. These equations must be solved in the “building” phase, which was performed using other codes.

[ascl:2305.017] simple-m2m: Extensions to the standard M2M algorithm for full modeling of observational data

Made-to-measure (M2M) is a standard technique for modeling the dynamics of astrophysical systems in which the system is modeled with a set of N particles with weights that are slowly optimized to fit a set of constraints while integrating these particles forward in the gravitational potential. Simple-m2m extends this standard technique to allow parameters of the system other than the particle weights to be fit as well, including nuisance parameters that describe the observer's relation to the dynamical system (e.g., the inclination) or parameters describing an external potential.

[ascl:2305.016] gw_pta_emulator: Gravitational Waves via Pulsar Timing Arrays

The gw_pta_emulator reads in gravitational wave (GW) characteristic strain spectra from black-hole population simulations, re-bins for the user's observing baseline, and constructs new spectra. The user can train a Gaussian process to emulate the spectral behavior at all frequencies across the astrophysical parameter space of supermassive black-hole binary environments.

[ascl:2305.015] EIDOS: Modeling primary beams of radio astronomy antennas

EIDOS models the primary beam of radio astronomy antennas. The code can be used to create MeerKAT L-band beams from both holographic (AH) observations and EM simulations within a maximum diameter of 10 degrees. The beam model is less accurate at higher frequencies, and performs much better below 1400 MHz. The diagonal terms of the model beam Jones matrix are much better known than the off-diagonal terms. The performance of EIDOS is dependent on the quality of the given AH and EM datasets; as more accurate AH models and EM simulations become available, this pipeline can be used to create more accurate sparse representation of primary beams using Zernike polynomials.

[ascl:2305.014] DP3: Streaming processing pipeline for radio interferometric data

DP3 (the Default Preprocessing Pipeline) is the LOFAR data pipeline processing program and is the successor to DPPP (ascl:1804.003). It performs many kinds of operations on the data in a pipelined way so the data are read and written only once. DP3 preprocesses the data of a LOFAR observation by executing steps such as flagging or averaging. Such steps can be used for the raw data as well as the calibrated data by defining the data column to use. One or more of the following steps can be defined as a pipeline. DP3 has an implicit input and output step. It is also possible to have intermediate output steps. DP3 comes with predefined steps, but also allows the user to plug in arbitrary steps implemented in either C++ or Python.

[ascl:2305.013] aartfaac2ms: Aartfaac datasets converter

aartfaac2ms converts raw Aartfaac correlator files to the casacore (ascl:1912.002) measurement set format. It phase rotates the data to a common phase center, and (optionally) flags, averages, and compresses the data. The code includes a tool, afedit, to splice a raw Aartfaac set based on LST.

[ascl:2305.012] KERN: Radio telescope toolkit

KERN contains most of the standard tools needed to work with radio telescope data. The suite saves time and reduces frustration in setting up of scientific pipelines, and also improves scientific reproducibility. It includes a wide variety of packages, including 21cmfast (ascl:1102.023), BRATS (ascl:1806.025), CARTA (ascl:2103.031), casacore (ascl:1912.002), CubiCal (ascl:1805.031), DDFacet (ascl:2305.008), PyBDSF (ascl:1502.007),TiRiFiC (ascl:1208.008), WSClean (ascl:1408.023), and many others. KERN can be run on a supported platform such as Ubuntu, with Docker and Singularity, or in a virtual machine.

[ascl:2305.011] DarkMappy: Mapping the dark universe

DarkMappy reconstructs maximum a posteriori (MAP) convergence maps by formulating an unconstrained Bayesian inference problem in order to implement hybrid Bayesian dark-matter reconstruction techniques on the plane and on the celestial sphere. These convergence maps support principled uncertainty quantification and provide hypothesis testing of structure, from which it is possible to distinguish between physical objects and artifacts of the reconstruction.

[ascl:2305.010] FLAGLET: Fast and exact wavelet transform on the ball

FLAGLET computes flaglet transforms with arbitrary spin direction, probing the angular features of this generic wavelet transform for rapid analysis of signals from wavelet coefficients. The code enables the decomposition of a band-limited signal into a set of flaglet maps that capture all information contained in the initial band-limited map, and it can reconstruct the individual flaglets at varying resolutions. FLAGLET relies upon the SSHT (ascl:2207.034), S2LET (ascl:1211.001), and SO3 codes to provide angular transforms and sampling theorems, as well as the FFTW (ascl:1201.015) code to compute Fourier transforms.

[ascl:2305.009] breizorro: Image masking tool

Given a FITS image, breizorro creates a binary mask. The software allows the user control various parameters and functions, such as setting a sigma threshold for masking, merging in or subtracting one or more masks or region files, filling holes, applying dilation within a defined radius of pixels, and inverting the mask.

[ascl:2305.008] DDFacet: Facet-based radio imaging package

DDFacet provides a wideband wide-field spectral imaging and deconvolution framework that accounts for generic direction-dependent effects (DDEs). It implements a wide-field coplanar faceting scheme and uses nontrivial facet-dependent w-kernels to correct for noncoplanarity within the facets. In the imaging and deconvolution steps, DDFacet can handle generic, spatially discrete, time-frequency-baseline-direction-dependent full polarization Jones matrices, and computes a direction dependent PSF for use in the minor cycle of deconvolution for time-frequency-baseline dependent Mueller matrices. The code also allows for the effects of time and bandwidth averaging to be explicitly incorporated into deconvolution. DDFacet has been successfully tested with data diverse telescopes such as LOFAR, VLA, MeerKAT AR1, and ATCA.

[ascl:2305.007] Stimela: Containerized radio interferometry scripting framework

stimela provides a system-agnostic scripting framework for simulating, processing, and imaging radio interferometric data. The framework executes radio interferometry related tasks such as imaging, calibration, and data synthesis in Docker containers using Python modules. stimela offers a simple interface to packages that perform these tasks rather than doing any data processing, synthesis or analysis itself. stimela only requires Docker and Python. Moreover, because of Docker, a stimela script runs the same way (in the same iso­lated environment) regardless of the host machine’s settings, thus providing a user-friendly and modular scripting environment that gives general users easy access to novel radio interferometry calibration, imaging, and synthesis packages.

[ascl:2305.006] QuartiCal: Fast radio interferometric calibration

QuartiCal is the successor to CubiCal (ascl:1805.031). It implements a suite of fast radio interferometric calibration routines exploiting complex optimization. Unlike CubiCal, QuartiCal allows for any available Jones terms to be combined. It can also be deployed on a cluster.

[ascl:2305.005] killMS: Direction-dependent radio interferometric calibration package

killMS implements two very efficient algorithms for solving the Direction-Dependent calibration problem (also known as third generation calibration). This problem naturally arises in the Radio Interferometry Measurement Equation (RIME), but only became overwhelmingly problematic with the construction of the SKA precursors and pathfinders. Solving for the DDE calibration problem basically consists in inverting a number of non-linear equations, while the system is very large and often subject to ill conditioning. The two algorithms killMS uses are based on complex optimization techniques and exploit algorithmic shortcuts; killMS also runs an extended Kalman filter.

[ascl:2305.004] katdal: MeerKAT Data Access Library

katdal interacts with the chunk stores and HDF5 files produced by the MeerKAT radio telescope and its predecessors (KAT-7 and Fringe Finder), which are collectively known as MeerKAT Visibility Format (MVF) data sets. The library uses memory carefully, allowing data sets to be inspected and partially loaded into memory. Data sets may be concatenated and split via a flexible selection mechanism. In addition, katdal provides a script to convert these data sets to CASA MeasurementSets.

[ascl:2305.003] extrapops: Fast simulation and analysis of extra-galactic binary GW sources

extrapops simulates extra-galactic populations of gravitational waves sources and models their emission during the inspiral phase. The code approximately assesses the detectability of individual sources by LISA and computes the background due to unresolved sources in the LISA band using different methods. The simulated populations can be saved in a format compatible with LISA LDC. Simulations are well calibrated to produce accurate background calculations and fair random generation at the tails of the distributions, which is important for accurate probability of detectable events. extrapops uses a number of ad-hoc techniques for rapid simulation and allows room for further optimization up to almost 1 order of magnitude.

[ascl:2305.002] Virtual Telescope: Next-Generation Space Telescope Simulator

Virtual Telescope predicts the signal-to-noise and other parameters of imaging and/or spectroscopic observations as a function of telescope size, detector noise, and other factors for the Next-Generation Space Telescope.

[ascl:2305.001] FRIDDA: Fisher foRecast code for combIned reDshift Drift and Alpha

FRIDDA forecasts the cosmological impact of measurements of the redshift drift and the fine-structure constant (alpha) as well as their combination. The code is based on Fisher Matrix Analysis techniques and works for various fiducial cosmological models. Though designed for the ArmazoNes high Dispersion Echelle Spectrograph (ANDES), it is easily adaptable to other fiducial cosmological models and to other instruments with similar scientific goals.

[ascl:2304.006] JET: JWST Exoplanet Targeting

JET (JWST Exoplanet Targeting) optimizes lists of exoplanet targets for atmospheric characterization by the James Webb Space Telescope (JWST). The software uses catalogs of planet detections, either simulated, or actual and categorizes targets by radius and equilibrium temperature; it also estimates planet masses and generates model spectra and simulated instrument spectra. JET then performs a statistical analysis to determine if the instrument spectra can confirm an atmospheric detection and finally ranks the targets within each category by observation time required for detection.

[ascl:2304.005] FALCO: Fast Linearized Coronagraph Optimizer in Python

FALCO (Fast Linearized Coronagraph Optimizer) performs coronagraphic focal plane wavefront correction. It includes routines for pair-wise probing estimation of the complex electric field and Electric Field Conjugation (EFC) control. FALCO utilizes and builds upon PROPER (ascl:1405.006) and rapidly computes the linearized response matrix for each DM, which facilitates re-linearization after each control step for faster DM-integrated coronagraph design and wavefront correction experiments. A MATLAB implementation of FALCO (ascl:2304.004) is also available.

[ascl:2304.004] FALCO: Fast Linearized Coronagraph Optimizer in MATLAB

FALCO (Fast Linearized Coronagraph Optimizer) performs coronagraphic focal plane wavefront correction. It includes routines for pair-wise probing estimation of the complex electric field and Electric Field Conjugation (EFC) control. FALCO utilizes and builds upon PROPER (ascl:1405.006) and rapidly computes the linearized response matrix for each DM, which facilitates re-linearization after each control step for faster DM-integrated coronagraph design and wavefront correction experiments. A Python 3 implementation of FALCO (ascl:2304.005) is also available.

[ascl:2304.003] BatAnalysis: HEASOFT wrapper for processing Swift-BAT data

BatAnalysis processes and analyzes Swift Burst Alert Telescope (BAT) survey data in a comprehensive computational pipeline. The code downloads BAT survey data, batch processes the survey observations, and extracts light curves and spectra for each survey observation for a given source. BatAnalysis allows for the use of BAT survey data in advanced analyses of astrophysical sources including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. BatAnalysis can also create mosaicked images at different time bins and extract light curves and spectra from the mosaicked images for a given source.

[ascl:2304.002] Applefy: Robust detection limits for high-contrast imaging

Applefy calculates detection limits for exoplanet high contrast imaging (HCI) datasets. The package provides features and functionalities to improve the accuracy and robustness of contrast curve calculations. Applefy implements the classical approach based on the t-test, as well as the parametric boostrap test for non-Gaussian residual noise. Applefy enables the comparison of imaging results across instruments with different noise characteristics.

[ascl:2304.001] ASSIST: Solar system test particles trajectories integrator

ASSIST integrates test particle trajectories in the field of the Sun, Moon, planets, and massive asteroids, with the positions of the masses obtained from the JPL DE441 ephemeris and its associated asteroid perturber file. Using REBOUND's (ascl:1110.016) IAS15 integrator, ASSIST incorporates the most significant gravitational harmonics and general relativistic corrections and accounts for position- and velocity-dependent non-gravitational effects. The first-order variational equations are included for all terms to support orbit fitting and covariance mapping.

[ascl:2303.020] HaloGraphNet: Predict halo masses from simulations

HaloGraphNet predicts halo masses from simulations using Graph Neural Networks. Given a dark matter halo and its galaxies, this software creates a graph with information about the 3D position, stellar mass and other properties. It then trains a Graph Neural Network to predict the mass of the host halo. Data are taken from the CAMELS hydrodynamic simulations.

[ascl:2303.019] pulsar_spectra: Pulsar flux density measurements, spectral models fitting, and catalog

pulsar_spectra provides a pulsar flux density catalog and automated spectral fitting software for finding spectral models. The package can also produce publication-quality plots and allows users to add new spectral measurements to the catalog. The spectral fitting software uses robust statistical methods to determine the best-fitting model for individual pulsar spectra.

[ascl:2303.018] MORPHOFIT: Morphological analysis of galaxies

MORPHOFIT consists of a series of modules for estimating galaxy structural parameters. The package uses SEXTRACTOR (ascl:1010.064) in forced photometry mode to get an initial estimate of the galaxy structural parameters and create a multiband catalog. It also uses GALFIT (ascl:1010.064), running it on galaxy stamps and galaxy regions from the parent image and also on galaxies from the full image using SEXTRACTOR properties as input. MORPHOFIT has been optimized and tested in both low-density and crowded environments, and can recover the input structural parameters of galaxies with good accuracy.

[ascl:2303.017] bajes: Bayesian Jenaer software

bajes [baɪɛs] provides a user-friendly interface for setting up a Bayesian analysis for an arbitrary model, and is specialized for the analysis of gravitational-wave and multi-messenger transients. The code runs a parameter estimation job, inferring the properties of the input model. bajes is designed to be simple-to-use and light-weighted with minimal dependencies on external libraries. The user can set up a pipeline for parameters estimation of multi-messenger transients by writing a configuration file containing the information to be passed to the executables. The package also includes tools and methods for data analysis of multi-messenger signals. The pipeline incorporates an interface with reduced-order-quadratude (ROQ) interpolants. In particular, the ROQ pipeline relies on the output provided by PyROQ-refactored.

[ascl:2303.016] SatGen: Semi-analytical satellite galaxy and dark matter halo generator

SatGen generates satellite-galaxy populations for host halos of desired mass and redshift. It combines halo merger trees, empirical relations for galaxy-halo connection, and analytic prescriptions for tidal effects, dynamical friction, and ram-pressure stripping. It emulates zoom-in cosmological hydrosimulations in certain ways and outperforms simulations regarding statistical power and numerical resolution.

[ascl:2303.015] SIDM: Density profiles of self-interacting dark-matter halos with inhabitant galaxies

The SIDM model combines the isothermal Jeans model and the model of adiabatic halo contraction into a simple semi-analytic procedure for computing the density profile of self-interacting dark-matter (SIDM) haloes with the gravitational influence from the inhabitant galaxies. It agrees well with cosmological SIDM simulations over the entire core-forming stage and up to the onset of gravothermal core-collapse. The fast speed of the method facilitates analyses that would be challenging for numerical simulations.

[ascl:2303.014] Delphes: Fast simulation of a generic collider experiment

Delphes simulates a fast multipurpose detector response. The simulation includes a tracking system, embedded into a magnetic field, calorimeters and a muon system. The Delphes framework is interfaced to standard file formats (e.g. Les Houches Event File or HepMC) and outputs observables such as isolated leptons, missing transverse energy and collection of jets that can be used for dedicated analyses. The simulation of the detector response takes into account the effect of magnetic field, the granularity of the calorimeters and sub-detector resolutions. Visualization of the final state particles is also built-in using the corresponding ROOT library.

[ascl:2303.013] FastJet: Jet finding in pp and e+e− collisions

The FastJet package provides fast native implementations of many sequential recombination algorithms, including the longitudinally invariant kt longitudinally invariant inclusive Cambridge/Aachen and anti-kt jet finders. It also provides a uniform interface to external jet finders via a plugin mechanism. FastJet also includes tools for calculating jet areas and performing background (pileup/UE) subtraction and for jet substructure analyses.

[ascl:2303.012] EvoEMD: Cosmic Evolution with an Early Matter-Dominated era

EvoEMD evaluates cosmic evolution with or without an early matter dominated (EMD) era. The framework includes global parameter, particle, and process systems, and different methods for Hubble parameter calculation. EvoEMD automatically builds up the Boltzmann equation according to the user's definition of particle and process,solves the Boltzmann equation using 4th order Runge-Kutta method with adaptive steps tailored to cosmology application, and caches the collision rate calculation results for fast evaluation.

[ascl:2303.011] Scri: Manipulate time-dependent functions of spin-weighted spherical harmonics

Scri manipulates time-dependent functions of spin-weighted spherical harmonics. It implements the BMS transformations of the most common gravitational waveforms, including the Newman-Penrose quantity ψ4, the Bondi news function, the shear spin coefficient σ, and the transverse-traceless metric perturbation h, as well as the remaining Newman-Penrose quantities ψ0 through ψ3.

[ascl:2303.010] spinsfast: Fast and exact spin-s spherical harmonic transforms

spinsfast is a fast spin-s spherical harmonic transform algorithm, which is flexible and exact for band-limited functions. It permits the computation of several distinct spin transforms simultaneously. Specifically, only one set of special functions is computed for transforms of quantities with any spin, namely the Wigner d matrices evaluated at π/2, which may be computed with efficient recursions. For any spin, the computation scales as O(L^3), where L is the band limit of the function.

[ascl:2303.009] Pandora: Fast exomoon transit detection algorithm

Pandora searches for exomoons by employing an analytical photodynamical model that includes stellar limb darkening, full and partial planet-moon eclipses, and barycentric motion of planet and moon. The code can be used with nested samplers such as UltraNest (ascl:1611.001) or dynesty (ascl:1809.013). Pandora is fast, calculating 10,000 models and log-likelihood evaluation per second (give or take an order of magnitude, depending on parameters and data); this means that a retrieval with 250 Mio. evaluations until convergence takes about 5 hours on a single core. For searches in large amounts of data, it is most efficient to assign one core per light curve.

[ascl:2303.008] nd-redshift: Number Density Redshift Evolution Code

Comparing galaxies across redshifts via cumulative number densities is a popular way to estimate the evolution of specific galaxy populations. nd-redshift uses abundance matching in the ΛCDM paradigm to estimate the median change in number density with redshift. It also provides estimates for the 1σ range of number densities corresponding to galaxy progenitors and descendants.

[ascl:2303.007] PyCom: Interstellar communication

PyCom provides function calls for deriving the optimal communication scheme to maximize the data rate between a remote probe and home-base. It includes models for the loss of photons from diffraction, technological limitations, interstellar extinction and atmospheric transmission, and manages major atmospheric, zodiacal, stellar and instrumental noise sources. It also includes scripts for creating figures appearing in the referenced paper.

[ascl:2303.006] GPCC: Gaussian process cross-correlation for time delay estimation

Gaussian Process Cross-Correlation (GPCC) uses Gaussian processes to estimate time delays for reverberation mapping (RM) of Active Galactic Nuclei (AGN). This statistically principled model delivers a posterior distribution for the delay and accounts for observational noise and the non-uniform sampling of the light curves. Written in Julia, GPCC quantifies the uncertainty and propagates it to subsequent calculations of dependent physical quantities, such as black hole masses. The code delivers out-of-sample predictions, which enables model selection, and can calculate the joint posterior delay for more than two light curves. Though written for RM, the software can also be applied to other fields where cross-correlation analysis is performed.

[ascl:2303.005] Blobby3D: Bayesian inference for gas kinematics

Blobby3D performs Bayesian inference for gas kinematics on emission line observations of galaxies using Integral Field Spectroscopy. The code robustly infers gas kinematics for regularly rotating galaxies even if the gas profiles have significant substructure. Blobby3D also infers gas kinematic properties free from the effects of beam smearing (where beam smearing is the effect of the observational seeing spatially blurring the gas profiles), which has significant effects on the observed gas kinematic properties, particularly the observed velocity dispersion.

[ascl:2303.004] naif: Frequency analysis package

naif extracts frequencies and respective amplitudes from time-series, such as that of an orbital coordinate. Based on the Numerical Analysis of Fundamental Frequencies (NAFF) algorithm and written in Python, naif offers some improvements, particularly in computation time. It also offers functions to plot the power-spectrum before extraction of each frequency, which can be useful for debugging particular orbits.

[ascl:2303.003] SeeKAT: Localizer for transients detected in tied-array beams

SeeKAT is a Python implementation of a novel maximum-likelihood estimation approach to localizing transients and pulsars detected in multiple MeerKAT tied-array beams at once to (sub-)arcsecond precision. It reads in list of detections (RA, Dec, S/N) and the beam PSF and computes a covariance matrix of the S/N value ratios, assuming 1-sigma Gaussian errors on each measurement. It models the aggregate beam response by arranging beam PSFs appropriately relative to each other and calculates a likelihood distribution of obtaining the observed S/N in each beam according to the modeled response. In addition, SeeKAT can plot the likelihood function over RA and Dec with 1-sigma uncertainty, overlaid on the beam coordinates and sizes.

[ascl:2303.002] line_selections: Automatic line detection for large spectroscopic surveys

The Python code line_selections reads synthetic "full" spectra and elemental spectra, automatically identifies the detectable lines at a given resolution (provided the linelist used to compute the spectra), and returns a table containing various properties of the lines (e.g., purity, central wavelength, and depth). The code then stores the information in a pandas DataFrame. line_selections demonstrates where chemical information is present in a stellar spectrum, and allows the user to optimize observational strategies, such as choosing resolution and spectra windows, as well as analysis codes with the application of high-quality masks.

[submitted] World Observatory

World Observatory visualizes S/N-versus-cost tradeoffs for large optical and near-infrared telescopes. Both mid-latitude and Arctic/Antarctic sites can be considered; the intent is a simple simulation to grow intuition for where major capital costs lie relative to key observatory design choices, and against expected scientific performance at various sites. User-defined unit costs for (a possibly "effective") roadway, enclosure, aperture, focal length, and adaptive optics can be scaled up for polar sites, and down for better seeing and lower sky brightness in K-band. Observatory models and results are immediately displayed side-by-side. Either point-source-detection S/N or recovery of bulge-to-total ratios in a simulated galaxy survey are divided by the total project cost, thus providing a universal metric.

[ascl:2303.001] cysgp4: Wrapper for C++ SGP4 satellite library

The cysgp4 Cython-powered package wraps the C++ SGP4 Library for computing satellite positions from two-line elements (TLE). It provides similar functionality as the sgp4 Python package, though also works well with arrays of TLEs and/or observing times and makes use of multi-core platforms (via OpenMP) to improve processing times.

[ascl:2302.026] HDMSpectra: Dark Matter Spectra from the electroweak to the Planck scale

HDMSpectra computes the decay spectrum for dark matter with masses above the scale of electroweak symmetry breaking, down to Planck scale and including all relevant electroweak interactions. The code determines the distribution of stable states for photons, neutrinos, positrons, and antiprotons.

[ascl:2302.025] Diffmah: Differentiable models of halo and galaxy formation history

Diffmah approximates the growth of individual halos as a simple power-law function of time, where the power-law index smoothly decreases as the halo transitions from the fast-accretion regime at early times to the slow-accretion regime at late times. The code has a typical accuracy of 0.1 dex for times greater than one billion years in halos of mass greater than 10e11 M_sun. Diffmah self-consistently captures the mean and variance of halo mass accretion rates across long time scales, and it generates Monte Carlo simulations of cosmologically-representative and differentiable halo histories.

[ascl:2302.024] DSPS: Differentiable Stellar Population Synthesis

DSPS synthesizes stellar populations, leading to fully-differentiable predictions for galaxy photometry and spectroscopy. The code implements an empirical model for stellar metallicity, and it also supports the Diffstar (ascl:2302.012) model of star formation and dark matter halo history. DSPS rapidly generates and simulates galaxy-halo histories on both CPU and GPU hardware.

[ascl:2302.023] AART: Adaptive Analytical Ray Tracing

AART (Adaptive Analytical Ray Tracing) exploits the integrability properties of the Kerr spacetime to compute high-resolution black hole images and their visibility amplitude on long interferometric baselines. It implements a non-uniform adaptive grid on the image plane suitable to study black hole photon rings (narrow ring-shaped features, predicted by general relativity but not yet observed). The code implements all the relevant equations required to compute the appearance of equatorial sources on the (far) observer's screen.

[ascl:2302.022] RALF: RADEX Line Fitter

The RADEX Line Fitter provides a Python 3 interface that calls RADEX (ascl:1010.075) to make a non-LTE fit to a set of observed lines and derive the column density of the molecule that produced the lines and optionally also the molecular hydrogen (H2) number density or the kinetic temperature of the molecule. This code requires RADEX to be installed locally.

[ascl:2302.021] AMICAL: Aperture Masking Interferometry Calibration and Analysis Library

AMICAL (Aperture Masking Interferometry Calibration and Analysis Library) processes Aperture Masking Interferometry (AMI) data from major existing facilities, such as NIRISS on the JWST, SPHERE and VISIR from the European Very Large Telescope (VLT) and VAMPIRES from SUBARU telescope. The library cleans the reduced datacube from the standard instrument pipelines, extracts the interferometrical quantities (visibilities and closure phases) using a Fourier sampling approach, and calibrates those quantities to remove the instrumental biases. In addition, two external packages (CANDID and Pymask) are included to analyze the final outputs obtained from a binary-like sources (star-star or star-planet); these stand-alone packages are interfaced with AMICAL to quickly estimate scientific results (e.g., separation, position angle, contrast ratio, and contrast limits) using different approaches.

[ascl:2302.020] UBER: Universal Boltzmann Equation Solver

UBER (Universal Boltzmann Equation Solver) solves the general form of Fokker-Planck equation and Boltzmann equation, diffusive or non-diffusive, that appear in modeling planetary radiation belts. Users can freely specify the coordinate system, boundary geometry and boundary conditions, and the equation terms and coefficients. The solver works for problems in one to three spatial dimensions. The solver is based upon the mathematical theory of stochastic differential equations. By its nature, the solver scheme is intrinsically Monte Carlo, and the solutions thus contain stochastic uncertainty, though the user may dictate an arbitrarily small relative tolerance of the stochastic uncertainty at the cost of longer Monte Carlo iterations.

[ascl:2302.019] MADCUBA: MAdrid Data CUBe Analysis

MADCUBA analyzes astronomical datacubes and multiple spectra from various astronomical facilities, including ALMA, Herschel, VLA, IRAM 30m, APEX, GBT, and others. These telescopes, and in particular ALMA, generate extremely large datacubes (spatial, spectral and polarization). This software combines a user-friendly interface and powerful data analysis system to derive the physical conditions of molecular gas, its chemical complexity and the kinematics from datacubes. Built using the ImageJ (ascl:1206.013) infrastructure, MADCUBA visualizes astronomical datacubes with thousands on spectral channels, and datasets with thousands of spectra; it also identifies molecular species using publicly available molecular catalogs. It can automatically derive the physical parameters of the molecular species: column density, excitation temperature, velocity and linewidths and provides the best non-linear least-squared fit using the Levenberg-Marquardt algorithm, among other tasks.

[ascl:2302.018] GCP: Automated GILDAS-CLASS Pipeline

This library of scripts provides a simple interface for running the CLASS software from GILDAS (ascl:1305.010) in a semi-automatic way. Using these scripts, one can extract and organize spectra from data files in CLASS format (for example, .30m and .40m), reduce them, and even combine or average them once they are reduced. The library contains five Python scripts and two optional Julia scripts.

[ascl:2302.017] RichValues: Managing numeric values with uncertainties and upper/lower limits

RichValues transforms numeric values with uncertainties and upper/lower limits to create "rich values" that can be written in plain text documents in an easily readable format and used to propagate uncertainties automatically. Rich values can also be exported in the same formatting style as the import. The RichValues library uses a specific formatting style to represent the different kinds of rich values with plain text; it can also be used to create rich values within a script. Individual rich values can be used in, for example, tuples, lists, and dictionaries, and also in arrays and tables.

[ascl:2302.016] swyft: Scientific simulation-based inference at scale

swyft implements Truncated Marginal Neural Radio Estimation (TMNRE), a Bayesian parameter inference technique for complex simulation data. The code improves performance by estimating low-dimensional marginal posteriors rather than the joint posteriors of distributions, while also targeting simulations to targets of observational interest via an indicator function. The use of local amortization permits statistical checks, enabling validation of parameters that cannot be performed using sampling-based methods. swyft is also based on stochastic simulations, mapping parameters to observational data, and incorporates a simulator manager.

[ascl:2302.015] FCFC: C toolkit for computing correlation functions from pair counts

FCFC (Fast Correlation Function Calculator) computes correlation functions from pair counts. It supports the isotropic 2-point correlation function, anisotropic 2PCF, 2-D 2PCF, and 2PCF Legendre multipoles, among others. Written in C, FCFC takes advantage of three parallelisms that can be used simultaneously, distributed-memory processes via Message Passing Interface (MPI), shared-memory threads via Open Multi-Processing (OpenMP), and single instruction, multiple data (SIMD).

[ascl:2302.014] kima: Exoplanet detection in RVs with DNest4 and GPs

kima fits Keplerian curves to a set of RV measurements, using the Diffusive Nested Sampling (ascl:1010.029) algorithm to sample the posterior distribution for the model parameters. Additionally, the code can calculate the fully marginalized likelihood of a model with a given number of Keplerians and also infer the number of Keplerian signals detected in a given dataset. kima implements dedicated models for different analyses of a given dataset. The models share a common organization, but each has its own parameters (and thus priors) and settings.

[ascl:2302.013] SASHIMI-C: Semi-Analytical SubHalo Inference ModelIng for Cold Dark Matter

SASHIMI-C calculates various subhalo properties efficiently using semi-analytical models for cold dark matter (CDM), providing a full catalog of dark matter subhalos in a host halo with arbitrary mass and redshift. Each subhalo is characterized by its mass and density profile both at accretion and at the redshift of interest, accretion redshift, and effective number (or weight) corresponding to that particular subhalo. SASHIMI-C computes the subhalo mass function without making any assumptions such as power-law functional forms; the only assumed power law is that for the primordial power spectrum predicted by inflation. The code is not limited to numerical resolution nor to Poisson shot noise, and its results are well in agreement with those from numerical N-body simulations.

[ascl:2302.012] Diffstar: Differentiable star formation histories

Diffstar fits the star formation history (SFH) of galaxies to a smooth parametric model. Diffstar differs from existing SFH models because the parameterization of the model is directly based on basic features of galaxy formation physics, including halo mass assembly history, accretion of gas into the dark matter halo, the fraction of gas that is converted into stars, the time scale over which star formation occurs, and the possibility of rejuvenated star formation. The SFHs of a large number of simulated galaxies can be fit in parallel using mpi4py.

[ascl:2302.011] UniverseMachine: Empirical model for galaxy formation

The UniverseMachine applies simple empirical models of galaxy formation to dark matter halo merger trees. For each model, it generates an entire mock universe, which it then observes in the same way as the real Universe to calculate a likelihood function. It includes an advanced MCMC algorithm to explore the allowed parameter space of empirical models that are consistent with observations.

[ascl:2302.010] SASHIMI-W: Semi-Analytical SubHalo Inference ModelIng for Warm Dark Matter

SASHIMI-W calculates various subhalo properties efficiently using semi-analytical models for warm dark matter (WDM); the code is based on the extended Press-Schechter formalism and subhalos' tidal evolution prescription. The calculated constraints are independent of physics of galaxy formation and free from numerical resolution and the Poisson noise, and its results are well in agreement with those from numerical N-body simulations.

[ascl:2302.009] EXOTIC: EXOplanet Transit Interpretation Code

EXOTIC (EXOplanet Transit Interpretation Code) analyzes photometric data of transiting exoplanets into lightcurves and retrieves transit epochs and planetary radii. The software reduces images of a transiting exoplanet into a lightcurve, and fits a model to the data to extract planetary information crucial to increasing the efficiency of larger observational platforms. EXOTIC is written in Python and supports the citizen science project Exoplanet Watch. The software runs on Windows, Macintosh, and Linux/Unix computer, and can also be used via Google Colab.

[ascl:2302.008] HawkingNet: Finding Hawking points in the Cosmic Microwave Background

HawkingNet searches for Hawking points in large Cosmic Microwave Background (CMB) data sets. It is based on the deep residual network ResNet18 and consists of eighteen neural layers. Written in Paython, HawkingNet inputs the CMB data, processes the data through its internal network trained for data classification, and outputs the result in a form of a classification score that indicates how confident it is that a Hawking point is contained in the image patch.

[ascl:2302.007] AnalyticLC: Dynamical modeling of planetary systems

AnalyticLC generates an analytic light-curve, and optionally RV and astrometry data, from a set of initial (free) orbital elements and simultaneously fits these data. Written in MATLAB, the code is fast and efficient, and provides insight into the motion of the orbital elements, which is difficult to obtain from numerical integration. A Python wrapper for AnalyticLC is available separately.

[ascl:2302.006] RCR: Robust Chauvenet Outlier Rejection

RCR provides advanced outlier rejection that is easy to use. Both sigma clipping, the simplest form of outlier rejection, and traditional Chauvenet rejection make use of non-robust quantities, the mean and standard deviation, which are sensitive to the outliers that they are being used to reject. This limits such techniques to samples with small contaminants or small contamination fractions. RCR instead first makes use of robust replacements for the mean, such as the median and the half-sample mode, and similar robust replacements for the standard deviation. RCR has been carefully calibrated and can be applied to samples with both large contaminants and large contaminant fractions (sometimes in excess of 90% contaminated).

[ascl:2302.005] celmech: Sandbox for celestial mechanics calculations

celmech provides a variety of analytical and semianalytical tools for celestial mechanics and dynamical astronomy. The package interfaces closely with the REBOUND N-body integrator (ascl:1110.016), thus facilitating comparisons between calculation results and direct N-body integrations. celmech can isolate the contribution of particular resonances to a system's dynamical evolution, and can develop simple analytical models with the minimum number of terms required to capture a particular dynamical phenomenon.

[ascl:2302.004] SFQEDtoolkit: Strong-field QED processes modeling for PIC and Monte Carlo codes

SFQEDtoolkit implements strong-field QED (SFQED) processes in existing particle-in-cell (PIC) and Monte Carlo codes to determine the dynamics of particles and plasmas in extreme electromagnetic fields, such as those present in the vicinity of compact astrophysical objects. The code uses advanced function approximation techniques to calculate high-energy photon emission and electron-positron pair creation probability rates and energy distributions within the locally-constant-field approximation (LCFA) as well as with more advanced models.

[ascl:2302.003] PHOTOe: Monte Carlo model for simulating the slowing down of photoelectrons

PHOTOe simulates the slowing down of photoelectrons in a gas with arbitrary amounts of H, He and O atoms, and thermal electrons, making PHOTOe useful for investigating the atmospheres of exoplanets. The multi-score scheme used in this code differs from other Monte Carlo approaches in that it efficiently handles rare collisional channels, as in the case of low-abundance excited atoms that undergo superelastic and inelastic collisions. PHOTOe outputs include production and energy yields, steady-state photoelectron flux, and estimates of the 'relaxation' time required by the photoelectrons to slow down from the injection energy to the cutoff energy. The model can also estimate the pathlength travelled by the photoelectrons while relaxing.

[ascl:2302.002] deconfuser: Fast orbit fitting to directly imaged multi-planetary systems

Deconfuser performs fast orbit fitting to directly imaged multi-planetary systems. It quickly fits orbits to planet detections in 2D images and ensures that all orbits within a certain tolerance are found. The code also tests all groupings of detections by planets (which detection belongs to which planet), and ranks partitions of detections by planets by deciding which assignment of detection-to-planet best fits the data.

[ascl:2302.001] nicaea: NumerIcal Cosmology And lEnsing cAlculations

nicaea calculates cosmology and weak-lensing quantities and functions from theoretical models of the large-scale structure. Written in C, it can compute the Hubble parameter, distances, and geometry for background cosmology, and linear perturbations, including growth factor, transfer function, cluster mass function, and linear 3D power spectra. It also calculates fitting formulae for non-linear power spectra, emulators, and halo model for Non-linear evolution, and the HOD model for galaxy clustering. In addition, nicaea can compute quantities for cosmic shear such as the convergence power spectrum, second-order correlation functions and derived second-order quantities, and third-order aperture mass moment; it can also calculate CMB anisotropies via CAMB (ascl:1102.026).

[submitted] PREVIS: Python Request Engine for Virtual Interferometric Survey

PREVIS is a Python module that provides functions to help determine the observability of astronomical sources from long-baseline interferometers worldwide: VLTI (ESO, Chile) and CHARA (USA). PREVIS uses data from the Virtual Observatory (OV), such as magnitudes, Spectral Energy Distribution (SED), celestial coordinates or Gaia distances. Then, it compares the target brightness to the limiting magnitudes of each instrument to determine whether the target is observable with present performances. PREVIS includes main facilities at the VLTI with PIONIER (H band), GRAVITY (K band) and MATISSE (L, M, N bands), and at CHARA array with VEGA (V band), PAVO (R bands), MIRC (H band), CLIMB (K band) and CLASSIC (H, K bands). PREVIS also uses the V or G magnitudes to check the guiding restriction or the tip/tilt correction limit. For the VLTI: if the star is too faint in G mag, PREVIS will look for the list of stars around the target (57 arcsec) with the appropriate magnitude and give the list of celestial coordinates usable as the guiding star.

[ascl:2301.030] HIPP: HIgh-Performance Package for scientific computation

HIPP (HIgh-Performance Package for scientific computation) provides elegant interfaces for some well-known HPC libraries. Some libraries are wrapped with full-OOP interfaces, and many new extensions based on those raw-interfaces are also provided. This C++ toolkit for HPC can significantly reduce the length of your code, making programming more productive.

[ascl:2301.029] ALMA3: plAnetary Love nuMbers cAlculator

ALMA3 computes loading and tidal Love numbers for a spherically symmetric, radially stratified planet. Both real (time-domain) and complex (frequency-domain) Love numbers can be computed. The planetary structure can include an arbitrary number of layers, and each layer can have a different rheological law. ALMA3 can model numerous linear rheologies, including Elastic, Maxwell visco-elastic, Newtonian viscous fluid, Kelvin-Voigt solid, Burgers and Andrade transient rheologies.

[ascl:2301.028] special: SPEctral Characterization of directly ImAged Low-mass companions

special (SPEctral Characterization of directly ImAged Low-mass companions) characterizes low-mass (M, L, T) dwarfs down to giant planets at optical/IR wavelengths. It can also be used more generally to characterize any type of object with a measured spectrum, provided a relevant input model grid, regardless of the observational method used to obtain the spectrum (direct imaging or not) and regardless of the format of the spectra (multi-band photometry, low-resolution or medium-resolution spectrum, or a combination thereof). It analyzes measured spectra, calculating the spectral correlation between channels of an IFS datacube and empirical spectral indices for MLT-dwarfs. It fits input spectra to either photo-/atmospheric model grids or a blackbody model, including additional parameters such as (extra) black body component(s), extinction and total-to-selective extinction ratio, and can use emcee (ascl:1303.002), nestle (ascl:2103.022), or UltraNest (ascl:1611.001) samplers infer posterior distributions on spectral model parameters in a Bayesian framework, among other tasks.

[ascl:2301.027] Puri-Psi: Radio interferometric imaging

Puri-Psi addresses radio interferometric imaging problems using state-of-the-art optimization algorithms and deep learning. It performs scalable monochromatic, wide-band, and polarized imaging. It also provide joint calibration and imaging, and scalable uncertainty quantification. A scalable framework for wide-field monochromatic intensity imaging is also available, which encompasses a pure optimization algorithm, as well as an AI-based method in the form of a plug-and-play algorithm propelled by Deep Neural Network denoisers.

[ascl:2301.026] MGwave: Detect kinematic moving groups in astronomical data

The 2-D wavelet transformation code MGwave detects kinematic moving groups in astronomical data; it can also investigate underdensities which can eventually provide further information about the MW's non-axisymmetric features. The code creates a histogram of the input data, then performs the wavelet transformation at the specified scales, returning the wavelet coefficients across the entire histogram in addition to information about the detected extrema. MGwave can also run Monte Carlo simulations to propagate uncertainties. It runs the wavelet transformation on simulated data (pulled from Gaussian distributions) many times and tracks the percentage of the simulations in which a given extrema is detected. This quantifies whether a detected overdensity or underdensity is robust to variations of the data within the provided errors.

[ascl:2301.025] desitarget: Selecting DESI targets from photometric catalogs

desitarget selects targets for spectroscopic follow-up by Dark Energy Spectroscopic Instrument (DESI). The pipeline uses bitmasks to record that a specific source has been selected by a particular targeting algorithm, setting bit-values in output data files in a number of different columns that indicate whether a particular target meets specific selection criteria. desitarget also outputs a unique TARGETID that allows each target to be tracked throughout the DESI survey. This TARGETID encodes information about each DESI target, such as the catalog the target was selected from, whether a target is a sky location or part of a random catalog, and whether a target is part of a secondary program.

[submitted] nFITSview: A simple and user-friendly FITS image viewer

nFITSview is a simple, user-friendly and open-source FITS image viewer available for Linux and Windows. One of the main concepts of nFITSview is to provide an intuitive user interface which may be helpful both for scientists and for amateur astronomers. nFITSview has different color mapping and manipulation schemes, supports different formats of FITS data files as well as exporting them to different popular image formats. It also supports command-line exporting (with some restrictions) of FITS files to other image formats.
The application is written in C++/Qt for achieving better performance, and with every next version the performance aspect is taken into account.
nFITSview uses its own libnfits library (can be used separately as well) for parsing the FITS files.

[ascl:2301.024] SOXS: Simulated Observations of X-ray Sources

SOXS creates simulated X-ray observations of astrophysical sources. The package provides a comprehensive set of tools to design source models and convolve them with simulated models of X-ray observatories. In particular, SOXS is the primary simulation tool for simulations of Lynx and Line Emission Mapper observations. SOXS provides facilities for creating spectral models, simple spatial models for sources, astrophysical background and foreground models, as well as a Python implementation of the SIMPUT file format.

[ascl:2301.023] PoWR: Potsdam Wolf-Rayet Models

PoWR (Potsdam Wolf-Rayet Models) calculates synthetic spectra for Wolf-Rayet and OB stars from model atmospheres which account for Non-LTE, spherical expansion and metal line blanketing. The model data is provided through a web interface and includes Spectral Energy Distribution, line spectrum in high resolution for different wavelength bands, and atmosphere stratification. For Wolf-Rayet stars of the nitrogen subclass, there are grids of hydrogen-free models and of models with a specified mass fraction of hydrogen. The iron-group and total CNO mass fractions correspond to the metallicity of the Galaxy, the Large Magellanic Cloud, or the Small Magellanic Cloud, respectively. The source code is available as a tarball on the same web interface.

[ascl:2301.022] GalCEM: GALactic Chemical Evolution Model

GalCEM (GALactic Chemical Evolution Model) tracks isotope masses as a function of time in a given galaxy. The list of tracked isotopes automatically adapts to the complete set provided by the input yields. The prescription includes massive stars, low-to-intermediate mass stars, and Type Ia supernovae as enrichment channels. Multi-dimensional interpolation curves are extracted from the input yield tables with a preprocessing tool; these interpolation curves improve the computation speeds of the full convolution integrals, which are computed for each isotope and for each enrichment channel. GalCEM also provides tools to track the mass rate change of individual isotopes on a typical spiral galaxy with a final baryonic mass of 5×1010M⊙.

[ascl:2301.021] WALDO: Waveform AnomaLy DetectOr

WALDO (Waveform AnomaLy DetectOr) flags possible anomalous Gravitational Waves from Numerical Relativity catalogs using deep learning. It uses a U-Net architecture to learn the waveform features of a dataset. After computing the mismatch between those waveforms and the neural predictions, WALDO isolates high mismatch evaluations for anomaly search.

[ascl:2301.020] VDA: Void Dwarf Analyzer

void-dwarf-analysis analyzes Keck Cosmic Web Imager datacubes to produce maps of kinematic properties (velocity and velocity dispersion), emission line fluxes, and gas-phase metallicities of void dwarf galaxies.

[ascl:2301.019] KCWI_DRP: Keck Cosmic Web Imager Data Reduction Pipeline in Python

KCWI_DRP, written in Python and based on kderp (ascl:2301.018), is the official DRP for the Keck Cosmic Web Imager at the W. M. Keck Observatory. It provides all of the functionality of the older pipeline and has three execution modes: multi-threading for CPU intensive tasks such as wavelength calibration, and multi-processing for large datasets. It offers vacuum to air and heliocentric or barycentric correction and the ability to use KOA file names or original file names. KCWI_DRP also improves the provenance and traceability of DRP versions and execution steps in the headers over kderp, and has versatile sky subtraction modes including using external sky frames and ability of masking regions.

[ascl:2301.018] kderp: Keck Cosmic Web Imager Data Extraction and Reduction Pipeline in IDL

kderp (KCWI Data Extraction and Reduction Pipeline) reduces data for the Keck Cosmic Web Imager. Written in IDL, it performs basic CCD reduction on raw images to produce bias and overscan subtracted, gain-corrected, trimmed and cosmic ray removed images; it can also subtract the sky. It defines the geometric transformations required to map each pixel in the 2d image into slice, postion, and wavelength, and performs flat field and illumination corrections. It generates cubes, applying the transformations previously solved to the object intensity, variance and mask images output from any of the previous stages, and uses a standard star observation to generate an inverse sensitivity curve which is applied to the corresponding observations to flux calibrate them.

This pipeline has been superseded by KCWI_DRP (ascl:2301.019).

[ascl:2301.017] ReACT: Calculation of non-linear power spectra from non-standard physics

ReACT extends the Copter (ascl:1304.022) and MG-Copter packages, which calculate redshift and real space large scale structure observables for a wide class of gravity and dark energy models. Additions to Copter include spherical collapse in modified gravity, halo model power spectrum for general theories, and real and redshift space LSS 2 point statistics for modified gravity and dark energy. ReACT also includes numerical perturbation theory kernel solvers, real space bispectra in modified gravity, and a numerical perturbation theory kernel solver up to 4th order for 1-loop bispectrum.

[ascl:2301.016] FERRE: Match physical models to measurements

FERRE matches physical models to observed data, taking a set of observations and identifying the model parameters that best reproduce the data, in a chi-squared sense. It solves the common problem of having numerical parametric models that are costly to evaluate and need to be used to interpret large data sets. FERRE provides flexibility to search for all model parameters, or hold constant some of them while searching for others. The code is written to be truly N-dimensional and fast. Model predictions are to be given as an array whose values are a function of the model parameters, i.e., numerically. FERRE holds this array in memory, or in a direct-access binary file, and interpolates in it. The code returns, in addition to the optimal set of parameters, their error covariance, and the corresponding model prediction. The code is written in FORTRAN90.

[ascl:2301.015] SOAP-GPU: Spectral time series simulations with GPU

SOAP-GPU is a revision of SOAP 2 (ascl:1504.021), which simulates spectral time series with the effect of active regions (spot, faculae or both). In addition to the traditional outputs of SOAP 2.0 (the cross-correlation function and extracted parameters: radial velocity, bisector span, full width at half maximum), SOAP-GPU generates the integrated spectra at each phase for given input spectra and spectral resolution. Additional capabilities include fast spectral simulation of stellar activity due to GPU acceleration, simulation of more complicated active region structures with superposition between active regions, and more realistic line bisectors, based on solar observations, that varies as function of mu angle for both quiet and active regions. In addition, SOAP-GPU accepts any input high resolution observed spectra. The PHOENIX synthetic spectral library are already implemented at the code level which allows users to simulate stellar activity for stars other than the Sun. Furthermore, SOAP-GPU simulates realistic spectral time series with either spot number/SDO image as additional inputs. The code is written in C and provides python scripts for input pre-processing and output post-processing.

[ascl:2301.014] LBL: Line-by-line velocity measurements

LBL derives velocity measurements from high-resolution (R>50 000) datasets by accounting for outliers in the spectra data. It is tailored for fiber-fed multi-order spectrographs, both in optical and near-infrared (up to 2.5µm) domains. The domain is split into individual units (lines) and the velocity and its associated uncertainty are measured within each line and combined through a mixture model to allow for the presence of spurious values. In addition to the velocity, other quantities are also derived, the most important being a value (dW) that can be understood (for a Gaussian line) as a change in the line FWHM. These values provide useful stellar activity indicators. LBL works on data from a variety of instruments, including SPIRou, NIRPS, HARPS, and ESPRESSO. The code's output is an rdb table that can be uploaded to the online DACE pRV analysis tool.

[ascl:2301.013] pyExoRaMa: An interactive tool to investigate the radius-mass diagram for exoplanets

pyExoRaMa visualizes and manipulates data related to exoplanets and their host stars in a multi-dimensional parameter space. It enables statistical studies based on the large and constantly increasing number of detected exoplanets, identifies possible interdependence among several physical parameters, and compares observables with theoretical models describing the exoplanet composition and structure.

[ascl:2301.012] XGA: Efficient analysis of XMM observations

XGA (X-ray: Generate and Analyse) analyzes X-ray sources observed by the XMM-Newton Space telescope. It is based around declaring different types of source and sample objects which correspond to real X-ray sources, finding all available data, and then insulating the user from the tedious generation and basic analysis of X-ray data products. XGA generates photometric products and spectra for individual sources, or whole samples, with just a few lines of code. Though not a pipeline, pipelines for complex analysis can be built on top of it. XGA provides an easy to use (and parallelized) Python interface with XMM's Science Analysis System (ascl:1404.004), as well as with XSPEC (ascl:9910.005). All XMM products and fit results are read into an XGA source storage structure, thus avoiding the need to leave a Python environment at any point during the analysis. This module also supports more complex analyses for specific object types such as the easy generation of scaling relations, the measurement of gas masses for galaxy clusters, and the PSF correction of images.

[ascl:2301.011] Rosetta: Platform for resource-intensive, interactive data analysis

Rosetta runs tasks for resource-intensive, interactive data analysis as software containers. The code's architecture frames user tasks as microservices – independent and self-contained units – which fully support custom and user-defined software packages, libraries and environments. These include complete remote desktop and GUI applications, common analysis environments such as the Jupyter Notebooks. Rosetta relies on Open Container Initiative containers, allowing for safe, effective and reproducible code execution. It can use a number of container engines and runtimes and seamlessly supports several workload management systems, thus enabling containerized workloads on a wide range of computing resources.

[ascl:2301.010] Fastcc: Broadband radio telescope receiver fast color corrections

Fastcc returns color corrections for different spectra for various Cosmic Microwave Background experiments. Available in both Python and IDL, the script is easy to use when analyzing radio spectra of sources with data from multiple wide-survey CMB experiments in a consistent way across multiple experiments.

[ascl:2301.009] Xpol: Pseudo-Cl power spectrum estimator

Xpol computes angular power spectra based on cross-correlation between maps and covariance matrices. The code is written in C and is fully MPI parallelized in CPU and memory using spherical transform by s2hat (ascl:1110.013). It has been used to derive CMB and dust power spectra for Archeops and CMB, dust, CIB, SZ, SZ-CIB for Planck, among others.

[ascl:2301.008] HiLLiPoP: High-L Likelihood Polarized for Planck

HiLLiPoP is a multifrequency CMB likelihood for Planck data. The likelihood is a spectrum-based Gaussian approximation for cross-correlation spectra from Planck 100, 143 and 217GHz split-frequency maps, with semi-analytic estimates of the Cl covariance matrix based on the data. The cross-spectra are debiased from the effects of the mask and the beam leakage using Xpol (ascl:2301.009) before being compared to the model, which includes CMB and foreground residuals. They cover the multipoles from ℓ=30 to ℓ=2500. HiLLiPoP is interfaced with the Cobaya (ascl:1910.019) MCMC sampler.

[ascl:2301.007] LoLLiPoP: Low-L Likelihood Polarized for Planck

LoLLiPoP is a Planck low-l polarization likelihood based on cross-power-spectra for which the bias is zero when the noise is uncorrelated between maps. It uses a modified approximation to apply to cross-power spectra and is interfaced with the Cobaya (ascl:1910.019) MCMC sampler. Cross-spectra are computed on the CMB maps from Commander component separation applied on each detset-split Planck frequency maps.

[ascl:2301.006] Self-cal: Optical/IR long-baseline interferometry

Self-cal produces radio-interferometric images of an astrophysical object. The code is an adaptation of the self-calibration algorithm to optical/infrared long-baseline interferometry, especially to make use of differential phases and differential visibilities. It works together with the Mira image reconstruction software and has been used mainly on VLTI data. Self-cal, written in Yorick, is also available as part of fitsOmatic (ascl:2301.005).

[ascl:2301.005] fitOmatic: Interferometric data modeling

The fitOmatic model-fitting prototyping tool tests multi-wavelength model-fitting and exploits VLTI data. It provides tools to define simple geometrical models and conveniently adjust the model's parameters. Written in Yorick, it takes optical interferometry FITS (oifits) files as input and allows the user to define a model of the source from a set of pre-defined models, which can be combined to make more complicated models. fitOmatic then computes the Fourier Transform of the modeled brightness distribution and synthetic observables are computed at the wavelengths and projected baselines of the observations. fitomatic's strength is its ability to define vector-parameters, i.e., parameters that may depend on wavelength and/or time. The self-cal (ascl:2301.006) component of fitOmatic is also available as a separate code.

[ascl:2301.004] HEADSS: HiErArchical Data Splitting and Stitching for non-distributed clustering algorithms

HEADSS (HiErArchical Data Splitting and Stitching) facilitates clustering at scale, unlike clustering algorithms that scale poorly with increased data volume or that are intrinsically non-distributed. HEADSS automates data splitting and stitching, allowing repeatable handling, and removal, of edge effects. Implemented in conjunction with scikit's HDBSCAN, the code achieves orders of magnitude reduction in single node memory requirements for both non-distributed and distributed implementations, with the latter offering similar order of magnitude reductions in total run times while recovering analogous accuracy. HEADSS also establishes a hierarchy of features by using a subset of clustering features to split the data.

[ascl:2301.003] WF4Py: Gravitational waves waveform models in pure Python language

WF4Py implements frequency-domain gravitational wave waveform models in pure Python, thus enabling parallelization over multiple events at a time. Waveforms in WF4Py are built as classes; the functions take dictionaries containing the parameters of the events to analyze as input and provide Fourier domain waveform models. All the waveforms are accurately checked with their implementation in LALSuite (ascl:2012.021) and are a core element of GWFAST (ascl:2212.001).

[ascl:2301.002] Pyxel: Detector and end-to-end instrument simulation

Pyxel hosts and pipelines models (analytical, numerical, statistical) simulating different types of detector effects on images produced by Charge-Coupled Devices (CCD), Monolithic, and Hybrid CMOS imaging sensors. Users can provide one or more input images to Pyxel, set the detector and model parameters, and select which effects to simulate, such as cosmic rays, detector Point Spread Function (PSF), electronic noises, Charge Transfer Inefficiency (CTI), persistence, dark current, and charge diffusion, among others. The output is one or more images including the simulated detector effects combined. The Pyxel framework, written in Python, provides basic image analysis tools, an input image generator, and a parametric mode to perform parametric and sensitivity analysis. It also offers a model calibration mode to find optimal values of its parameters based on a target dataset the model should reproduce.

[ascl:2301.001] CALSAGOS: Select cluster members and search, find, and identify substructures

CALSAGOS (Clustering ALgorithmS Applied to Galaxies in Overdense Systems) selects cluster members and searches, finds, and identifies substructures and galaxy groups in and around galaxy clusters using the redshift and position in the sky of the galaxies. The package offers two ways to determine cluster members, ISOMER and CLUMBERI. The ISOMER (Identifier of SpectrOscopic MembERs) function selects the spectroscopic cluster members by defining cluster members as those galaxies with a peculiar velocity lower than the escape velocity of the cluster. The CLUMBERI (CLUster MemBER Identifier) function select the cluster members using a 3D-Gaussian Mixture Modules (GMM). Both functions remove the field interlopers by using a 3-sigma clipping algorithm. CALSAGOS uses the function LAGASU (LAbeller of GAlaxies within SUbstructures) to search, find, and identify substructures and groups in and around a galaxy cluster; this function is based on clustering algorithms (GMM and DBSCAN), which search areas with high density to define a substructure or groups.

[submitted] unWISE-verse: An Integrated WiseView and Zooniverse Data Pipeline

unWISE-verse is an integrated Python pipeline for downloading sets of unWISE time-resolved coadd cutouts from the WiseView image service and uploading subjects to Zooniverse.org for use in astronomical citizen science research. This software was initially designed for the Backyard Worlds: Cool Neighbors research project and is optimized for target sets containing low luminosity brown dwarf candidates. However, unWISE-verse can be applied to other future astronomical research projects that seek to make use of unWISE infrared sky maps, such as studies of infrared variable/transient sources.

[ascl:2212.026] Spender: Neural spectrum encoder and decoder

Spender establishes a restframe for galaxy spectra that has higher resolution and larger wavelength range than the spectra from which it is trained. The model can be trained from spectra at different redshifts or even from different instruments without the need to standardize the observations. Spender also has an explicit, differentiable redshift dependence, which can be coupled with a redshift estimator for a fully data-driven spectrum analysis pipeline. The code describes the restframe spectrum by an autoencoder and transforms the restframe model to the observed redshift; it also matches the spectral resolution and line spread function of the instrument.

[ascl:2212.025] CONTROL: Colorado Ultraviolet Transit Experiment data reduction pipeline

CONTROL (CUTE autONomous daTa ReductiOn pipeLine) produces science-quality output with a single command line with zero user interference for CUTE (Colorado Ultraviolet Transit Experiment) data. It can be used for any single order spectral data in any wavelength without any modification. The pipeline is governed by a parameter file, which is available with this distribution. CONTROL is fully automated and works in a series of steps following standard CCD reduction techniques. It creates a reduction log to track processes carried out and any parameters used.

[ascl:2212.024] Burning Arrow: Black hole massive particles orbit degradation

Burning Arrow determines the destabilization of massive particle circular orbits due to thermal radiation, emitted in X-ray, from the hot accretion disk material. This code requires the radiation forces exerted on the material at the point of interest found by running the code Infinity (ascl:2212.021). Burning Arrow begins by assuming a target particle in the disk that moves in a circular orbit. It then introduces the recorded radiation forces from Infinity code for the target region. The forces are subsequently introduced into the target particle equations of motion and the trajectory is recalculated. Burning Arrow then produces images of the black hole - accretion disk system that includes the degenerated particle trajectories that obey the assorted velocity profiles.

[ascl:2212.023] Tranquillity: Creating black hole spin divergence plots

Tranquillity creates an observing screen looking toward a black hole - accretion disk system, seeks the object, then searches and locates its contour. Subsequently, it attempts to locate the first Einstein "echo" ring and its location. Finally, it collates the retrieved information and draws conclusions; these include the accretion disk level inclination compared to the line of sight and the main disk and the first echo median. The displacement, and thus the divergence of the latter two, is the required information in order to construct the divergence plots. Other programs can later on automatically read these plots and provide estimations of the central black hole spin.

[ascl:2212.022] Elysium: Observing black hole accretion disks

Elysium creates an observing screen at the desirable distance away from a black hole system. Observers set on every pixel of this screen then photograph the area toward the black hole - accretion disk system and report back what they record. This can be the accretion disk (incoming photons bring in radiation and thus energy), the black hole event horizon, or the empty space outside and beyond the system (there are no incoming photons or energy). The central black hole can be either Schwarzschild (nonrotating) or Kerr (rotating) by choice of the user.

[ascl:2212.021] Infinity: Calculate accretion disk radiation forces onto moving particles

Infinity sets an observer in a black hole - accretion disk system. The black hole can be either Schwarzschild (nonrotating) or Kerr (rotating) by choice of the user. This observer can be on the surface of the disk, in its exterior or its interior (if the disk is not opaque). Infinity then scans the entire sky around the observer and investigates whether photons emitted by the hot accretion disk material can reach them. After recording the incoming radiation, the program calculates the stress-energy tensor of the radiation. Afterwards, the program calculates the radiation flux and hence, the radiation force exerted on target particles of various velocity profiles.

[ascl:2212.020] Omega: Photon equations of motion

Omega solves the photon equations of motion in the environment surrounding a black hole. This black hole can be either Schwarzschild (nonrotating) or Kerr (rotating) by choice of the user. The software offers numerous options, such as the geometrical setup of the accretion disk around the black hole (including no disk, band, slab, wedge, among others, the spin parameter of the central black hole, and the thickness of the accretion disk. Other options that can be set includ the azimuthal angle of the photon emission/reception, the poloidal angle of the photon emission/reception, and how far away or close to the system to look.

[ascl:2212.019] m2mcluster: Star clusters made-to-measure modeling

m2mcluster performs made-to-measure modeling of star clusters, and can fit target observations of a Galactic globular cluster's 3D density profile and individual kinematic properties, including proper motion velocity dispersion, and line of sight velocity dispersion. The code uses AMUSE (ascl:1107.007) to model the gravitational N-body evolution of the system between time steps; GalPy (ascl:1411.008) is also required.

[ascl:2212.018] SourceXtractor++: Extracts sources from astronomical images

SourceXtractor++ extracts a catalog of sources from astronomical images; it is the successor to SExtractor (ascl:1010.064). SourceXtractor++ has been completely rewritten in C++ and improves over its predecessor in many ways. It provides support for multiple “measurement” images, has an optimized multi-object, multi-frame model-fitting engine, and can define complex priors and dependencies for model parameters. It also offers efficient image data caching and multi-threaded processing, and has a modular design with support for third-party plug-ins.

[ascl:2212.017] powspec: Power and cross spectral density of 2D arrays

powspec provides functions to compute power and cross spectral density of 2D arrays. Units are properly taken into account. It can, for example, create fake Gaussian field images, compute power spectra P(k) of each image, shrink a mask with regard to a kernel, generate a Gaussian field, and plot various results.

[ascl:2212.016] AbundanceMatching: Subhalo abundance matching with scatter

The AbundanceMatching Python module creates (interpolates and extrapolates) abundance functions and also provides fiducial deconvolution and abundance matching.

[ascl:2212.015] SImMER: Stellar Image Maturation via Efficient Reduction

SImMER (Stellar Image Maturation via Efficient Reduction) reduces astronomical imaging data. It performs standard dark-subtraction and flat-fielding operations on data from, for example, the ShARCS camera on the Shane 3-m telescope at Lick Observatory and the PHARO camera on the Hale 5.1-m telescope at Palomar Observatory; its object-oriented design allows the software to be extended to other instruments. SImMER can also perform sky-subtraction, image registration, FWHM measurement, and contrast curve calculation, and can generate tables and plots. For widely separated stars which are of somewhat equal brightness, a “wide binary” mode allows the user to selects which star is the primary around which each image should be centered.

[ascl:2212.014] pyTANSPEC: Python tool for extracting 1D TANSPEC spectra from 2D images

pyTANSPEC extracts XD-mode spectra automatically from data collected by the TIFR-ARIES Near Infrared Spectrometer (TANSPEC) on India's ground-based 3.6-m Devasthal Optical Telescope at Nainital, India. The TANSPEC offers three modes of observations, imaging with various filters, spectroscopy in the low-resolution prism mode with derived R~ 100-400 and the high-resolution cross-dispersed mode (XD-mode) with derived median R~ 2750 for a slit of width 0.5 arcsec. In the XD-mode, ten cross-dispersed orders are packed in the 2048 x 2048 pixels detector to cover the full wavelength regime. The XD-mode is most utilized; pyTANSPEC provides a dedicated pipeline for consistent data reduction for all orders and to reduces data reduction time. The code requires nominal human intervention only for the quality assurance of the reduced data. Two customized configuration files are used to guide the data reduction. The pipeline creates a log file for all the fits files in a given data directory from its header, identifies correct frames (science, continuum and calibration lamps) based on the user input, and offers an option to the user for eyeballing and accepting/removing of the frames, does the cleaning of raw science frames and yields final wavelength calibrated spectra of all orders simultaneously.

[ascl:2212.013] PACMAN: Planetary Atmosphere, Crust, and MANtle geochemical evolution

PACMAN (Planetary Atmosphere, Crust, and MANtle geochemical evolution) runs a coupled redox-geochemical-climate evolution model. It runs Monte Carlo calculations over nominal parameter ranges, including number of iterations and number of cores for parallelization, which can be altered to reproduce different scenarios and sensitivity tests. Model outputs and corresponding input parameters are saved in separate files which are used to plot results; the the user can choose which outputs to plot, including all successful outputs, nominal Earth outputs, waterworld false positives, desertworld false positives, and high CO2:H2O false positives. Among other functions, PACMAN contains functions for interpolating the pre-computed Outgoing Longwave Radiation (OLR) grid, the atmosphere-ocean partitioning grid, and the stratospheric water vapor grid, calculating bond albedo and outgassing fluxes.

[ascl:2212.012] BANZAI-NRES: BANZAI data reduction pipeline for NRES

The BANZAI-NRES pipeline processes data from the Network of Robotic Echelle Spectrographs (NRES) on the Las Cumbres Observatory network and provides extracted, wavelength calibrated spectra. If the target is a star, it provides stellar classification parameters (e.g., effective temperature and surface gravity) and a radial velocity measurement. The automated radial velocity measurements from this pipeline have a precision of ~ 10 m/s for high signal-to-noise observations. The data flow and infrastructure of this code relies heavily on BANZAI (ascl:2207.031), enabling BANZAI-NRES to focus on analysis that is specific to spectrographs. The wavelength calibration is primarily done using xwavecal (ascl:2212.011). The pipeline propagates an estimate of the formal uncertainties from all of the data processing stages and includes these in the output data products. These are used as weights in the cross correlation function to measure the radial velocity.

[ascl:2212.011] xwavecal: Wavelength calibrating echelle spectrographs

The xwavecal library automatically wavelength calibrates echelle spectrographs for high precision radial velocity work. The routines are designed to operate on data with extracted 1D spectra. The library provides a convienience function which returns a list of wavelengths from just a list of spectral feature coordinates (pixel and order) and a reference line list. The returned wavelengths are the wavelengths of the measured spectral features under the best fit wavelength model. xwavecal also provides line identification and spectral reduction utilities. The library is modular; each step of the wavelength calibration is a stage which can be disabled by removing the associated line in the config.ini file. Wavelength calibrating data which already have spectra means only using the wavelength calibration stages. Using the full experimental pipeline means enabling the other data reduction stages, such as overscan subtraction.

[ascl:2212.010] sf_deconvolve: PSF deconvolution and analysis

sf_deconvolve performs PSF deconvolution using a low-rank approximation and sparsity. It can handle a fixed PSF for the entire field or a stack of PSFs for each galaxy position. The code accepts Numpy binary files or FITS as input, takes the observed (i.e. with PSF effects and noise) stack of galaxy images and a known PSF, and attempts to reconstruct the original images. sf_deconvolve can be run in a terminal or in an active Python session, and includes options for initialization, optimization, low-Rank approximation, sparsity, PSF estimation, and other attributes.

[ascl:2212.009] Hazma: Compute indirect detection constraints on sub-GeV dark matter

Hazma enables indirect detection of sub-GeV dark matter. It computes gamma-ray and electron/positron spectra from dark matter annihilations, sets limits on sub-GeV dark matter using existing gamma-ray data, and determines the discovery reach of future gamma-ray detectors. The code also derives accurate CMB constraints. Hazma comes with several sub-GeV dark matter models, for which it provides functions to compute dark matter annihilation cross sections and mediator decay widths. A variety of low-level tools are provided to make it straightforward to define new models.

[ascl:2212.008] panco2: Pressure profile measurements of galaxy clusters

panco2 extracts measurements of the pressure profile of the hot gas inside galaxy clusters from millimeter-wave observations. The extraction is performed using forward modeling the millimeter-wave signal of clusters and MCMC sampling of a posterior distribution for the parameters given the input data. Many characteristic features of millimeter-wave observations can be taken into account, such as filtering (both through PSF smearing and transfer functions), point source contamination, and correlated noise.

[ascl:2212.007] PyMCCF: Python Modernized Cross Correlation Function for reverberation mapping studies

PyMCCF (Python Modernized Cross Correlation Function), also known as MCCF, cross correlates two light curves that are unevenly sampled using linear interpolation and measures the peak and centroid of the cross-correlation function. Based on PyCCF (ascl:1805.032) and ICCF, it introduces a new parameter, MAX, to reduce the number of interpolated points used to just those which are not farther from the nearest real one than the MAX. This significantly reduces noise from interpolation errors. The estimation of the errors in PyMCCF is exactly the same as in PyCCF.

[ascl:2212.006] GPry: Bayesian inference of expensive likelihoods with Gaussian processes

GPry efficiently obtains marginal quantities from computationally expensive likelihoods. It works best with smooth (continuous) likelihoods and posteriors that are slow to converge by other methods, which is dependent on the number of dimensions and expected shape of the posterior distribution. The likelihood should be low-dimensional (d<20 as a rule of thumb), though the code may still provide considerable improvements in speed in higher dimensions, despite an increase in the computational overhead of the algorithm. GPry is an alternative to samplers such as MCMC and Nested Sampling with a goal of speeding up inference in cosmology, though the software will work with any likelihood that can be called as a python function. It uses Cobaya's (ascl:1910.019) model framework so all of Cobaya's inbuilt likelihoods work, too.

[ascl:2212.005] MTNeedlet: Spherical maps filtering

MTNeedlet uses needlets to filter spherical (Healpix) maps and detect and analyze the maxima population using a multiple testing approach. It has been developed with the CMB in mind, but it can be applied to other spherical maps. It pivots around three basic steps: 1.) The calculation of several types of needlets and their possible use to filter maps; 2.) The detection of maxima (or minima) on spherical maps, their visualization and basic analysis; and 3.) The multiple testing approach in order to detect anomalies in the maxima population of the maps with respect to the expected behavior for a random Gaussian map. MTNeedlet relies on Healpy (ascl:2008.022) to efficiently deal with spherical maps.

[ascl:2212.004] FastDF: Integrating neutrino geodesics in linear theory

FastDF (Fast Distribution Function) integrates relativistic particles along geodesics in a comoving periodic volume with forces determined by cosmological linear perturbation theory. Its main application is to set up accurate particle realizations of the linear phase-space distribution of massive relic neutrinos by starting with an analytical solution deep in radiation domination. Such particle realizations are useful for Monte Carlo experiments and provide consistent initial conditions for cosmological N-body simulations. Gravitational forces are calculated from three-dimensional potential grids, which are obtained by convolving random phases with linear transfer functions using Fast Fourier Transforms. The equations of motion are solved using a symplectic leapfrog integration scheme to conserve phase-space density and prevent the build-up of errors. Particles can be exported in different gauges and snapshots are provided in the HDF5 format, compatible with N-body codes like SWIFT (ascl:1805.020) and Gadget-4 (ascl:2204.014). The code has an interface with CLASS (ascl:1106.020) for calculating transfer functions and with monofonIC (ascl:2008.024) for setting up initial conditions with dark matter, baryons, and neutrinos.

[ascl:2212.003] MGCosmoPop: Modified gravity and cosmology with binary black holes population models

MGCosmoPop implements a hierarchical Bayesian inference method for constraining the background cosmological history, in particular the Hubble constant, together with modified gravitational-wave propagation and binary black holes population models (mass, redshift and spin distributions) with gravitational-wave data. It includes support for loading and analyzing data from the GWTC-3 catalog as well as for generating injections to evaluate selection effects, and features a module to run in parallel on clusters.

[ascl:2212.002] Eventdisplay: Analysis and reconstruction package for ground-based Gamma-ray astronomy

Eventdisplay reconstructs and analyzes data from the Imaging Atmospheric Cherenkov Telescopes (IACT). It has been primarily developed for VERITAS and CTA analysis. The package calibrates and parametrizes images, event reconstruction, and stereo analysis, and provides train boosted decision trees for direction and energy reconstruction. It fills and uses lookup tables for mean scaled width and length calculation, energy reconstruction, and stereo reconstruction, and calculates radial camera acceptance from data files and instrument response functions such as effective areas, angular point-spread function, and energy resolution. Eventdisplay offers additional tools as well, including tools for calculating sky maps and spectral energy distribution, and to plot instrument response function, spectral energy distributions, light curves, and sky maps, among others.

[ascl:2212.001] GWFAST: Fisher information matrix python package for gravitational-wave detectors

GWFAST forecasts the signal-to-noise ratios and parameter estimation capabilities of networks of gravitational-wave detectors, based on the Fisher information matrix approximation. It is designed for applications to third-generation gravitational-wave detectors. It is based on Automatic Differentiation, which makes use of the library JAX (ascl:2111.002). This allows efficient parallelization and numerical accuracy. The code includes a module for parallel computation on clusters.

[submitted] SLEPLET

Many fields in science and engineering measure data that inherently live on non-Euclidean geometries, such as the sphere. Techniques developed in the Euclidean setting must be extended to other geometries. Due to recent interest in geometric deep learning, analogues of Euclidean techniques must also handle general manifolds or graphs. Often, data are only observed over partial regions of manifolds, and thus standard whole-manifold techniques may not yield accurate predictions. In this thesis, a new wavelet basis is designed for datasets like these.

Although many definitions of spherical convolutions exist, none fully emulate the Euclidean definition. A novel spherical convolution is developed, designed to tackle the shortcomings of existing methods. The so-called sifting convolution exploits the sifting property of the Dirac delta and follows by the inner product of a function with the translated version of another. This translation operator is analogous to the Euclidean translation in harmonic space and exhibits some useful properties. In particular, the sifting convolution supports directional kernels; has an output that remains on the sphere; and is efficient to compute. The convolution is entirely generic and thus may be used with any set of basis functions. An application of the sifting convolution with a topographic map of the Earth demonstrates that it supports directional kernels to perform anisotropic filtering.

Slepian wavelets are built upon the eigenfunctions of the Slepian concentration problem of the manifold - a set of bandlimited functions which are maximally concentrated within a given region. Wavelets are constructed through a tiling of the Slepian harmonic line by leveraging the existing scale-discretised framework. A straightforward denoising formalism demonstrates a boost in signal-to-noise for both a spherical and general manifold example. Whilst these wavelets were inspired by spherical datasets, like in cosmology, the wavelet construction may be utilised for manifold or graph data.

[ascl:2211.020] EXCEED-DM: EXtended Calculation of Electronic Excitations for Direct detection of Dark Matter

EXCEED-DM (EXtended Calculation of Electronic Excitations for Direct detection of Dark Matter) provides a complete framework for computing DM-electron interaction rates. Given an electronic configuration, EXCEED-DM computes the relevant electronic matrix elements, then particle physics specific rates from these matrix elements. This allows for separation between approximations regarding the electronic state configuration, and the specific calculation being performed.

[ascl:2211.019] APERO: A PipelinE to Reduce Observations

APERO (A PipelinE to Reduce Observations) performs data reduction for the Canada-France-Hawaii Telescope's near-infrared spectropolarimeter SPIRou and offers different recipes or modules for performing specific tasks. APERO can individually run recipes or process a set of files, such as cleaning a data file of detector effects, collecting all dark files and creating a master dark image to use for correction, and creating a bad pixel mask for identifying and dealing with bad pixels. It can extract out flat images to measure the blaze and produced blaze correction and flat correction images, extract dark frames to provide correction for the thermal background after extraction of science or calibration frames, and correct extracted files for leakage coming from a FP (for OBJ_FP files only). It can also take a hot star and calculate telluric transmission, and then use the telluric transmission to calculate principle components (PCA) for correcting input images of atmospheric absorption, among many other tasks.

[ascl:2211.018] ODNet: Asteroid occultation detection convolutional neural network

ODNet uses a convolutional neural network to examine frames of a given observation, using the flux of a targeted star along time, to detect occultations. This is particularly useful to reliably detect asteroid occultations for the Unistellar Network, which consists of 10,000 digital telescopes owned by citizen scientists that is regularly used to record asteroid occultations. ODNet is not costly in term of computing power, opening the possibility for embedding the code on the telescope directly. ODNet's models were developed and trained using TensorFlow version 2.4.

[ascl:2211.017] BiGONLight: Bi-local Geodesic Operators framework for Numerical Light propagation

BiGONLight (Bi-local geodesic operators framework for numerical light propagation) encodes the Bi-local Geodesic Operators formalism (BGO) to study light propagation in the geometric optics regime in General Relativity. The parallel transport equations, the optical tidal matrix, and the geodesic deviation equations for the bilocal operators are expressed in 3+1 form and encoded in BiGONLight as Mathematica functions. The bilocal operators are used to obtain all possible optical observables by combining them with the observer and emitter four-velocities and four-accelerations. The user can choose the position of the source and the observer anywhere along the null geodesic with any four-velocities and four-accelerations.

[ascl:2211.016] Korg: 1D local thermodynamic equilibrium stellar spectral synthesis

Korg computes stellar spectra from 1D model atmospheres and linelists assuming local thermodynamic equilibrium and implements both plane-parallel and spherical radiative transfer. The code is generally faster than other codes, and is compatible with automatic differentiation libraries and easily extensible, making it ideal for statistical inference and parameter estimation applied to large data sets.

[ascl:2211.015] H-FISTA: Phase retrieval for pulsar spectroscopy

H-FISTA (Hierarchical Fast Iterative Shrinkage Thresholding Algorithm) retrieves the phases of the wavefield from intensity measurements for pulsar spectroscopy. The code accepts input data in ASCII format as produced by PSRchive's (ascl:1105.014) psrflux function, a FITS file, or a pickle. If using a notebook, any custom reader can be used as long as the data ends up in a NumPy array. H-FISTA obtains sparse models of the wavefield in a hierarchical approach with progressively increasing depth. Once the tail of the noise distribution is reached, the hierarchy terminates with a final unregularized optimization, resulting in a fully dense model of the complex wavefield that permits the discovery of faint signals by appropriate averaging.

[ascl:2211.014] PDFchem: Average abundance of species from Av-PDFs

PDFchem models the cold ISM at moderate and large scales using functions connecting the quantities of the local and the observed visual extinctions and the local number density with probability density functions. For any given observed visual extinction sampled with thousands of clouds, the algorithm instantly computes the average abundances of the most important species and performs radiative transfer calculations to estimate the average emission of the most commonly observed lines.

[ascl:2211.013] 2DFFTUtils: 2DFFT Utilities implementation

The Python module 2DFFTUtils implements tasks associated with measuring spiral galaxy pitch angle with 2DFFT (ascl:1608.015). Since most of the 2DFFT utilities are implemented in one place, it makes preparing images for 2DFFT and dealing with 2DFFT data interactively or in scripts event easier.

[ascl:2211.012] gsf: Grism SED Fitting package

gsf fits photometric data points, simultaneously with grism spectra if provided, to get posterior probability of galaxy physical properties, such as stellar mass, dust attenuation, metallicity, as well as star formation and metallicity enrichment histories. Designed for extra-galactic science, this flexible, python-based SED fitting code involves a Markov-Chain Monte-Carlo (MCMC) process, and may take more time (depending on the number of parameters and length of MCMC chains) than other SED fitting codes based on chi-square minimization.

[ascl:2211.011] fastSHT: Fast Spherical Harmonic Transforms

fastSHT performs spherical harmonic transforms on a large number of spherical maps. It converts massive SHT operations to a BLAS level 3 problem and uses the highly optimized matrix multiplication toolkit to accelerate the computation. GPU acceleration is supported and can be very effective. The core code is written in Fortran, but a Python wrapper is provided and recommended.

[ascl:2211.010] BlackJAX: Library of samplers for JAX

BlackJAX is a sampling library designed for ease of use, speed, and modularity and works on CPU as well as GPU. It is not a probabilistic programming library (PLL), though it integrates well with PPLs as long as they can provide a (potentially unnormalized) log-probability density function compatible with JAX. BlackJAX is written in pure Python and depends on XLA via JAX (ascl:2111.002). It can be used by those who have a logpdf and need a sampler or need more than a general-purpose sampler. It is also useful for building a sample on GPU and for users who want to learn how sampling algorithms work.

[ascl:2211.009] ovejero: Bayesian neural network inference of strong gravitational lenses

ovejero conducts hierarchical inference of strongly-lensed systems with Bayesian neural networks. It requires lenstronomy (ascl:1804.012) and fastell (ascl:9910.003) to run lens models with elliptical mass distributions. The code trains Bayesian Neural Networks (BNNs) to predict posteriors on strong gravitational lensing images and can integrate with forward modeling tools in lenstronomy to allow comparison between BNN outputs and more traditional methods. ovejero also provides hierarchical inference tools to generate population parameter estimates and unbiased posteriors on independent test sets.

[ascl:2211.008] pmclib: Population Monte Carlo library

The Population Monte-Carlo (PMC) sampling code pmclib performs fast end efficient parallel iterative importance sampling to compute integrals over the posterior including the Bayesian evidence.

[ascl:2211.007] mgcnn: Standard and modified gravity (MG) cosmological models classifier

mgcnn is a Convolutional Neural Network (CNN) architecture for classifying standard and modified gravity (MG) cosmological models based on the weak-lensing convergence maps they produce. It is implemented in Keras using TensorFlow as the backend. The code offers three options for the noise flag, which correspond to noise standard deviations, and additional options for the number of training iterations and epochs. Confusion matrices and evaluation metrics (loss function and validation accuracy) are saved as numpy arrays in the generated output/ directory after each iteration.

[ascl:2211.006] baobab: Training data generator for hierarchically modeling strong lenses with Bayesian neural networks

baobab generates images of strongly-lensed systems, given some configurable prior distributions over the parameters of the lens and light profiles as well as configurable assumptions about the instrument and observation conditions. Wrapped around lenstronomy (ascl:1804.012), baobab supports prior distributions ranging from artificially simple to empirical. A major use case for baobab is the generation of training and test sets for hierarchical inference using Bayesian neural networks (BNNs); the code can generate the training and test sets using different priors.

[ascl:2211.005] unTimely_Catalog_explorer: A search and visualization tool for the unTimely Catalog

unTimely Catalog Explorer searches for and visualizes detections in the unTimely Catalog, a full-sky, time-domain catalog of detections based on WISE and NEOWISE image data acquired between 2010 and 2020. The tool searches the catalog by coordinates to create finder charts for each epoch with overplotted catalog positions and light curves using the unTimely photometry, to overplot these light curves with AllWISE multi-epoch and NEOWISE-R single exposure (L1b) photometry, and to create image blinks with overlaid catalog positions in GIF format.

[ascl:2211.004] PAHDecomp: Decomposing the mid-IR spectra of extremely obscured galaxies

PAHDecomp models mid-infrared spectra of galaxies; it is based on the popular PAHFIT code (ascl:1210.009). In contrast to PAHFIT, this model decomposes the continuum into a star-forming component and an obscured nuclear component based on Bayesian priors on the shape of the star-forming component (using templates + prior on extinction), making this tool ideally suited for modeling the spectra of heavily obscured galaxies. PAHDecomp successfully recovers properties of Compact Obscured Nuclei (CONs) where the inferred nuclear optical depth strongly correlates with the surface brightness of HCN-vib emission in the millimeter. This is currently set up to run on the short low modules of Spitzer IRS data (5.2 - 14.2 microns) but will be ideal for JWST/MIRI MRS data in the future.

[ascl:2211.003] AMBER: Abundance Matching Box for the Epoch of Reionization

AMBER (Abundance Matching Box for the Epoch of Reionization) models the cosmic dawn. The semi-numerical code allows users to directly specify the reionization history through the redshift midpoint, duration, and asymmetry input parameters. The reionization process is further controlled through the minimum halo mass for galaxy formation and the radiation mean free path for radiative transfer. The parallelized code is over four orders of magnitude faster than radiative transfer simulations and will efficiently enable large-volume models, full-sky mock observations, and parameter-space studies.

[ascl:2211.002] KC: Analytical propagator with collision detection for Keplerian systems

The analytic propagator Kepler-Collisions calculates collisions for Keplerian systems. The algorithm maintains a list of collision possibilities and jumps from one collision to the next; since collisions are rare in astronomical scales, jumping from collision to collision and calculating each one is more efficient than calculating all the time steps that are between collisions.

[ascl:2211.001] PTAfast: PTA correlations from stochastic gravitational wave background

PTAfast calculates the overlap reduction function in Pulsar Timing Array produced by the stochastic gravitational wave background for arbitrary polarizations, propagation velocities, and pulsar distances.

[ascl:2210.030] cuvarbase: fast period finding utilities for GPUs

cuvarbase provides a Python library for performing period finding (Lomb-Scargle, Phase Dispersion Minimization, Conditional Entropy, Box-least squares) on astronomical time-series datasets. Speedups over CPU implementations depend on the algorithm, dataset, and GPU capabilities but are typically ~1-2 orders of magnitude and are especially high for BLS and Lomb-Scargle.

[ascl:2210.029] paltas: Simulation-based inference on strong gravitational lensing systems

paltas conducts simulation-based inference on strong gravitational lensing images. It builds on lenstronomy (ascl:1804.012) to create large datasets of strong lensing images with realistic low-mass halos, Hubble Space Telescope (HST) observational effects, and galaxy light from HST's COSMOS field. paltas also includes the capability to easily train neural posterior estimators of the parameters of the lensing system and to run hierarchical inference on test populations.

[ascl:2210.028] CK: Cloud modeling and removal

Cloud Killer recovers surface albedo maps by using reflected light photometry to map the clouds and surface of unresolved exoplanets. For light curves with negligible photometric uncertainties, the minimal top-of-atmosphere albedo at a location is a good estimate of its surface albedo. On synthetic data, it shows little bias, good precision, and accuracy, but slightly underestimated uncertainties; exoplanets with large, changing cloud structures observed near quadrature phases are good candidates for Cloud Killer cloud removal.

[ascl:2210.027] LensingETC: Lensing Exposure Time Calculator

LensingETC optimizes observing strategies for multi-filter imaging campaigns of galaxy-scale strong lensing systems. It uses the lens modelling software lenstronomy (ascl:1804.012) to simulate and model mock imaging data, forecasts the lens model parameter uncertainties, and optimizes observing strategies.

[ascl:2210.026] PGOPHER: Rotational, vibrational, and electronic spectra simulator

PGOPHER simulates and fits rotational, vibrational, and electronic spectra. It handles linear molecules and symmetric and asymmetric tops, including effects due to unpaired electrons and nuclear spin, with a separate mode for vibrational structure. The code performs many sorts of transitions, including Raman, multiphoton, and forbidden transitions. It can simulate multiple species and states simultaneously, including special effects such as perturbations and state dependent predissociation. Fitting can be to line positions, intensities, or band contours. PGOPHER uses a standard graphical user interface and makes comparison with, and fitting to, spectra from various sources easy. In addition to overlaying numerical spectra, it is also possible to overlay pictures from pdf files and even plate spectra to assist in checking that published constants are being used correctly.

[ascl:2210.025] tvguide: Observability by TESS

tvguide determines whether stars and galaxies are observable by TESS. It uses an object's right ascension and declination and estimates the pointing of TESS's cameras using predicted spacecraft ephemerides to determine whether and for how long the object is observable with TESS. tvguide returns a file with two columns, the first the minimum number of sectors the target is observable for and the second the maximum.

[ascl:2210.024] Faiss: Similarity search and clustering of dense vectors library

The Faiss library performs efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU.

[ascl:2210.023] BornRaytrace: Weak gravitational lensing effects simulator

BornRaytrace uses neural data compression of weak lensing map summary statistics to simulate weak gravitational lensing effects. It can raytrace through overdensity Healpix maps to return a convergence map, include shear-kappa transformation on the full sphere, and also include intrinsic alignments (NLA model).

[ascl:2210.022] MCCD: Multi-CCD Point Spread Function Modelling

MCCD (Multi-CCD) generates a Point Spread Function (PSF) model based on stars observations in the field of view. After defining the MCCD model parameters and running and validating the training, the model can recover the PSF at any position in the field of view. Written in Python, MCCD also calculates various statistics and can plot a random test star and its model reconstruction.

[ascl:2210.021] SHEEP: Machine Learning pipeline for astronomy classification

The photometric redshift-aided classification pipeline SHEEP uses ensemble learning to classify astronomical sources into galaxies, quasars and stars. It uses tabular data and also allows the use of sparse data. The approach uses SDSS and WISE photometry, but SHEEP can also be used with other types of tabular data, such as radio fluxes or magnitudes.

[ascl:2210.020] ixpeobssim: Imaging X-ray Polarimetry Explorer simulator and analyzer

The simulation and analysis framework ixpeobssim was specifically developed for the Imaging X-ray Polarimetry Explorer (IXPE). It produces realistic simulated observations, in the form of event lists in FITS format, that also contain a strict superset of the information included in the publicly released IXPE data products. The framework's core simulation capabilities are complemented by post-processing applications that support the spatial, spectral, and temporal models needed for analysis of typical polarized X-ray sources, allowing implementation of complex, polarization-aware analysis pipelines. Where applicable, the data formats are consistent with the common display and analysis tools used by the community, e.g., the binned count spectra can be fed into XSPEC (ascl:9910.005), along with the corresponding response functions, for doing standard spectral analysis. All ixpeobssim simulation and analysis tools are fully configurable via the command line.

[ascl:2210.019] POSYDON: Single and binary star population synthesis code

POSYDON (POpulation SYnthesis with Detailed binary-evolution simulatiONs) incorporates full stellar structure and evolution modeling for single and binary-star population synthesis. The code is modular and allows the user to specify initial population properties and adopt choices that determine how stellar evolution proceeds. Populations are simulated with the use of MESA (ascl:1010.083) evolutionary tracks for single, non-interacting, and interacting binaries organized in grids. Machine-learning methods are incorporated and applied on the grids for classification and various interpolation calculations, and the development of irregular grids guided by active learning, for computational efficiency.

[ascl:2210.018] LavAtmos: Gas-melt equilibrium calculations for a given temperature and melt composition

LavAtmos performs gas-melt equilibrium calculations for a given temperature and melt composition. The thermodynamics of the melt are modeled by the MELTS code as presented in the Thermoengine package (ascl:2208.006). In combination with atmospheric chemistry codes, LavAtmos enables the characterization of interior compositions through atmospheric signatures.

[ascl:2210.017] PySME: Spectroscopy Made Easy reimplemented with Python

PySME is a partial reimplementation of Spectroscopy Made Easy (SME, ascl:1202.013), which fits an observed spectrum of a star with a model spectrum. The IDL routines of SME used to call a dynamically linked library of compiled C++ and Fortran programs have been rewritten in Python. In addition, an object oriented paradigm and continuous integration practices, including build automation, self-testing, and frequent builds, have been added.

[ascl:2210.016] PETSc: Portable, Extensible Toolkit for Scientific Computation

PETSc (Portable, Extensible Toolkit for Scientific Computation) provides a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations, and is intended for use in large-scale application projects. The toolkit includes a large suite of parallel linear, nonlinear equation solvers and ODE integrators that are easily used in application codes written in C, C++, Fortran and Python. PETSc provides many of the mechanisms needed within parallel application codes, such as simple parallel matrix and vector assembly routines that allow the overlap of communication and computation. In addition, PETSc (pronounced PET-see) includes support for managing parallel PDE discretizations.

[ascl:2210.015] Solar-MACH: Multi-spacecraft longitudinal configuration plotter

Solar-MACH (Solar MAgnetic Connection HAUS) derives and visualizes the spatial configuration and solar magnetic connection of different observers (i.e., spacecraft or planets) in the heliosphere at different times. It provides publication-ready figures for analyzing Solar Energetic Particle events (SEPs) or solar transients such as Coronal Mass Ejections (CMEs). Solar-MACH is available as a Python package; a Streamlit-enabled tool that runs in a browser is also available (solar-mach.github.io)

[ascl:2210.014] Blacklight: GR ray tracing code for post-processing Athena++ simulations

Blacklight postprocesses general-relativistic magnetohydrodynamic simulation data and produces outputs for analyzing data sets, including maps of auxiliary quantities and false-color renderings. The code can use Athena++ (ascl:1912.005) outputs directly, and also supports files in HARM (ascl:1209.005) and iHARM3d (ascl:2210.013) format. Written in C++, Blacklight offers support for adaptive mesh refinement input, slow-light calculations, and adaptive ray tracing.

[ascl:2210.013] iharm3D: Hybrid MPI/OpenMP 3D HARM with vectorization

iharm3D implements the HARM algorithm (ascl:1209.005) with modifications and enables a second-order, conservative, shock-capturing scheme for general-relativistic magnetohydrodynamics (GRMHD). Written in C, it simulates black hole accretion systems in arbitrary stationary spacetimes.

[ascl:2210.012] pixmappy: Python interface to gbdes astrometry solutions

pixmappy provides a Python interface to gbdes pixel map (astrometry) solutions. It reads the YAML format astrometry solutions produced by gbdes (ascl:2210.011) and issues a PixelMap instance, which is a map from one 2d coordinate system ("pixel") to another ("world") 2d system. A PixelMap instance can be used as a function mapping one (or many) coordinate pairs. An inverse method does reverse mapping, and the local jacobian of the map is available also. The type of mapping that can be expressed is very flexible, and PixelMaps can be compounded into chains of tranformations.

[ascl:2210.011] gbdes: DECam instrumental signature fitting and processing programs

gbdes derives photometric and astrometric calibration solutions for complex multi-detector astronomical imagers. The package includes routines to filter catalogs down to useful stellar objects, collect metadata from the catalogs and create a config file holding FITS binary tables describing exposures, instruments, fields, and other available information in the data, and uses a friends-of-friends matching algorithm to link together all detections of common objects found in distinct exposures. gbdes also calculates airmasses and parallactic angles for each exposure, calculates and saves the expected differential chromatic refraction (DCR) needed for precision astrometry, optimizes the parameters of a photometric model to maximize agreement between magnitudes measured in different exposures of the same source, and optimizing the parameters of an astrometric model to maximize agreement among the exposures and any reference catalogs, and performs other tasks. The solutions derived and used by gbdes are stored in YAML format; gbdes uses the Python code pixmappy (ascl:2210.012) to read the astrometric solution files and execute specified transformations.

[ascl:2210.010] TSRecon: Time series reconstruction method of massive astronomical catalogs

The time series reconstruction method of massive astronomical catalogs reconstructs all celestial objects' time series data for astronomical catalogs with great accuracy. In addition, the program, which requires a Spark cluster, solves the boundary source leakage problem on the premise of ensuring accuracy, and the user can set different parameters for different data sets to filter the error records in the catalogs.

[ascl:2210.009] NEMESIS: Non-linear optimal estimator for multivariate spectral analysis

NEMESIS (Non-linear optimal Estimator for MultivariatE spectral analySIS) is the general purpose correlated-k/LBL retrieval code developed from the RADTRAN project (ascl:2210.008). Originally based on the correlated-k approximation, NEMESIS also works in line-by-line (LBL) mode. It has been designed to be generally applicable to any planet and with any observing mode and so is suitable for both solar-system studies and also exoplanetary studies.

[ascl:2210.008] RADTRAN: General purpose planetary radiative transfer model

RADTRAN calculates the transmission, absorption or emission spectra emitted by planetary atmospheres using either line-by-line integration, spectral band models, or 'correlated-K' approaches. Part of the NEMESIS project (ascl:2210.009), the code also incorporates both multiple scattering and single scattering calculations. RADTRAN is general purpose and not hard-wired to any specific planet.

[ascl:2210.007] COMET: Emulated predictions of large-scale structure observables

COMET (Clustering Observables Modelled by Emulated perturbation Theory) provides emulated predictions of large-scale structure observables from models that are based on perturbation theory. It substantially speeds up these analytic computations without any relevant sacrifice in accuracy, enabling an extremely efficient exploration of large-scale structure likelihoods. At its core, COMET exploits an evolution mapping approach which gives it a high degree of flexibility and allows it to cover a wide cosmology parameter space at continuous redshifts up to z∼3z \sim 3z∼3. Among others, COMET supports parameters for cold dark matter density (ωc\omega_cωc​), baryon density (ωb\omega_bωb​), Scalar spectral index (nsn_sns​), Hubble expansion rate (hhh) and Curvature density (ΩK\Omega_KΩK​). The code can obtain the real-space galaxy power spectrum at one-loop order multipoles (monopole, quadrupole, hexadecapole) of the redshift-space, power spectrum at one-loop order, the linear matter power spectrum (with and without infrared resummation), Gaussian covariance matrices for the real-space power spectrum, and redshift-space multipoles and χ2\chi^2χ2's for arbitrary combinations of multipoles. COMET provides an easy-to-use interface for all of these computations.

[ascl:2210.006] ExoRad2: Generic point source radiometric model

ExoRad 2.0, a generic point source radiometric model, interfaces with any instrument to provide an estimate of several Payload performance metrics. For each target and for each photometric and spectroscopic channel, the code provides estimates of signals in pixels, saturation times, and read, photon, and dark current noise. ExoRad also provides estimates for the zodiacal background, inner sanctum, and sky foreground.

[ascl:2210.005] PSFr: Point Spread Function reconstruction

PSFr empirically reconstructs an oversampled version of the point spread function (PSF) from astronomical imaging observations. The code provides a light-weighted API of a refined version of an algorithm originally implemented in lenstronomy (ascl:1804.012). It provides user support with different artifacts in the data and supports the masking of pixels, or the treatment of saturation levels. PSFr has been used to reconstruct the PSF from multiply imaged lensed quasar images observed by the Hubble Space Telescope in a crowded lensing environment and more recently with James Webb Space Telescope (JWST) imaging data for a wide dynamical flux range.

[ascl:2210.004] Finder_charts: Create finder charts from image data of various sky surveys

Finder_charts creates multi-band finder charts from image data of various partial- and all-sky surveys such as DSS, 2MASS, WISE, UKIDSS, VHS, Pan-STARRS, and DES. It also creates a WISE time series of image data acquired between 2010 and 2021. All images are reprojected so that north is up and east is to the left. The resulting finder charts can be overplotted with corresponding catalog positions. All catalog entries within the specified field of view can be saved in a variety of formats, including ipac, csv, and tex, as can the finder charts in png, pdf, eps, and other common graphics formats. Finder_charts consists of a single Python module, which depends only on well-known packages, making it easy to install.

[ascl:2210.003] NIRDust: Near Infrared Dust finder for Type2 AGN K-band spectra

NIRDust uses K-band (2.2 micrometers) spectra to measure the temperature of the dust heated by an Active Galactic Nuclei (AGN) accretion disk. The package provides several functionalities to pre-process spectra and fit the hot dust component of a AGN K-band spectrum with a blackbody function. NIRDust needs a minimum of two spectra to run: a target spectrum, where the dust temperature will be estimated, and a reference spectrum, where the emission is considered to be purely stellar. The reference spectrum will be used by NIRDust to model the stellar emission from the target spectrum.

[ascl:2210.002] SPINspiral: Parameter estimation for analyzing gravitational-wave signals

SPINspiral analyzes gravitational-wave signals from stellar-mass binary inspirals detected by ground-based interferometers such as LIGO and Virgo. It performs parameter estimation on these signals using Markov-chain Monte-Carlo (MCMC) techniques. This analysis includes the spins of the binary components. Written in C, the package is modular; its main routine is as small as possible and calls other routines, which perform tasks such as reading input, choosing and setting (starting or injection) parameters, and handling noise. Other routines compute overlaps and likelihoods, contain the MCMC core, and manage more general support functions and third-party routines.

[ascl:2210.001] PSS: Pulsar Survey Scraper

Pulsar Survey Scraper aggregates pulsar discoveries before they are included in the ATNF pulsar catalog and enables searching and filtering based on position and dispersion measure. This facilitates identifying new pulsar discoveries. Pulsar Survey Scraper can be downloaded or run online using the Pulsar Survey Scraper webform.

[submitted] EleFits

EleFits is a modern C++ package to read and write FITS files which focuses on safety, user-friendliness, and performance.

[ascl:2209.020] FastQSL: Quasi-separatrix Layers computation method

FastQSL calculate the squashing factor Q at the photosphere, a cross section, or a box volume, given a 3D magnetic field with Cartesian, uniform or stretched grids. It is available in IDL and in an optimized version using Fortran for calculations and field line tracing. Use of a GPU accelerates a step-size adaptive scheme for the most computationally intensive part, the field line tracing, making the code fast and efficient.

[ascl:2209.019] SolTrack: Compute the position of the Sun in topocentric coordinates

SolTrack computes the position of the Sun, the rise and set times and azimuths, and transit times and altitudes. It includes corrections for aberration and parallax, and has a simple routine to correct for atmospheric refraction, taking into account local atmospheric conditions. SolTrack is derived from the Fortran library libTheSky (ascl:2209.018). The package can be used to track the Sun on a low-specs machine, such as a microcontroller or PLC, and can be used for (highly) concentrated (photovoltaic) solar power or accurate solar-energy modeling.

[ascl:2209.018] libTheSky: Compute positions of celestial bodies and events

libTheSky compute the positions of celestial bodies, such as the Moon, planets, and stars, and events, including conjunctions and eclipses, with great accuracy. Written in Fortran, libTheSky can use different reference frames (heliocentric, geocentric, topocentric) and coordinate systems (ecliptic, equatorial, galactic; spherical, rectangular), and the user can choose low- or high-accuracy calculations, depending on need.

[ascl:2209.017] SpectraPy: Extract and reduce astronomical spectral data

SpectraPy collects algorithms and methods for data reduction of astronomical spectra obtained by a through slits spectrograph. It produces two-dimensional wavelength calibrated spectra corrected by instrument distortions. The library is designed to be spectrograph independent and can be used on both longslit (LS) and multi object spectrograph (MOS) data. SpectraPy comes with a set of already configured spectrographs, but it can be easily configured to reduce data of other instruments.

[ascl:2209.016] RAPOC: Rosseland and Planck mean opacities calculator

RAPOC (Rosseland and Planck Opacity Converter) uses molecular absorption measurements (i.e., wavelength-dependent opacities) for a given temperature, pressure, and wavelength range to calculate Rosseland and Planck mean opacities for use in atmospheric modeling. The code interpolates between discrete data points and can use ExoMol and DACE data, or any user-defined data provided in a readable format. RAPOC is simple, straightforward, and easily incorporated into other codes.

[ascl:2209.015] TauREx3: Tau Retrieval for Exoplanets

TauREx 3 (Tau Retrieval for Exoplanets) provides a fully Bayesian inverse atmospheric retrieval framework for exoplanetary atmosphere modeling and retrievals. It is fully customizable, allowing the user to mix and match atmospheric parameters and add additional ones. The framework builds forward models, simulates instruments, and performs retrievals, and provides a rich library of classes for building additional programs and using new atmospheric parameters.

[ascl:2209.014] SyntheticISOs: Synthetic Population of Interstellar Objects

Synthetic Population of Interstellar Objects generates a synthetic population of interstellar objects (orbits and sizes) in arbitrary volume of space around the Sun. The only necessary assumption is that the population of ISOs in the interstellar space (far from any massive body) is homogeneous and isotropic. The assumed distribution of interstellar velocities of ISOs has to be provided as an input. This distribution can be defined analytically, but also in a discrete form. The algorithm, based on the multivariate inverse transform sampling method, is implemented in Python.

[ascl:2209.013] wsynphot: Synthetic photometry package using quantities

wsynphot provides a broad set of filters, including observation facility, instrument, and wavelength range, and functions for imaging stars to produce a filter curve showing the transmission of light for each wavelength value. It can create a filter curve object, plot the curve, and allows the user to do calculations on the filter curve object.

[ascl:2209.012] URILIGHT: Time-dependent Monte-Carlo radiative-transfer

The time dependent Monte-Carlo code URILIGHT, written in Fortran 90, assumes homologous expansion. Energy deposition resulting from the decay of radioactive isotopes is calculated by a Monte-Carlo solution of the γ-ray transport, for which interaction with matter is included through Compton scattering and photoelectric absorption. The temperature is iteratively solved for in each cell by requiring that the total emissivity equals the total absorbed energy.

[ascl:2209.011] GaLight: 2D modeling of galaxy images

GaLight (Galaxy shapes of Light) performs two-dimensional model fitting of optical and near-infrared images to characterize the light distribution of galaxies with components including a disk, bulge, bar and quasar. Light is decomposes into PSF and Sersic, and the fitting is based on lenstronomy (ascl:1804.01). GaLight's automated features including searching PSF stars in the FOV, automatically estimating the background noise level, and cutting out the target object galaxies (QSOs) and preparing the materials to model the data. It can also detect objects in the cutout stamp and quickly create Sersic keywords to model them, and model QSOs and galaxies using 2D Sersic profile and scaled point source.

[ascl:2209.010] HyPhy: Hydrodynamical Physics via Deep Generative Painting

HyPhy maps from dark matter only simulations to full hydrodynamical physics models. It uses a fully convolutional variational auto-encoder (VAE) to synthesize hydrodynamic fields conditioned on dark matter fields from N-body simulations. After training, HyPhy can probabilistically map new dark matter only simulations to corresponding full hydrodynamical outputs and generate posterior samples for studying the variance of the mapping. This conditional deep generative model is implemented in TensorFlow.

[ascl:2209.009] GRUMPY: Galaxy formation with RegUlator Model in PYthon

GRUMPY (Galaxy formation with RegUlator Model in PYthon) models the formation of dwarf galaxies. When coupled with realistic mass accretion histories of halos from simulations and reasonable choices for model parameter values, this simple regulator-type framework reproduces a broad range of observed properties of dwarf galaxies over seven orders of magnitude in stellar mass. GRUMPY matches observational constraints on the stellar mass--halo mass relation and observed relations between stellar mass and gas phase and stellar metallicities, gas mass, size, and star formation rate. It also models the general form and diversity of star formation histories (SFHs) of observed dwarf galaxies. The software can be used to predict photometric properties of dwarf galaxies hosted by dark matter haloes in N-body simulations, such as colors, surface brightnesses, and mass-to-light ratios and to forward model observations of dwarf galaxies.

[ascl:2209.008] PINION: Accelerating radiative transfer simulations for cosmic reionization

PINION (Physics-Informed neural Network for reIONization) predicts the complete 4-D hydrogen fraction evolution from the smoothed gas and mass density fields from pre-computed N-body simulations. Trained on C2-Ray simulation outputs with a physics constraint on the reionization chemistry equation, PINION accurately predicts the entire reionization history between z = 6 and 12 with only five redshift snapshots and a propagation mask as a simplistic approximation of the ionizing photon mean free path. The network's predictions are in good agreement with simulation to redshift z > 7, though the oversimplified propagation mask degrades the network's accuracy for z < 7.

[ascl:2209.007] AMBER: Fast pipeline for detecting single-pulse radio transients

AMBER (Apertif Monitor for Bursts Encountered in Real-time) detects single-pulse radio phenomena, such as pulsars and fast radio bursts, in real time. It is a fully auto-tuned pipeline that offloads compute-intensive kernels to many-core accelerators; the software automatically tunes these kernels to achieve high performance on different platforms.

[ascl:2209.006] KaRMMa: Curved-sky mass map reconstruction

KaRMMa (Kappa Reconstruction for Mass MApping) performs curved-sky mass map reconstruction using a lognormal prior from weak-lensing surveys. It uses a fully Bayesian approach with a physically motivated lognormal prior to sample from the posterior distribution of convergence maps. The posterior distribution of KaRMMa maps are nearly unbiased in one-point and two-point functions and peak/void counts. KaRMMa successfully captures the non-Gaussian nature of the distribution of κ values in the simulated maps, and KaRMMa posteriors correctly characterize the uncertainty in summary statistics.

[ascl:2209.005] SCORE: Shape COnstraint REstoration

The Shape COnstraint REstoration algorithm (SCORE) is a proximal algorithm based on sparsity and shape constraints to restore images. Its main purpose is to restore images while preserving their shape information. It can, for example, denoise a galaxy image by instanciating SCORE and using its denoise method and then visualize the results, and can deconvolve multiple images with different parameter values.

[ascl:2209.004] Cluster Toolkit: Tools for analyzing galaxy clusters

Cluster Toolkit calculates weak lensing signals from galaxy clusters and cluster cosmology. It offers 3D density and correlation functions, halo bias models, projected density and differential profiles, and radially averaged profiles. It also calculates halo mass functions, mass-concentration relations, Sunyaev-Zel’dovich (SZ) cluster signals, and cluster magnification. Cluster Toolkit consists of a Python front end wrapped around a well optimized back end in C.

[ascl:2209.003] DeepMass: Cosmological map inference with deep learning

DeepMass infers dark matter maps from weak gravitational lensing measurements and uses deep learning to reconstruct cosmological maps. The code can also be incorporated into a Moment Network to enable high-dimensional likelihood-free inference.

[ascl:2209.002] Herculens: Differentiable gravitational lensing

Herculens models imaging data of strong gravitational lenses. The package supports various degrees of model complexity, ranging from standard smooth analytical profiles to pixelated models and machine learning approaches. In particular, it implements multiscale pixelated models regularized with sparsity constraints and wavelet decomposition, for modeling both the source light distribution and the lens potential. The code is fully differentiable - based on JAX (ascl:2111.002) - which enables fast convergence to the solution, access to the parameters covariance matrix, efficient exploration of the parameter space including the sampling of posterior distributions using variational inference or Hamiltonian Monte-Carlo methods.

[ascl:2209.001] A-SLOTH: Semi-analytical model to connect first stars and galaxies to observables

A-SLOTH (Ancient Stars and Local Observables by Tracing Halos) connects the formation of the first stars and galaxies to observables. The model is based on dark matter merger trees, on which A-SLOTH applies analytical recipes for baryonic physics to model the formation of both metal-free and metal-poor stars and the transition between them. The software samples individual stars and includes radiative, chemical, and mechanical feedback. A-SLOTH has versatile applications with moderate computational requirements. It can be used to constrain the properties of the first stars and high-z galaxies based on local observables, predicts properties of the oldest and most metal-poor stars in the Milky Way, can serve as a subgrid model for larger cosmological simulations, and predicts next-generation observables of the early Universe, such as supernova rates or gravitational wave events.

[ascl:2208.025] Yonder: Data denoising and reconstruction

YONDER uses singular value decomposition to perform low-rank data denoising and reconstruction. It takes a tabular data matrix and an error matrix as input and returns a denoised version of the original dataset as output. The approach enables a more accurate data analysis in the presence of uncertainties. Consequently, this package can be used as a simple toolbox to perform astronomical data cleaning.

[ascl:2208.024] toise: Performance estimator for high-energy neutrino detectors

The toise framework estimates the sensitivity of natural-medium neutrino detectors such as IceCube-Gen2 to sources of high-energy astrophysical neutrinos. It uses parameterizations of a detector's fiducial area or volume, selection efficiency, energy resolution, angular resolution, and event classification efficiency to convert (surface) neutrino fluxes into mean event rates in bins of observable space. These are then used to estimate statistical quantities of interest, e.g., the median sensitivity to some flux (i.e., 90% upper limit assuming the true flux is zero) or the median discovery potential (i.e., the flux level at which the null hypothesis would be rejected at 5 sigma in 50% of realizations).

[ascl:2208.023] CubeFit: Regularized 3D fitting for spectro-imaging data

Cubefit is an OXY class that performs spectral fitting with spatial regularization in a spectro-imaging context. The 3D model is based on a 1D model and 2D parameter maps; the 2D maps are regularized using an L1L2 regularization by default. The estimator is a compound of a chi^2 based on the 1D model, a regularization term based of the 2D regularization of the various 2D parameter maps, and an optional decorrelation term based on the cross-correlation of specific pairs of parameter maps.

[ascl:2208.022] PyNAPLE: Automated pipeline for detecting changes on the lunar surface

PyNAPLE (PYthon Nac Automated Pair Lunar Evaluator) detects changes and new impact craters on the lunar surface using Lunar Reconnaissance Orbiter Narrow Angle Camera (LRO NAC) images. The code enables large scale analyses of sub-kilometer scale cratering rates and refinement of both scaling laws and the luminous efficiency.

[ascl:2208.021] GSSP: Grid Search in Stellar Parameters

GSSP (Grid Search in Stellar Parameters) is based on a grid search in the fundamental atmospheric parameters and (optionally) individual chemical abundances of the star (or binary stellar components) in question. It uses atmosphere models and spectrum synthesis, which assumes a comparison of the observations with each theoretical spectrum from the grid. The code can optimize five stellar parameters at a time (effective temperature, surface gravity, metallicity, microturbulent velocity, and projected rotational velocity of the star) and synthetic spectra can be computed in any number of wavelength ranges. GSSP builds the grid of theoretical spectra from all possible combinations of the above mentioned parameters, and delivers the set of best fit parameters, the corresponding synthetic spectrum, and the ASCII file containing the individual parameter values for all grid points and the corresponding chi-square values.

[ascl:2208.020] GStokes: Magnetic field structure and line profiles calculator

GStokes performs simple multipolar fits to circular polarization data to provide information about the field strength and geometry. It provides forward calculation of the disc-integrated Stokes parameter profiles as well as magnetic inversions under several widely used simplifying approximations of the polarized line formation. GStokes implements the Unno–Rachkovsky analytical solution of the polarized radiative transfer equation and the weak-field approximation with the Gaussian local profiles. The magnetic field geometry is described with one of the common low-order multipolar field parametrizations. Written in IDL, GStokes provides a user-friendly graphical front-end.

[ascl:2208.019] RadioLensfit: Radio weak lensing shear measurement in the visibility domain

RadioLensfit measures star-forming galaxy ellipticities using a Bayesian model fitting approach. The software uses an analytical exponential Sersic model and works in the visibility domain avoiding Fourier Transform. It also simulates visibilities of observed SF galaxies given a source catalog and Measurement Sets containing the description of the radio interferometer and of the observation. It provides both serial and MPI versions.

[ascl:2208.018] EstrellaNueva: Expected rates of supernova neutrinos calculator

EstrellaNueva calculates expected rates of supernova neutrinos in detectors. It provides a link between supernova simulations and the expected events in detectors by calculating fluences and event rates in order to ease any comparison between theory and observation. The software is a standalone tool for exploring many physics scenarios, and offers an option to add analytical cross sections and define any target material.

[ascl:2208.017] HOCHUNK3D: Dust radiative transfer in 3D

HOCHUNK3D is an updated version of the HOCHUNK radiative equilibrium code (ascl:1711.013); the code has been converted to Fortran 95, which allows a specification of one-dimensional (1D), 2D, or 3D grids at runtime. The code is parallelized so it can be run on multiple processors on one machine, or on multiple machines in a network. It includes 3-D functionality and several other additional geometries and features. The code calculates radiative equilibrium temperature solution, thermal and PAH/vsg emission, scattering and polarization in protostellar geometries. HOCHUNK3D also computes spectral energy distributions (SEDs), polarization spectra, and images.

[ascl:2208.016] CRPropa3: Simulation framework for propagating extraterrestrial ultra-high energy particles

CRPropa3, an improved version of CRPropa2 (ascl:1412.013), provides a simulation framework to study the propagation of ultra-high-energy nuclei up to iron on their voyage through an (extra)galactic environment. It takes into account pion production, photodisintegration, and energy losses by pair production of all relevant isotopes in the ambient low-energy photon fields, as well as nuclear decay. CRPropa3 can model the deflection in (inter)galactic magnetic fields, the propagation of secondary electromagnetic cascades, and neutrinos for a multitude of scenarios for different source distributions and magnetic environments. It enables the user to predict the spectra of UHECR (and of their secondaries), their composition and arrival direction distribution. Additionally, the low-energy Galactic propagation can be simulated by solving the transport equation using stochastic differential equations. CRPropa3 features a very flexible simulation setup with python steering and shared-memory parallelization.

[ascl:2208.015] J-comb: Combine high-resolution and low-resolution data

J-comb combines high-resolution data with large-scale missing information with low-resolution data containing the short spacing. Based on uvcombine (ascl:2208.014), it takes as input FITS files of low- and high-resolution images, the angular resolution of the input images, and the pixel size of the input images, and outputs a FITS file of the combined image.

[ascl:2208.014] uvcombine: Combine images with different resolutions

uvcombine combines single-dish and interferometric data. It can combine high-resolution images that are missing large angular scales (Fourier-domain short-spacings) with low-resolution images containing the short/zero spacing. uvcombine includes the "feathering" technique for interferometry data, implementing a similar approach to CASA’s (ascl:1107.013) feather task but with additional options. Also included are consistency tests for the flux calibration and single-dish scale by comparing the data in the uv-overlap range.

[ascl:2208.013] SPAMMS: Spectroscopic PAtch Model for Massive Stars

SPAMMS (Spectroscopic PAtch Model for Massive Stars), designed with geometrically deformed systems in mind, combines the eclipsing binary modelling code PHOEBE 2 (ascl:1106.002) and the NLTE radiative transfer code FASTWIND to produce synthetic spectra for systems at given phases, orientations and geometries. SPAMMS reproduces the morphology of observed spectral line profiles for overcontact systems and the Rossiter-Mclaughlin and Struve-Sahade effects.

[ascl:2208.012] DELIGHT: Identify host galaxies of transient candidates

DELIGHT (Deep Learning Identification of Galaxy Hosts of Transients) automatically identifies host galaxies of transient candidates using multi-resolution images and a convolutional neural network. This library has a class with several methods to get the most likely host coordinates starting from given transient coordinates. In order to do this, the DELIGHT object needs a list of object identifiers and coordinates (oid, ra, dec). With this information, it downloads PanSTARRS images centered around the position of the transients (2 arcmin x 2 arcmin), gets their WCS solutions, creates the multi-resolution images, does some extra preprocessing of the data, and finally predicts the position of the hosts using a multi-resolution image and a convolutional neural network. DELIGHT can also estimate the host's semi-major axis if requested, taking advantage of the multi-resolution images.

[ascl:2208.011] POIS: Python Optical Interferometry Simulation

POIS (Python Optical Interferometry Simulation) provides the building blocks to simulate the operation of a ground-based optical interferometer perturbed by atmospheric seeing perturbations. The package includes functions to generate simulated atmospheric turbulent wavefront perturbations, correct these perturbations using adaptive optics, and combine beams from an arbitrary number of telescopes, with or without spatial filtering, to provide complex fringe visibility measurements.

[ascl:2208.010] FFD: Flare Frequency Distribution

FFD (Flare Frequency Distribution) fits power-laws to FFDs. FFDs relate the frequency (i.e., occurrence rate) of flares to their energy, peak flux, photometric equivalent width, or other parameters. This module was created to handle disparate datasets between which the flare detection limit varies; in essence, the number of flares detected is treated as following a Poisson distribution while the flare energies are treated as following a power law.

[ascl:2208.009] LeXInt: Leja Exponential Integrators

LeXInt (Leja interpolation for eXponential Integrators) is a temporal exponential integration package using the method of polynomial interpolation at Leja points. Exponential Rosenbrock (EXPRB) and Exponential Propagation Iterative Runge-Kutta (EPIRK) methods use the Leja interpolation method to compute the functions. For linear PDEs, one can get the exact solution (in time) by directly computing the matrix exponential.

[ascl:2208.008] RJ-plots: Automated objective classification of 2D structures

RJ-plots uses a moments of inertia method to disentangle a 2D structure's elongation from its centrally over/under-density, thus providing a means for the automated and objective classification of such structures. It may be applied to any 2D pixelated image such as column density maps or moment zero maps of molecular lines. This method is a further development of J-plots (ascl:2009.007).

[ascl:2208.007] VapoRock: Modeling magma ocean atmospheres and stellar nebula

VapoRock calculates the equilibrium partial pressures of metal-bearing gas species of specific elements above the magma ocean surface to determine the metal-bearing composition of the atmosphere as a function of temperature and the bulk composition of the magma ocean. It utilizes ENKI's ThermoEngine (ascl:2208.006) and combines estimates for element activities in silicate melts with thermodynamic data for metal and metal oxide vapor species.

[ascl:2208.006] ThermoEngine: Thermodynamic properties estimator and phase equilibrium calculator

ThermoEngine estimates the thermodynamic properties of minerals, fluids, and melts, and calculates phase equilibriums. The Equilibrate module of ThermoEngine provides Python functions and classes for computing equilibrium phase assemblages with focus on MELTS calculations. The Phases module includes Python functions and classes for computing standard thermodynamic calculations utilizing the Berman, Holland and Powell, or Stixrude-Lithgow-Bertelloni endmember databases, and calculations based on solution properties utilized by MELTS. There are many helper functions available in this module that assist in the calculation of pseudosections, univariant equilibria and the construction of phase diagrams.

[ascl:2208.005] Asymmetric Uncertainty: Handling nonstandard numerical uncertainties

Asymmetric Uncertainty implements and provides an object class for dealing with uncertainties for physical quantities that are not symmetric. Instances of the class behave appropriately with other numeric objects under most mathematical operations, and the associated errors propagate accordingly. The class also provides utilities such as methods for evaluating and plotting probability density functions, as well as capabilities for handling arrays of such objects. Standard and symmetric uncertainties are also supported.

[ascl:2208.004] TOM Toolkit: Target and Observation Manager Toolkit

The TOM Toolkit combines a flexible, searchable database of all information related to a scientific research project, with an observation and data analysis control system, and communication and data visualization tools. This Toolkit includes a fully operational TOM (Target and Observation Manager) system in addition to a range of optional tools for specific tasks, including interfaces to widely-used observing facilities and data archives and data visualization tools. With TOM Toolkit, project teams can develop and customize a system for their own science goals, without needing specialist expertise in databasing.

[ascl:2208.003] Scatfit: Scattering fits of time domain radio signals (Fast Radio Bursts or pulsars)

Scatfit models observed burst signals of impulsive time domain radio signals ( e.g., Fast Radio Bursts (FRBs) or pulsars pulses), which usually are convolution products of various effects, and fits them to the experimental data. It includes several models for scattering and instrumental effects. The code loads the experimental time domain radio data, cleans them, fits an aggregate scattering model to the data, and robustly estimates the model parameters and their uncertainties. Additionally, scatfit determines the scaling of the scattering time with frequency, i.e. the scattering index, and the scattering-corrected dispersion measure of the burst or pulse.

[ascl:2208.002] qrpca: QR-based Principal Components Analysis

qrpca uses QR-decomposition for fast principal component analysis. The software is particularly suited for large dimensional matrices. It makes use of torch for internal matrix computations and enables GPU acceleration, when available. Written in both R and python languages, qrpca provides functionalities similar to the prcomp (R) and sklearn (python) packages.

[ascl:2208.001] BlaST: Synchrotron peak estimator for blazars

BlaST (Blazar Synchrotron Tool) estimates the synchrotron peak of blazars given their spectral energy distribution. It uses a machine-learning algorithm that simplifies the estimation and also provides a reliable uncertainty estimation. The package naturally accounts for additional SED components from the host galaxy and the disk emission. BlaST also supports bulk estimation, e.g. estimating a whole catalog, by providing a directory or zip file containing the seds as well as an output file in which to write the results.

[submitted] Eidein: Interactive Visualization Tool for Deep Active Learning

Eidein interactively visualizes a data sample for the selection of an informative (contains data with high predictive uncertainty, is diverse, but not redundant) data subsample for deep active learning. The data sample is projected to 2-D with a dimensionality reduction technique. It is visualized in an interactive scatter plot that allows a human expert to select and annotate the data subsample.

[submitted] BMarXiv

BMarXiv scans new (i.e., since the last time checked) submissions from arXiv, ranks submissions based on keyword matches, and produces an HTML page as an output.

The keywords are looked for (with regex capabilities) in the title, abstract, but also the author list, so it is possible to look for people too. The score is calculated for each specific entry but additional (and optional) scoring is performed using the first author recent submissions and/or the other authors' recent submissions.

It is possible to include/exclude any arXiv categories (within astro-ph or not). New astronomical conferences (from CADC by default) and new codes (from ASCL.net) are also checked and can also be scanned for keywords.

A local bibliography file can be scanned to find frequent words/groups of words that could become scanned keywords.

[ascl:2207.035] massmappy: Mapping dark matter on the celestial sphere

massmappy recovers convergence mass maps on the celestial sphere from weak lensing cosmic shear observations. It relies on SSHT (ascl:2207.034) and HEALPix (ascl:1107.018) to handle sampled data on the sphere. The spherical Kaiser-Squires estimator is implemented.

[ascl:2207.034] SSHT: Fast spin spherical harmonic transforms

SSHT performs fast and exact spin spherical harmonic transforms; functionality is also provided to perform fast and exact adjoint transforms, forward and inverse transforms, and spherical harmonic transforms for a number of alternative sampling schemes. The code can interface with DUCC (ascl:2008.023) and use it as a backend for spherical harmonic transforms and rotations.

[ascl:2207.033] piXedfit: Analyze spatially resolved SEDs of galaxies

piXedfit provides a self-contained set of tools for analyzing spatially resolved properties of galaxies using imaging data or a combination of imaging data and the integral field spectroscopy (IFS) data. piXedfit has six modules that can handle all tasks in the analysis of the spatially resolved SEDs of galaxies, including images processing, a spatial-matching between reduced broad-band images with an IFS data cube, pixel binning, performing SED fitting, and making visualization plots for the SED fitting results.

[ascl:2207.032] gwdet: Detectability of gravitational-wave signals from compact binary coalescences

gwdet computes the probability of detecting a gravitational-wave signal from compact binaries averaging over sky-location and source inclination. The code has two classes, averageangles and detectability. averageangles computes the detection probability, averaged over all angles (such as sky location, polarization, and inclination), as a function of the projection parameter. detectability computes the detection probability of a non-spinning compact binary.

[ascl:2207.031] BANZAI: Beautiful Algorithms to Normalize Zillions of Astronomical Images

BANZAI (Beautiful Algorithms to Normalize Zillions of Astronomical Images) processes raw data taken from Las Cumbres Observatory and produces science quality data products. It is capable of reducing single or multi-extension fits files. For historical data, BANZAI can also reduce the data cubes that were produced by the Sinistro cameras.

[ascl:2207.030] Analysis of dipole alignment in large-scale distribution of galaxy spin directions

This code analyzes a dipole axis in the distribution of galaxy spin directions. The code takes as input a list of galaxies, their equatorial coordinates, and their spin directions. It then determines the statistical significance of possible dipole axis at any point in the sky by comparing the cosine dependence of the spin directions to the mean and standard deviation of the cosine dependence after 2000 runs with random spin directions. A code to analyze the binomial distribution of the spin directions using Monte Carlo simulation is also available.

[ascl:2207.029] ParticleGridMapper: Particle data interpolator

ParticleGridMapper.jl interpolates particle data onto either a Cartesian (uniform) grid or an adaptive mesh refinement (AMR) grid where each cell contains no more than one particle. The AMR grid can be trimmed with a user-defined maximum level of refinement. Three different interpolation schemes are supported: nearest grid point (NGP), smoothed-particle hydrodynamics (SPH), and Meshless finite mass (MFM). It is multi-threading parallel.

[ascl:2207.028] disksurf: Measure the molecular emission surface of protoplanetary disks

disksurf measures the height of optically thick emission or photosphere in moderately inclined protoplanetary disks. The package is dependent on AstroPy (ascl:1304.002) and uses GoFish (ascl:2011.016) to retrieve data from FITS data cubes and user-specified parameters to return a surface object containing the disk-centric coordinates of the surface and the gas temperature and rotation velocity at those locations. disksurf provides clipping, smoothing, and diagnostic functions as well.

[ascl:2207.027] ConeRot: Velocity perturbations extractor

ConeRot extracts velocity perturbations in protoplanetary disks from observed line centroids maps ν∘, by creating axially-symmetric centroid maps. It also derives 3D rotation curves in disk-centered cylindrical coordinates, and can estimate the disk orientation based on line data alone. It approximates the unit opacity surface of an axially symmetric disc by a series of cones whose orientations are fit to the observed velocity centroid in concentric radial domains, or regions, with the disc orientation and the rotation curve both optimized to fit ν∘ in each region. ConeRot extracts the perturbations directly from observations without strong assumptions about the underlying disk model and employs a reduced number of free parameters.

[ascl:2207.026] pdspy: MCMC tool for continuum and spectral line radiative transfer modeling

pdspy fits Monte Carlo radiative transfer models for protostellar/protoplanetary disks to ALMA continuum and spectral line datasets using Markov Chain Monte Carlo fitting. It contains two tools, one to fit ALMA continuum visibilities and broadband spectral energy distributions (SEDs) with full radiative transfer models, and another to fit ALMA spectral line visibilities with protoplanetary disk models that include a vertically isothermal, power law temperature distribution. No radiative equilibrium calculation is done.

[ascl:2207.025] casa_cube: Display and analyze astronomical data cubes

casa_cube provides an interface to data cubes generated by CASA (ascl:1107.013) or Gildas (ascl:1305.010). It performs simple tasks such as plotting given channel maps, moment maps, and line profile in various units, and also corrects for cloud extinction, reconvolves with a beam taper, and permits quick and easy comparisons with models.

[ascl:2207.024] pymcfost: Python interface to the MCFOST 3D radiative transfer code

pymcfost provides an interface to and can be used to visualize results from the 3D radiative transfer code MCFOST (ascl:2207.023). pymcfost can set up continuum and line models, read a single model or library of models, plot basic quantities such as density structures and temperature maps, and plot observables, including SEDs, polarization maps, visibilities, and channels maps (with spatial and spectral convolution). It can also convert units (e.g. W.m-2 to Jy or brightness temperature), and it provides an interface to the ALMA CASA simulator (ascl:1107.013).

[ascl:2207.023] MCFOST: Radiative transfer code

MCFOST is a 3D continuum and line radiative transfer code based on an hybrid Monte Carlo and ray-tracing method. It is mainly designed to study the circumstellar environment of young stellar objects, but has been used for a wide range of astrophysical problems. The calculations are done exactly within the limitations of the Monte Carlo noise and machine precision, i.e., no approximation are used in the calculations. The code has been strongly optimized for speed.

MCFOST is primarily designed to study protoplanetary disks. The code can reproduce most of the observations of disks, including SEDs, scattered light images, IR and mm visibilities, and atomic and molecular line maps. As the Monte Carlo method is generic, any complex structure can be handled by MCFOST and its use can be extended to other astrophysical objects. For instance, calculations have succesfully been performed on infalling envelopes and AGB stars. MCFOST also includes a non-LTE line transfer module, and NLTE level population are obtained via iterations between Monte Carlo radiative transfer calculations and statistical equilibrium.

[ascl:2207.022] triple-stability: Triple-star system stability determinator

triple-stability uses a simple form of an artificial neural network, a multi-layer perceptron, to check whether a given configuration of a triple-star system is dynamically stable. The code is written in Python and the MLP classifier can be imported to other custom Python3 scripts.

[ascl:2207.021] BAYGAUD: BAYesian GAUssian Decomposer

BAYGAUD (BAYesian GAUssian Decomposer) implements the decomposition of velocity profiles in a data cube and subsequent classification. It uses MultiNest (ascl:1109.006) for calculating the posterior distribution and the evidence for a given likelihood function. The code models a given line profile with an optimal number of Gaussians based on the Bayesian Markov Chain Monte Carlo (MCMC) techniques. BAYGAUD is parallelized using the Message-Passing Interface (MPI) standard, which reduces the time needed to calculate the evidence using MCMC techniques.

[ascl:2207.020] vKompth: Time-dependent Comptonization model for black-hole X-ray binaries

vKompth fits the energy-dependent rms-amplitude and phase-lag spectra of low-frequency quasi-periodic oscillations in low mass black-hole X-ray binaries using a variable Comptonization model. The accretion disc is modeled as a multi-temperature blackbody source emitting soft photons which are then Compton up-scattered in a spherical corona, including feedback of Comptonized photons that return to the disc.

[ascl:2207.019] walter: Predictor for the number of resolved stars in a given observation from RST

walter calculates the number density of stars detected in a given observation aiming to resolve a stellar population. The code also calculates the exposure time needed to reach certain population features, such as the horizontal branch, and provides an estimate of the crowding limit. walter was written with the expectation that such calculations will be very useful for planning surveys with the Nancy Grace Roman Space Telescope (RST, formerly WFIRST).

[ascl:2207.018] pocoMC: Preconditioned Monte Carlo method for accelerated Bayesian inference

pocoMC performs Bayesian inference, including model comparison, for challenging scientific problems. The code utilizes a normalizing flow to precondition the target distribution by removing any correlations between its parameters. pocoMC then generates posterior samples, used for parameter estimation, with a powerful adaptive Sequential Monte Carlo algorithm manifesting a sampling efficiency that can be orders of magnitude higher than without precondition. Furthermore, pocoMC also provides an unbiased estimate of the model evidence that can be used for the task of Bayesian model comparison. The code is designed to excel in demanding parameter estimation problems that include multimodal and highly non–Gaussian target distributions.

[ascl:2207.017] LOTUS: 1D Non-LTE stellar parameter determination via Equivalent Width method

LOTUS (non-LTE Optimization Tool Utilized for the derivation of atmospheric Stellar parameters) derives stellar parameters via Equivalent Width (EW) method with the assumption of 1D non-local thermodynamic equilibrium. It mainly applies on the spectroscopic data from high resolution spectral survey. It can provide extremely accurate measurement of stellar parameters compared with non-spectroscopic analysis from benchmark stars. LOTUS provides a fast optimizer for obtaining stellar parameters based on Differential Evolution algorithm, well constrained uncertainty of derived stellar parameters from slice-sampling MCMC from PyMC3 (ascl:1610.016), and can interpolate the Curve of Growth from theoretical EW grid under the assumptions of LTE and Non-LTE. It also visualizes excitation and ionization balance when at the optimal combination of stellar parameters.

[ascl:2207.016] DustPy: Simulation of dust evolution in protoplanetary disks

DustPy simulates the radial evolution of gas and dust in protoplanetary disks, involving viscous evolution of the gas disk and advection and diffusion of the dust disk, as well as dust growth by solving the Smoluchowski equation. The package provides a standard simulation and the ability to plot results, and also allows modification of the initial conditions for dust, gas, the grid, and the central star.

[ascl:2207.015] calviacat: Calibrate star photometry by catalog comparison

calviacat calibrates star photometry by comparison to a catalog, including PanSTARRS 1, ATLAS-RefCat2, and SkyMapper catalogs. Catalog queries are cached so that subsequent calibrations of the same or similar fields can be more quickly executed.

[ascl:2207.014] petitRADTRANS: Exoplanet spectra calculator

petitRADTRANS (pRT) calculates transmission and emission spectra of exoplanets for clear and cloudy planets. It also incorporates an easy subpackage for running retrievals with nested sampling. It allows the calculation of emission or transmission spectra, at low or high resolution, clear or cloudy, and includes a retrieval module to fit a petitRADTRANS model to spectral data. pRT has two different opacity treatment modes. The low resolution mode runs calculations at λ/Δλ ≤ 1000 using the so-called correlated-k treatment for opacities. The high resolution mode runs calculations at λ/Δλ ≤ 106, using a line-by-line opacity treatment.

[ascl:2207.013] MuSCAT2_transit_pipeline: MuSCAT2 photometry and transit analysis pipelines

MuSCAT2_transit_pipeline provides photometry and transit analysis pipelines for MuSCAT2. It consists of a set of executable scripts and two Python packages: muscat2ph for photometry, and muscat2ta for transit analysis. The MuSCAT2 photometry can be carried out using the scripts only. The transit analysis can also in most cases be done using the main transit analysis script m2fit, but the muscat2ta package also offers high-level classes that can be used to carry out more customized transit analysis as a Python script (or Jupyter notebook).

[ascl:2207.012] ExoCTK: Exoplanet Characterization Tool Kit

The Exoplanet Characterization ToolKit (ExoCTK) focuses primarily on the atmospheric characterization of exoplanets and provides tools for time-series observation planning, forward modeling, data reduction, limb darkening, light curve fitting, and retrievals. It contains calculators for contamination, visibility, integrations and groups, and includes several Jupyter Notebooks to aid in learning how to use the various tools included in the ExoCTK package.

[ascl:2207.011] samsam: Scaled Adaptive Metropolis SAMpler

The samsam package provides two samplers, a scaled adaptive metropolis algorithm to robustly obtain samples from a target distribution, and a covariance importance sampling algorithm to efficiently compute the model evidence (or other integrals). It also includes tools to assess the convergence of the sam sampler and a few commonly used prior distributions.

[ascl:2207.010] Helios-r2: Bayesian nested-sampling retrieval code

Helios-r2 performs atmospheric retrieval of brown dwarf and exoplanet spectra. It uses a Bayesian statistics approach by employing a nested sampling method to generate posterior distributions and calculate the Bayesian evidence. The nested sampling itself is done by Multinest (ascl:1109.006). The computationally most demanding parts of the model have been written in NVIDIA's CUDA language for an increase in computational speed. Successful applications include retrieval of brown dwarf emission spectra and secondary eclipse measurements of exoplanets.

[ascl:2207.009] SolAster: 'Sun-as-a-star' radial velocity variations

SolAster provides querying, analysis, and calculation methods to independently derive 'sun-as-a-star' RV variations using SDO/HMI data for any time span since SDO has begun observing. Scaling factors are provided in order to calculate RVs comparable to magnitudes measured by ground-based spectrographs (HARPS-N and NEID). In addition, there are routines to calculate magnetic observables to compare with RV variations and determine what is driving Solar activity.

[ascl:2207.008] TESS_PRF: Display the TESS pixel response function

TESS_PRF displays the TESS pixel response function (PRF) at any location on the detector. The package is primarily for estimating how the light from a point source is distributed given its position in a TESS Target Pixel File (TPF) or TESScut postage stamp. By default, it accesses the relevant PRF files on MAST, but can also reference files on a local directory. TESS_PRF assumes the PRF doesn't change considerably within a small TPF. The PRF model can be positioned by passing the relative row and column location within the TPF to the "resample" method. The pixel locations follow WCS convention, that an integer value corresponds to the center of a pixel.

[ascl:2207.007] Pyriod: Period detection and fitting routines

Pyriod provides basic period detection and fitting routines for astronomical time series. Written in Python and designed to be run interactively in a Jupyter notebook, it displays and allows the user to interact with time series data, fit frequency solutions, and save figures from the toolbar. It can display original or residuals time series, fold the time series on some frequency, add selected peaks from the periodogram to the model, and refine the fit by computing a least-squared fit of the model using Lmfit (ascl:1606.014).

[ascl:2207.006] MultiModes: Efficiently analyze pulsating stars

MultiModes extracts the most significant frequencies of a sample of classical pulsating stars. The code takes a directory with light curves and initial parameters as input. For every light curve, the code calculates the frequencies spectrum, or periodogram, with the Fast Lomb Scargle algorithm, extracts the higher amplitude peak, and evaluates whether it is a real signal or noise. It fits frequency, amplitude, and phase through non-linear optimization, using a multisine function. This function is redefined with the new calculated parameters. MultiModes then does a simultaneous fit of a number of peaks (20 by default), subtracts them from the original signal, and goes back to the beginning of the loop with the residual, repeating the same process until the stop criterion is reached. After that, the code can filter suspicious spurious frequencies, those of low amplitude below the Rayleigh resolution, and possible combined frequencies.

[ascl:2207.005] echelle: Dynamic echelle diagrams for asteroseismology

Echelle diagrams are used mainly in asteroseismology, where they function as a diagnostic tool for estimating Δν, the separation between modes of the same degree ℓ; the amplitude spectrum of a star is stacked in equal slices of Δν, the large separation. The echelle Python code creates and manipulates echelle diagrams. The code provides the ability to dynamically change Δν for rapid identification of the correct value. echelle features performance optimized dynamic echelle diagrams and multiple backends for supporting Jupyter or terminal usage.

[ascl:2207.004] cosmic-kite: Auto-encoding the Cosmic Microwave Background

Cosmic-kite performs a fast estimation of the TT Cosmic Microwave Background (CMB) power spectra corresponding to a set of cosmological parameters; it can also estimate the maximum-likelihood cosmological parameters from a power spectra. This software is an auto-encoder that was trained and calibrated using power spectra from random cosmologies computed with the CAMB code (ascl:1102.026).

[ascl:2207.003] MeSsI: MErging SystemS Identification

MeSsI performs an automatic classification between merging and relaxed clusters. This method was calibrated using mock catalogues constructed from the millennium simulation, and performs the classification using some machine learning techniques, namely random forest for classification and mixture of gaussians for the substructure identification.

[ascl:2207.002] pynucastro: Python interfaces to the nuclear reaction rate databases

pynucastro interfaces to the nuclear reaction rate databases, including the JINA Reaclib nuclear reactions database. This set of Python interfaces enables interactive exploration of rates and collection of rates (networks) in Jupyter notebooks and easy creation of the righthand side routines for reaction network integration (the ODEs) for use in simulation codes.

[ascl:2207.001] MULTIGRIS: Multicomponent probabilistic grid search

MULTIGRIS (also called mgris) uses the sequential Monte Carlo method in PyMC (ascl:1506.005) to extract the posterior distributions of primary grid parameters and predict unobserved parameters/observables. The code accepts either a discrete number of components and/or continuous (e.g., power-law, normal) distributions for any given parameter. MULTIGRIS, written in Python, infers the posterior probability functions of parameters in a multidimensional potentially incomplete grid with some observational tracers defined for each parameter set. Observed values and their potentially asymmetric uncertainties are used to calculate a likelihood which, together with predefined or custom priors, produces the posterior distributions. Linear combinations of parameter sets may be used with inferred mixing weights and nearest neighbor or linear interpolation may be used to sample the parameter space.

[submitted] CosmicEmu: High Precision Emulator for the Nonlinear Matter Power Spectrum

Modern cosmological surveys are delivering datasets characterized by unprecedented quality and statistical completeness. In order to maximally extract cosmological information from these observations, matching theoretical predictions are needed. In the nonlinear regime of structure formation, cosmological simulations are the primary means of obtaining the required information but the computational cost of sufficiently resolved large-volume simulations makes it prohibitive to run very large ensembles. Nevertheless, precision emulators built on a tractable number of high-quality simulations can be used to build very fast prediction schemes to enable a variety of cosmological inference studies. The "Mira-Titan Universe" simulation suite covers the standard six cosmological parameters and, in addition, includes massive neutrinos and a dynamical dark energy equation of state. It is based on 111 cosmological simulations, each covering a (2.1Gpc)^3 volume and evolving 3200^3 particles, and augments these higher-resolution simulations with an additional set of 1776 lower-resolution simulations and TimeRG perturbation theory results to cover scales straddling the linear to mildly nonlinear regimes. The emulator built on this suite, the CosmicEmu, provides predictions at the two to three percent level of accuracy over a wide range of cosmological parameters. Presented in: https://arxiv.org/abs/2207.12345.

[submitted] Compact Binary Chebyshev Polynomial Representation Ephemeris Kernel

The software used to transform the tabular USNO/AE98 asteroid ephemerides into a Chebyshev polynomial representations, and evaluate them at an arbitrary time is available. The USNO/AE98 consisted of the ephemerides of fifteen of the largest asteroids, and were used in The Astronomical Almanac from 2000 through 2015. These ephemerides are outdated and no longer available, but the software used to store and evaluate them is still available and provides a robust method for storing compact ephemerides of solar system bodies.

The object of the software is to provide a compact binary representation of solar system bodies with eccentric orbits, which can produce the body's position and velocity at an arbitrary instant within the ephemeris' time span. It uses a modification of the Newhall (1989) algorithm to achieve this objective. The Newhall algorithm is used to store both the Jet Propulsion Laboratory DE and the Institut de mécanique céleste et de calcul des éphémérides INPOP high accuracy planetary ephemerides. The Newhall algorithm breaks an ephemeris into a number time contiguous segments, and each segment is stored as a set of Chebyshev polynomial coefficients. The length of the time segments and the maximum degree Chebyshev polynomial coefficient is fixed for each body. This works well for bodies with small eccentricities, but it becomes inefficient for a body in a highly eccentric orbit. The time segment length and maximum order Chebyshev polynomial coefficient must be chosen to accommodate the strong curvature and fast motion near pericenter, while the body spends most of its time either moving slowly near apocenter or in the lower curvature mid-anomaly portions of its orbit. The solution is to vary the time segment length and maximum degree Chebyshev polynomial coefficient with the body's position. The portion of the software that converts tabular ephemerides into a Chebyshev polynomial representation (CPR) performs this compaction automatically, and the portion that evaluates that representation requires only a modest increase in the evaluation time.

The software also allows the user to choose the required tolerance of the CPR. Thus, if less accuracy is required a more compact, somewhat quicker to evaluate CPR can be manufactured and evaluated. Numerical tests show that a fractional precision of 4e-16 may be achieved, only a factor of 4 greater than the 1e-16 precision of a 64-bit IEEE (2019) compliant floating point number.

The software is written in C and designed to work with the C edition of the Naval Observatory Vector Astrometry Software (NOVAS). The programs may be used to convert tabular ephemerides of other solar system bodies as well. The included READ.ME file provides the details of the software and how to use it.

REFERENCES

IEEE Computer Society 2019, IEEE Standard for Floating-Point Arithmetic. IEEE STD 754-2019, IEEE, pp. 1–84

Newhall, X X 1989, 'Numerical Representation of Planetary Ephemerides,' Celest. Mech., 45, 305 - 310

[ascl:2206.028] Spritz: General relativistic magnetohydrodynamic code

The Spritz code is a fully general relativistic magnetohydrodynamic code based on the Einstein Toolkit (ascl:1102.014). The code solves the GRMHD equations in 3D Cartesian coordinates and on a dynamical spacetime. Spritz supports tabulated equations of state, takes finite temperature effects into account and allows for the inclusion of neutrino radiation.

[ascl:2206.027] DustFilaments: Paint filaments to produce a thermal dust full sky map at mm frequencies

DustFilaments paints filaments in the Celestial Sphere to generate a full sky map of the Thermal Dust emission at millimeter frequencies by integrating a population of 3D filaments. The code requires a magnetic field cube, which can be calculated separately or by DustFilaments. With the magnetic field cube as input, the package creates a random filament population with a given seed, and then paints a filament into a healpix map provided as input; the healpix map is updated in place.

[ascl:2206.026] ShapePipe: Galaxy shape measurement pipeline

ShapePipe processes single-exposure images and stacked images. Input images have to be calibrated beforehand for astrometry and photometry. The code can handle different image and file types, such as single-exposure mosaic, single-exposure single-CCD, stacked images, database catalog files, and PSF files, some of which are created by the pipeline during the analysis, among others. The end product of ShapePipe is a final catalog containing information for each galaxy, including its shape parameters and the ellipticity components :math:e_1 and :math:e_2. This catalog also contains shapes of artificially sheared images. This information is used in post-processing to compute calibrated shear estimates via metacalibration.

[ascl:2206.025] CuspCore: Core formation in dark matter haloes and ultra-diffuse galaxies by outflow episodes

CuspCore describes the formation of flat cores in dark matter haloes and ultra-diffuse galaxies from feedback-driven outflow episodes. The halo response is divided into an instantaneous change of potential at constant velocities followed by an energy-conserving relaxation. The core assumption of the model is that the total energy E=U+K is conserved for each shell enclosing a given dark matter mass, which is treated in the code as a least-square minimization of the difference between the final and the initial energy of each shell.

[ascl:2206.024] Wavetrack: Arbitrary time-evolving solar object recognition and tracking

Wavetrack recognizes and tracks CME shock waves, filaments, and other solar objects. The code creates base images by averaging а series of images a few minutes prior to the start of the eruption and constructs base difference images by subtracting base images from the current raw image of the sequence. This enhances the change in intensity caused by coronal bright fronts, omits static details, and reduces noise. Wavetrack then chooses an appropriate intensity interval and decomposes the base difference or running difference image with an A-Trous wavelet transform, where each wavelet coefficient is obtained by convolving the image array with a corresponding iteration of the wavelet kernel. When the maximum value of the wavelet coefficients for a connected set of pixels satisfies certain conditions, this region is considered as a structure on the respective wavelet coefficient. Separate stand-alone object masks are obtained with a clustering algorithm and objects are renumbered according to the number of the quadrant they belong at each iteration.

[ascl:2206.023] pyPipe3D: Spectroscopy analysis pipeline

The spectroscopy analysis pipeline pyPipe3D produces coherent and easy to distribute and compare parameters of stellar populations and ionized gas; it is suited in particular for data from the most recent optical IFS surveys. The pipeline is build using pyFIT3D, which is the main spectral fitting module included in this package.

[ascl:2206.022] RealSim-IFS: Realistic synthetic integral field spectrscopy of galaxies from numerical simulations

RealSim-IFS generates survey-realistic integral-field spectroscopy (IFS) observations of galaxies from numerical simulations of galaxy formation. The tool is designed primarily to emulate current and experimental observing strategies for IFS galaxy surveys in astronomy, and can reproduce both the flux and variance propagation of real galaxy spectra to cubes. RealSim-IFS has built-in functions supporting SAMI and MaNGA IFU footprints, but supports any fiber-based IFU design, in general.

[ascl:2206.021] PyCASSO2: Stellar population and emission line fits in integral field spectra

PyCASSO runs the STARLIGHT code (ascl:1108.006) in integral field spectra (IFS). Cubes from various instruments are supported, including PMAS/PPAK (CALIFA), MaNGA, GMOS and MUSE. Emission lines can be measured using DOBBY, which is included in the package. The package also includes tools for IFS cubes analysis and plotting.

[ascl:2206.020] CCDLAB: FITS image viewer and data reducer

CCDLAB provides graphical user interface functionality for FITS image viewing and data reduction based on the JPFITS FITS-file interface. It can view, manipulate, and save FITS primary image data and image extensions, view and manipulate FITS image headers, and view FITS Bintable extensions. The code enables batch processing, viewing, and saving of FITS images and searching FITS files on disk. CCDLAB also provides general image reduction techniques, source detection and characterization, and can create World Coordinate Solutions automatically or manually for FITS images.

[ascl:2206.019] SEVN: Stellar EVolution for N-body

The population synthesis code SEVN (Stellar EVolution for N-body) includes up-to-date stellar evolution (through look-up tables), binary evolution, and different recipes for core-collapse supernovae. SEVN also provides an up-to-date formalism for pair-instability and pulsational pair-instability supernovae, and is designed to interface with direct-summation N-body codes such as STARLAB (ascl:1010.076) and HiGPUs (ascl:1207.002).

[ascl:2206.018] MADYS: Isochronal parameter determination for young stellar and substellar objects

MADYS (Manifold Age Determination for Young Stars) determines the age and mass of young stellar and substellar objects. The code automatically retrieves and cross-matches photometry from several catalogs, estimates interstellar extinction, and derives age and mass estimates for individual objects through isochronal fitting. MADYS harmonizes the heterogeneity of publicly-available isochrone grids and the user can choose amongst several models, some of which have customizable astrophysical parameters. Particular attention has been dedicated to the categorization of these models, labeled through a four-level taxonomical classification.

[ascl:2206.017] atoMEC: Average-Atom code for Matter under Extreme Conditions

atoMEC simulates high energy density phenomena such as in warm dense matter. It uses Kohn-Sham density functional theory, in combination with an average-atom approximation, to solve the electronic structure problem for single-element materials at finite temperature.

[ascl:2206.016] wdwarfdate: White dwarfs age calculator

wdwarfdate derives the Bayesian total age of a white dwarf from an effective temperature and a surface gravity. It runs a chain of models assuming single star evolution and estimates the following parameters and their uncertainties: total age of the object, mass and cooling age of the white dwarf, and mass and lifetime of the progenitor star.

[ascl:2206.015] Smart: Automatic differentiation of accelerations and variational equations

Smart provides pre-processing for LP-VIcode (ascl:1501.007). It computes the accelerations and variational equations given a generic user-defined potential function, eliminating the need to calculate manually the accelerations and variational equations.

[ascl:2206.014] SpinSpotter: Stellar rotation periods from high-cadence photometry calculator

SpinSpotter calculates stellar rotation periods from high-cadence photometry. The code uses the autocorrelation function (ACF) to identify stellar rotation periods up to one-third the observational baseline of the data. SpinSpotter includes diagnostic tools that describe features in the ACF and allows tuning of the tolerance with which to accept a period detection.

[ascl:2206.013] smooth: Smoothing for N-body simulations

Smooth calculates several mean quantities for all particles in an N-Body simulation output file. The program produces a file for each type of output specified on the command line. This output file is in ASCII format with one smoothed quantity for each particle. The program uses a symmetric SPH (Smoothed Particle Hydrodynamics) smoothing kernel to find the mean quantities.

[ascl:2206.012] WDPhotTools: White Dwarf Photometric SED fitter and luminosity function builder

WDPhotTools generates color-color diagrams and color-magnitude diagrams in various photometric systems, plots cooling profiles from different models, and computes theoretical white dwarf luminosity functions based on the built-in or supplied models of the (1) initial mass function, (2) total stellar evolution lifetime, (3) initial-final mass relation, and (4) white dwarf cooling time. The software has three main parts: the formatters that handle the output models from various works in the format as they are downloaded; the photometric fitter that solves for the WD parameters based on the photometry, with or without distance and reddening; and the generator of the white dwarf luminosity function in bolometric magnitudes or in any of the photometric systems available from the atmosphere model.

[ascl:2206.011] IFSCube: Analyze and process integral field spectroscopy data cubes

IFSCube performs analysis tasks in data cubes of integral field spectroscopy. It contains routines for fitting spectral features in 1D spectra and data cubes and rotation models to velocity fields; it also contains a routine that inspects the fit results. Though originally intended to make user scripts more concise, analysis can also be performed on the fly by using an interactive interpreter such as ipython. By default, IFSCube assumes data are in the Flexible Image Transport System (FITS) standard, but the package can be modified easily to allow use of other data formats.

[submitted] JPFITS (C# .Net FITS File Interaction)

FITS File interaction written in Visual Studio C# .Net.

JPFITS is not based upon any other implementation and is written from the ground-up, consistent with the FITS standard, designed to interact with FITS files as object-oriented structures.

JPFITS provides functionality to interact with FITS images and binary table extensions, as well as providing common mathematical methods for the manipulation of data, data reductions, profile fitting, photometry, etc.

JPFITS also implements object-oriented classes for Point Source Extraction, World Coordinate Solutions (WCS), WCS automated field solving, FITS Headers and Header Keys, etc.

The automatic world coordinate solver is based on the trigonometric algorithm as described here:

https://iopscience.iop.org/article/10.1088/1538-3873/ab7ee8

All function parameters, methods, properties, etc., are coded with XML descriptions which will function with Visual Studio. Other code editors may or may not read the XML files.

Everything which is reasonable to parallelize in order to benefit from the computation speed increase for multi-threaded systems has been done so. In all such cases function options are given in order to specify the use of parallelism or not. Generally, most image manipulation functions are highly amenable to parallelism. No parallelism is forced, i.e., any code which may execute parallelized is given a user option to do so or not.

[submitted] fastrometry: Fast world coordinate solution solver

Fastrometry is a Python implementation of the fast world coordinate solution solver for the FITS standard astronomical image. When supplied with the approximate field center (+-25%) and the approximate field scale (+-10%) of the telescope and detector system the astronomical image is from, fastrometry provides WCS solutions almost instantaneously. The algorithm is also originally implemented with parallelism enabled in the Windows FITS image processor and viewer CCDLAB (ascl:2206.021).

[ascl:2206.010] pyHIIexplorerV2: Integrated spectra of HII regions extractor

pyHIIexplorerV2 extracts the integrated spectra of HII regions from integral field spectroscopy (IFS) datacubes. The detection of HII regions performed by pyHIIexplorer is based on two assumptions: 1) HII regions have strong emission lines that are clearly above the continuum emission and the average ionized gas emission across each galaxy, and 2) the typical size of HII regions is about a few hundreds of parsecs, which corresponds to a usual projected size of a few arcsec at the distance of our galaxies. These assumptions will define clumpy structures with a high Ha emission line contrast in comparison to the continuum. pyHIIexplorerV2 is written in Python; it is based on and is a successor to HIIexplorer (ascl:1603.017).

[ascl:2206.009] Craterstats3: Analyze and plot crater count data for planetary surface dating

Craterstats3 analyzes and plots crater count data for planetary surface dating. It is a Python implementation of Craterstats2 (ascl:2206.008) and is designed to replicate the output of the previous version as closely as possible. As before, it produces plots in cumulative, differential, Hartmann, and R-plot styles with possible overlays of crater counts, isochrons, equilibrium functions and epoch boundaries, as well aschronology and impact rate functions. Data can be shown with various binnings or unbinned, and age estimates made by either cumulative fitting, differential fitting, or Poisson timing evaluation. Numerical results can be output as text for further processing elsewhere. A number of published chronology systems are already set up for use, but new ones may be added by the user. The software is designed to be easily integrated into other software, which could allow the addition of a graphical interface or the inclusion of some Craterstats functions into a GIS.

[ascl:2206.008] Craterstats2: Planetary surface dating from crater size-frequency distribution measurements

Craterstats2 plots crater counts and determining surface ages. The software plots isochrons in cumulative, differential, R-plot and Hartmann presentations, and makes isochron fits to both cumulative and differential data. Hartmann-style piecewise production functions may also be used. A Python implementation of the software, Craterstats3, is also available.

[ascl:2206.007] CircleCraters: Crater-counting plugin for QGIS

CircleCraters is a projection independent crater counting plugin for QGIS. It has the flexibility to crater count in a GIS environment on Windows, OS X, or Linux, and uses three-click input to define crater rims as a circle.

[ascl:2206.006] MYRaf: Aperture photometry GUI for IRAF

MYRaf is a practicable astronomical image reduction and photometry software and interface for IRAF (ascl:9911.002). The library uses IRAF, PyRAF (ascl:1207.011), Ginga (ascl:1303.020), and other python packages with a Qt framework for automated software processing of data from robotic telescopes.

[ascl:2206.005] NonnegMFPy: Nonnegative Matrix Factorization with heteroscedastic uncertainties and missing data

NonnegMFPy solves nonnegative matrix factorization (NMF) given a dataset with heteroscedastic uncertainties and missing data with a vectorized multiplicative update rule; this can be used create a mask and iterate the process to exclude certain new data by updating the mask. The code can work on multi-dimensional data, such as images, if the data are first flattened to 1D.

[ascl:2206.004] pystortion: Distortion measurement support

pystortion provides support for distortion measurements in astronomical imagers. It includes classes to support fitting of bivariate polynomials of arbitrary degree and helper functions for crossmatching catalogs. The crossmatching uses an iterative approach in which a two-dimensional distortion model is fit at every iteration and used to continuously refine the position of extracted sources.

[ascl:2206.003] ExoJAX: Spectrum modeling of exoplanets and brown dwarfs

ExoJAX provides auto-differentiable line-by-line spectral modeling of exoplanets/brown dwarfs/M dwarfs using JAX (ascl:2111.002). In a nutshell, ExoJAX allows the user to do a HMC-NUTS fitting using the latest molecular/atomic data in ExoMol, HITRAN/HITEMP, and VALD3. The code enables a fully Bayesian inference of the high-dispersion data to fit the line-by-line spectral computation to the observed spectrum, from end-to-end (i.e. from molecular/atomic databases to real spectra), by combining it with the Hamiltonian Monte Carlo in recent probabilistic programming languages such as NumPyro.

[submitted] Green Bank Observatory Gridder

A stand-alone spectral gridder and imager for the Green Bank Telescope, as well as functionality for any diameter telescope. Based around the cygrid package from Benjamin Winkel and Daniel Lenz

[ascl:2206.002] TCF: Transit Comb Filter periodogram

TCF calculates a periodogram designed to detect exoplanet transits after the light curve has been differenced. It is a matched filter for a periodic double-spike pattern. The difference operator that can be used independently for detrending a light curve; it is also embedded in ARIMA (autoregressive integrated moving average) Box-Jenkins modeling.

[ascl:2206.001] vortex: Helmholtz-Hodge decomposition for an AMR velocity field

vortex performs a Helmholtz-Hodge decomposition on vector fields defined on AMR grids, decomposing a vector field in its solenoidal (divergence-less) and compressive (curl-less) parts. It works natively on vector fields defined on Adaptive Mesh Refinement (AMR) grids, so that it can perform the decomposition over large dynamical ranges; it is also applicable to particle-based simulations. As vortex is devised primarily to investigate the properties of the turbulent velocity field in the Intracluster Medium (ICM), it also includes routines for multi-scale filtering the velocity field.

[ascl:2205.025] simulateSearch: High-time resolution data sets simulations for radio telescopes

simulateSearch simulates high time-resolution data in radio astronomy. The code is built around producing multiple binary data files that contain information on the radiometer noise and sources that are being simulated. These binary data files subsequently get combined and output PSRFITS
search mode files produced. The PSRFITS files can be processed using standard pulsar software packages such as PRESTO (ascl:1107.017).

[ascl:2205.024] MM-LSD: Multi-Mask Least-Squares Deconvolution

MM-LSD (Multi-Mask Least-Squares Deconvolution) performs continuum normalization of 2D spectra (echelle order spectra). It also masks and partially corrects telluric lines and extracts RVs from spectra. The code requires RASSINE (ascl:2102.022) and uses spectral line data from VALD3.

[ascl:2205.023] PyWPF: Waterfall Principal Component Analysis (PCA) Folding

PyWPF (Waterfall Principal Component Analysis Folding) finds periodicity in one-dimensional timestream data sets; it is particularly designed for very high noise situations where traditional methods may fail. Given a timestream, with each point being the arrival times of a source, the software computes the estimated period. The core function of the package requires several initial parameters to run, and using the best known period of the source (T_init) is recommended.

[ascl:2205.022] BANG: BAyesian decomposiotioN of Galaxies

BANG (BAyesian decomposiotioN of Galaxies) models both the photometry and kinematics of galaxies. The underlying model is the superposition of different components with three possible combinations: 1.) Bulge + inner disc + outer disc + Halo; 2.) Bulge + disc + Halo; and 3.) inner disc + outer disc + Halo. As CPU parameter estimation can take days, running BANG on GPU is recommended.

[ascl:2205.021] CPNest: Parallel nested sampling

CPNest performs Bayesian inference using the nested sampling algorithm. It is designed to be simple for the user to provide a model via a set of parameters, their bounds and a log-likelihood function. An optional log-prior function can be given for non-uniform prior distributions. The nested sampling algorithm is then used to compute the marginal likelihood or evidence. As a by-product the algorithm produces samples from the posterior probability distribution. The implementation is based on an ensemble MCMC sampler which can use multiple cores to parallelize computation.

[ascl:2205.020] ASTROMER: Building light curves embeddings using transfomers

ASTROMER is a Transformer-based model trained on millions of stars for the representation of light curves. Pretrained models can be directly used or finetuned on specific datasets. ASTROMER is useful in downstream tasks in which data are limited to train deep learning models.

[ascl:2205.019] HOPS: Haystack Observatory Postprocessing System

HOPS (Haystack Observatory Postprocessing System) analyzes the data generated by DiFX VLBI correlators. It is written in C for Linux computers, and emphasizes quality-control aspects of data processing. It sits between the correlator and an image-processing and/or geodetic-processing package, and performs basic fringe-fitting, data editing, problem diagnosis, and correlator support functions.

[ascl:2205.018] ASOHF: Adaptive Spherical Overdensity Halo Finder

ASOHF (Adaptive Spherical Overdensity Halo Finder) identifies bound dark matter structures (dark matter haloes) in the outputs of cosmological simulations, and works directly on an input particle list. The computational cost of running ASOHF in simulations with a large number of particles can be reduced by using a domain decomposition to split the simulation box into smaller boxes, or subdomains, which are then processed independently. The basic output of ASOHF is a halo catalog. The package includes a python code to build a merger tree from ASOHF outputs.

[ascl:2205.017] LiSA: LIghtweight Source finding Algorithms for analysis of HI spectral data

The LIghtweight Source finding Algorithms (LiSA) library finds HI sources in next generation radio surveys. LiSA can analyze input data cubes of any size with pipelines that automatically decompose data into different domains for parallel distributed analysis. For source finding, the library contains python modules for wavelet denoising of 3D spatial and spectral data, and robust automatic source finding using null-hypothesis testing. The source-finding algorithms all have options to automatically choose parameters, minimizing the need for manual fine tuning. Finally, LiSA also contains neural network architectures for classification and characterization of 3D spectral data.

[ascl:2205.016] Pryngles: PlanetaRY spaNGLES

Pryngles produces visualizations of the geometric configuration of a ringed exoplanet (an exoplanet with a ring or exoring for short) and calculates the light-curve signatures produced by these kind of planets. The model behind the package has been developed in an effort to predict the signatures that exorings may produce not only in the light-curve of transiting exoplanets (a problem that has been extensively studied) but also in the light of stars having non-transiting exoplanets.

[ascl:2205.015] CS-ROMER: Compressed Sensing ROtation MEasure Reconstruction

CS-ROMER (Compressed Sensing ROtation MEasure Reconstruction) is a compressed sensing reconstruction framework for Faraday depth spectra. It can simulation Faraday depth sources, subtract Galactic RM, and reconstruct Faraday depth sources from linearly polarized data and Faraday depth sources using Compressed Sensing.

[ascl:2205.014] FHD: Fast Holographic Deconvolution

FHD is an open-source imaging algorithm for radio interferometers and is written in IDL. The three main use-cases for FHD are efficient image deconvolution for general radio astronomy, fast-mode Epoch of Reionization analysis, and simulation. FHD inputs beam models, calibration files, and sky model catalogs and requires input data to be in uvfits format.

[ascl:2205.013] ld-exosim: Simulate biases using different limb darkening laws

ld-exosim selects the optimal (i.e. best estimator in a MSE sense) limb-darkening law for a given transiting exoplanet lightcurve and calculates the limb-darkening induced biases on various exoplanet parameters. Limb-darkening laws include linear, quadratic, logarithmic, square-root and three-parameter laws.

[ascl:2205.012] Zelda: Generate correlation functions and power spectra from a galaxy catalog

The Zelda command-line tool extracts correlation functions in velocity space from a galaxy catalog. Zelda is modular, extendable, and can be generalized to produce power spectra and to work in position space. Written in C, it was heavily inspired by the cosmological Boltzmann code CLASS (ascl:1106.020). Zelda is a parallel code using the OpenMP standard.

[ascl:2205.011] myRadex: Radex with a twist

myRadex solves essentially the same problem as RADEX (ascl:1010.075), except that it takes a different approach to solve the statistical equilibrium problem. Given an initial distribution, myRadex evolves the system towards equilibrium using an ODE solver. Frequencies in the input file are used by default, and a function for calculating critical densities of all the transitions of a molecule is included.

[ascl:2205.010] pyICs: Initial Conditions creator for isolated galaxy formation simulations

pyICs creates initial condition (IC) files for N-body simulations of the formation of isolated galaxies. It uses the pynbody analysis package (ascl:1305.002) to create the actual IC files. pyICs generates dark matter halos (DM) in dynamical equilibrium which host a rotating gas sphere. The DM particle velocities are drawn from the equilibrium distribution function and the gas sphere has an angular momentum profile. The DM and the gas share the same 3D radial density profile. The code natively supports the αβγ-models: ρ ~ (r/a)-γ[1+(r/a)α](γ-β)/α. If γ <= 3, the profiles are smoothly truncated outside the virial radius. The radial profile can be arbitrary as long as python functions for the profile itself and its first and second derivative with radius are given.

[ascl:2205.009] hyperas: Keras + Hyperopt

Hyperas is a convenience wrapper around hyperopt (ascl:2205.008) for fast prototyping with keras models (ascl:1806.022). Hyperas lets you use the power of hyperopt without having to learn the syntax of it. Instead, just define your keras model as you are used to, but use a simple template notation to define hyper-parameter ranges to tune.

[ascl:2205.008] Hyperopt: Distributed asynchronous hyper-parameter optimization

The Python library Hyperopt performs serial and parallel optimization over awkward search spaces, which may include real-valued, discrete, and conditional dimensions. Three algorithms are implemented in hyperopt: Random Search, Tree of Parzen Estimators (TPE), and Adaptive TPE. Algorithms can be parallelized in two ways, using either Apache Spark or MongoDB. To use Hyperopt, the objective function to minimize and the space over which to search, and the database in which to store all the point evaluations of the search have to be described, and the search algorithm to use has to be specified.

[ascl:2205.007] EarthScatterLikelihood: Event rates and likelihoods for Dark Matter direct detection in the presence of Earth-Scattering

EarthScatterLikelihood calculates event rates and likelihoods for Earth-scattering Dark Matter. It is written in Fortran with plotting routines in Python. For input, it uses results from Monte Carlo simulations generated by DaMaSCUS (ascl:1706.003). It includes routines for submitting many reconstructions in parallel on a cluster, and the properties of the detector, such as for a Germanium and a Sapphire detector, can be edited.

[ascl:2205.006] LATTE: Lightcurve Analysis Tool for Transiting Exoplanet

LATTE identifies, vets and characterizes signals in TESS lightcurves to weed out instrumental and astrophysical false positives. The program performs a fast in-depth analysis of targets that have already been identified as promising candidates by the main TESS pipelines or via alternative methods such as citizen science. The code automatically downloads the data products for any chosen TIC ID (short or long cadence TESS data) and produces a number of diagnostic plots that are compiled in a concise report.

[ascl:2205.005] maelstrom: Forward modeling of pulsating stars in binaries

maelstrom models binary orbits through the phase modulation technique. This set of custom PyMC3 models and solvers fit each individual datapoint in the time series by forward modeling the time delay onto the light curve. This approach fully captures variations in a light curve caused by an orbital companion.

[ascl:2205.004] FAlCon-DNS: Framework of time schemes for direct numerical simulation of annular convection

FAlCon-DNS (Framework of time schemes for direct numerical simulation of annular convection) solves for 2-D convection in an annulus and analyzes different time integration schemes. The framework contains a suite of IMEX, IMEXRK and RK time integration schemes. The code uses a pseudospectral method for spatial discretization. The governing equations contain both numerically stiff (diffusive) and non-stiff (advective) components for time discretization. The software offers OpenMP for parallelization.

[ascl:2205.003] QSOGEN: Model quasar SEDs

The QSOGEN collection of Python code models quasar colors, magnitudes and SEDs. It implements an empirically-motivated parametric model to efficiently account for the observed emission-line properties, host-galaxy contribution, dust reddening, hot dust emission, and IGM suppression in the rest-frame 900-30000A wavelength range for quasars with a wide range of redshift and luminosity.
The code is packaged with a set of empirically-derived emission-line templates and an empirically-derived quasar dust extinction curve which are publicly released.

[ascl:2205.002] am: Microwave through submillimeter-wave propagation tool for the terrestrial atmosphere

am performs optical depth, radiative transfer, and refraction computations involving propagation through the terrestrial atmosphere and other media at microwave through submillimeter wavelengths. The program is used in radio astronomy, atmospheric radiometry, and radio spectrum management.

[ascl:2205.001] PMOIRED: Parametric Modeling of Optical Interferometric Data

PMOIRED models astronomical spectro-interferometric data stored in the OIFITS format. Parametric modeling is used to describe the observed scene as blocks such as disks, rings and Gaussians which can be combined and their parameters linked. It includes plotting, least-square fitting and bootstrapping estimation of uncertainties. For spectroscopic instruments (such as GRAVITY), tools are provided to model spectral lines and correct spectra for telluric lines.

[submitted] Python “sgp4” module that offers official SGP4 C++ library

The “sgp4” module is a Python wrapper around the C++ version of the standard SGP4 algorithm for propagating Earth satellite positions from the element sets published by organizations like SpaceTrak and Celestrak. The code is the most recent version, including all of the corrections and bug fixes described in the paper _Revisiting Spacetrack Report #3_ (AIAA 2006-6753) by Vallado, Crawford, Hujsak, and Kelso. The test suite verifies that the Python wrapper returns exactly the coordinates specified in the C++ test cases.

[submitted] SWIFTGalaxy

SWIFTGalaxy provides a software abstraction of simulated galaxies produced by the SWIFT smoothed particle hydrodynamics code. It extends the SWIFTSimIO module and is tailored to analyses of particles belonging to individual simulated galaxies. It inherits from and extends the functionality of the SWIFTDataset. It understands the output of halo finders and therefore which particles belong to a galaxy, and its integrated properties. The particles occupy a coordinate frame that is enforced to be consistent, such that particles loaded on-the-fly will match e.g. rotations and translations of particles already in memory. Intuitive masking of particle datasets is also enabled. Finally, some utilities to make working in cylindrical and spherical coordinate systems more convenient are also provided.

[ascl:2204.020] MonoTools: Planets of uncertain periods detector and modeler

MonoTools detects, vets, and models transiting exoplanets, with a specific emphasis on monotransiting planets and those with unknown periods. It includes scripts specifically for searching and assessing a lightcurve for the presence of monotransits. MonoTools can also performing a best-fit transit model, determine whether transits are linked to any detected multi-transiting planet candidate or with each other, and can fit planets in a Bayesian way to account for uncertain periods, lightcurve gaps, and stellar variability, among other things.

[ascl:2204.019] DarkFlux: Dark Matter annihilation spectrum computer

DarkFlux analyzes indirect-detection signatures for next-generation models of dark matter (DM) with multiple annihilation channels. Input is user-generated models with 2 → 2 tree-level dark matter annihilation to pairs of Standard Model (SM) particles. The code analyzes DM annihilation to γ rays using three modules; one computes the fractional annihilation rate, the second computes the total flux at Earth due to DM annihilation, and the third compares the total flux to observational data and computes the upper limit at 95% confidence level (CL) on the total thermally averaged DM annihilation cross section.

[ascl:2204.018] ProFuse: Galaxies and components modeler

ProFuse produces physical models of galaxies and their components by combining the functionalities of the source extraction code PROFOUND (ascl:1804.006), the Bayesian galaxy fitting tool ProFit (ascl:1612.004), and the spectral generation package ProSpect (ascl:2002.007). ProFuse uses a self-consistent model for the star formation and metallicity history of the bulge and disk separately to generate images. The package then defines the model likelihood and optimizes the physical galaxy reconstruction using target images across a range of wavelengths.

[ascl:2204.017] RSG: Redshift Search Graphs

Redshift Search Graphs provides a fast and reliable way to test redshifts found from sub-mm redshift searches. The scripts can graphically test the robustness of a spectroscopic redshift of a galaxy, test the efficiency of an instrument towards spectroscopic redshift searches, and optimize observations of tunable institutes (such as ALMA) for upcoming redshift searches.

[ascl:2204.016] pySIDES: Simulated Infrared Dusty Extragalactic Sky in Python

pySIDES generates mock catalogs of galaxies in the (sub-)millimeter domain and associates spectral cubes (e.g., for intensity mapping experiments). It produces both continuum and CO, [CII], and [CI] line emissions. pySIDES is the Python version of the Simulated Infrared Dusty Extragalactic Sky (SIDES).

[ascl:2204.015] ADBSat: Aerodynamic Database for Satellites

ADBSat computes aerodynamic coefficient databases for satellite geometries in free-molecular flow (FMF) conditions. Written in MATLAB, ADBSat imports body geometry from .stl or .obj mesh files, calculates aerodynamic force and moment coefficient for different gas-surface interaction models, and calculates solar radiation pressure force and moment coefficient. It also takes multiple surface and material characteristics into consideration. ADBSat is a panel-method tool that is able to calculate aerodynamic or solar force and moment coefficient sets for satellite geometries by applying analytical (closed-form) expressions for the interactions to discrete flat-plate mesh elements. The panel method of ADBSat assumes FMF conditions. The code analyzes basic shadowing to identify panels that are shielded from the flow by other parts of the body and will therefore not experience any surface interactions. However, this method is dependent on the refinement of the input mesh and can be sensitive to the orientation and arrangement of the mesh elements with respect to the oncoming flow direction.

[ascl:2204.014] GADGET-4: Parallel cosmological N-body and SPH code

GADGET-4 (GAlaxies with Dark matter and Gas intEracT) is a parallel cosmological N-body and SPH code that simulates cosmic structure formation and calculations relevant for galaxy evolution and galactic dynamics. It is massively parallel and flexible, and can be applied to a variety of different types of simulations, offering a number of sophisticated simulation algorithms. GADGET-4 supports collisionless simulations and smoothed particle hydrodynamics on massively parallel computers.

The code can be used for plain Newtonian dynamics, or for cosmological integrations in arbitrary cosmologies, both with or without periodic boundary conditions. Stretched periodic boxes, and special cases such as simulations with two periodic dimensions and one non-periodic dimension are supported as well. The modeling of hydrodynamics is optional. The code is adaptive both in space and in time, and its Lagrangian character makes it particularly suitable for simulations of cosmic structure formation. Several post-processing options such as group- and substructure finding, or power spectrum estimation are built in and can be carried out on the fly or applied to existing snapshots. Through a built-in cosmological initial conditions generator, it is also particularly easy to carry out cosmological simulations. In addition, merger trees can be determined directly by the code.

[ascl:2204.013] SCRIPT: Semi-numerical Code for ReIonization with PhoTon-conservation

SCRIPT (Semi-numerical Code for ReIonization with PhoTon-conservation) generates the ionization field during the epoch of cosmological reionization using a photon-conserving algorithm. The code depends on density and velocity files obtained using a N-body simulation, which can be generated with a 2LPT code such as MUSIC (ascl:1311.011).

[ascl:2204.011] SimAb: Planet formation model

SimAb (Simulating Abundances) simulates planet formation, focusing on the atmosphere accretion of gas giant planets. The package can run the simulation in two different modes. The single simulation mode is run by specifying the initial conditions (the core mass, the initial orbital distance, the planetesimal ratio, and the dust grain fraction), and the mature planet mass and orbital distance. The multi run simulation mode requires specifying the mass and the final orbital distance of the mature planet; the simulation randomly assigns initial orbital distance, initial core mass, initial planetesimal ratio, and initial dust grain fraction. The package also provides Jupyter codes for plotting the results of the simulations.

[ascl:2204.010] FBCTrack: Fragmentation and bulk composition tracking

The fragmentation and bulk composition tracking package contains two codes. The fragmentation code models fragmentation in collisions for the C version of REBOUND (ascl:1110.016). This code requires setting two global parameters. It automatically produces a collision report that details the time of every collision, the bodies involved, how the collision was resolved, and how many fragments were produced; collision outcomes are assigned a numerical value. The bulk composition tracking code tracks the composition change as a function of mass exchange for bodies with a homogenous composition. It is a post-processing code that works in conjunction with the fragmentation code, and requires the collision report generated by the fragmentation code.

[ascl:2204.009] MAYONNAISE: ADI data imaging processing pipeline

MAYONNAISE (Morphological Analysis Yielding separated Objects iN Near infrAred usIng Sources Estimation), or MAYO for short, is a pipeline for exoplanet and disk high-contrast imaging from ADI datasets. The pipeline is mostly automated; the package also loads the data and injects synthetic data if needed. MAYONNAISE parameters are written in a json file called parameters_algo.json and placed in a working_directory.

[ascl:2204.008] RMNest: Bayesian approach to measuring Faraday rotation and conversion in radio signals

RMNest directly fits the Stokes Q and U (and V) spectra of a radio signal to measure the effects of Faraday rotation (or conversion) induced by propagation through a magnetized plasma along the line of sight. The software makes use of the Bayesian Inference Library (Bilby; ascl:1901.011) as an interface to the dynesty (ascl:1809.013) nested sampling algorithm.

[ascl:2204.007] RTS: Radio Transient Simulations

Radio Transient Simulations uses Monte-Carlo simulations to accurately determine transient rates in radio surveys. The user inputs either a real or simulated observational setup, and the simulations code calculates transient rate as a function of transient duration and peak flux. These simulations allow for simulating a wide variety of scenarios including observations with varying sensitivities and durations, multiple overlapping telescope pointings, and a wide variety of light curve shapes with the user having the ability to easily add more. Though the current scientific focus is on the radio regime, the simulations code can be easily adapted to other wavelength regimes.

[ascl:2204.006] dsigma: Galaxy-galaxy lensing Python package

dsigma analyzes galaxy-galaxy lensing. Written in Python, it has a broadly applicable API and is optimized for computational efficiency. While originally intended to be used with the shape catalog of the Hyper-Suprime Cam (HSC) survey, it should work for other surveys, most prominently the Dark Energy Survey (DES) and the Kilo-Degree Survey (KiDS).

[ascl:2204.005] TESS-Localize: Localize variable star signatures in TESS Photometry

TESS-Localize identifies the location on the target pixel files (TPF) where sources of variability found in the aperture originate. The user needs only to provide a list of frequencies found in the aperture that belong to the same source and the number of principal components needed to be removed from the light curve to ensure it is free of systematic trends.

[ascl:2204.004] Bayesian SZNet: Bayesian deep learning to predict redshift with uncertainty

Bayesian SZNet predicts spectroscopic redshift through use of a Bayesian convolutional network. It uses Monte Carlo dropout to associate predictions with predictive uncertainties, allowing the user to determine unusual or problematic spectra for visual inspection and thresholding to balance between the number of incorrect redshift predictions and coverage.

[ascl:2204.003] legacystamps: Retrieve DESI Legacy Imaging Surveys cutouts

The Python module legacystamps provides easy retrieval, both standalone and scripted, of FITS and JPEG cutouts from the DESI Legacy Imaging Surveys through URLs provided by the Legacy Survey viewer.

[ascl:2204.002] Astroplotlib: Python scripts to handle astronomical images

Astroplotlib builds images with any scale, overlay contours, physical bars, and orientation arrows (N and E axes) automatically. The package contains scripts to overlay pseudo-slits and obtain statistics from apertures, estimate the background sky, and overlay the fitted isophotes and their respective contours on an image. Astroplotlib can work with the output table from the Ellipse task of IRAF and overlay fitted isophotes and their respective contours. It includes a GUI for masking areas in the images by using different polygons, and can also obtain statistical information (e.g., total flux and mean, among others) from the masked areas. There is also a GUI to overlay star catalogs on an image and an option to download them directly from the Vizier server.

[ascl:2204.001] TG: Turbulence Generator

Turbulence Generator generates a time sequence of random Fourier modes via an Ornstein-Uhlenbeck (OU) process, used to drive turbulence in hydrodynamical simulation codes. It can also generate single turbulent realizations. Turbulence driving based on this method is currently supported by implementations in AREPO (ascl:1909.010), FLASH (ascl:1010.082), GADGET (ascl:0003.001), PHANTOM (ascl:1709.002), PLUTO (ascl:1010.045), and Quokka (ascl:2110.009).

[ascl:2203.031] TAWAS: Wave equation solver

TAWAS solves the wave equation for torsional Alfvèn waves in a viscous plasma. The background magnetic field is axisymmetric and force-free with no azimuthal component and the plasma beta is assumed to be negligible. The solution is calculated over a uniform numerical grid with coordinates r and z for the radius and height respectively. TAWAS, written in IDL, requires no input files. The problem parameters at the top of the code can be changed as need. The 'plotting' variable determines which plots are shown by the script; the code contains several options for plotting. Outputs can be saved to a specific location by changing the variables save_dir and run_name listed just below the parameters. The code outputs include solutions for the velocity perturbation, the magnetic field perturbation and the wave energy flux.

[ascl:2203.030] Wigglewave: Linearized governing equations solver

Wigglewave uses a finite difference method to solve the linearized governing equations for a torsion Alfvèn wave propagating in a plasma with negligible plasma beta and in a force-free axisymmetric magnetic field with no azimuthal component embedded in a high density divergent tube structure. Wigglewave is fourth order in time and space using a fourth-order central difference scheme for calculating spatial derivatives and a fourth-order Runge-Kutta (RK4) scheme for updating at each timestep. The solutions calculated are the perturbations to the velocity, v and to the magnetic field, b. All variables are calculated over a uniform grid in radius r and height z.

[ascl:2203.029] Bootsik: Potential field calculator

The Bootsik software generates and visualizes potential magnetic fields. bootsik.f90 generates a potential magnetic field on a 3D mesh, staggered relative to the magnetic potential, by extrapolating the magnetic field normal to the photospheric surface. The code first calculates a magnetic potential using a modified Green’s function method and then uses a finite differencing scheme to calculate the magnetic field from the potential. The IDL script boobox.pro can then be used to visualize the magnetic field.

[ascl:2203.028] SimLine: Radiative transfer in molecular lines

SimLine computes the profiles of molecular rotational transitions and atomic fine structure lines in spherically symmetric clouds with arbitrary density, temperature and velocity structure. The code is designed towards a maximum flexibility and very high accuracy based on a completely adaptive discretization of all quantities. The code can treat arbitrary species in spherically symmetric configurations with arbitrary velocity structures and optical depths between about -5 and 5000. Moreover, SimLine includes the treatment of turbulence and clumping effects in a local statistical approximation combined with a radial dependence of the correlation parameters. The code consists of two parts: the self-consistent solution of the balance equations for all level populations and energy densities at all radial points and the computation of the emergent line profiles observed from a telescope with finite beam width and arbitrary offset.

[ascl:2203.027] Zoobot: Deep learning galaxy morphology classifier

Zoobot classifies galaxy morphology with Bayesian CNN. Deep learning models were trained on volunteer classifications; these models were able to both learn from uncertain volunteer responses and predict full posteriors (rather than point estimates) for what volunteers would have said. The code reproduces and improves Galaxy Zoo DECaLS automated classifications, and can be finetuned for new tasks.

[ascl:2203.026] axionCAMB: Modification of the CAMB Boltzmann code

axionCAMB is a modified version of the publicly available code CAMB (ascl:1102.026). axionCAMB computes cosmological observables for comparison with data. This is normally the CMB power spectra (T,E,B,\phi in auto and cross power), but also includes the matter power spectrum.

[ascl:2203.025] SetCoverPy: A heuristic solver for the set cover problem

SetCoverPy finds an (near-)optimal solution to the set cover problem (SCP) as fast as possible. It employs an iterative heuristic approximation method, combining the greedy and Lagrangian relaxation algorithms. It also includes a few useful tools for a quick chi-squared fitting given two vectors with measurement errors.

[ascl:2203.024] Magrathea-Pathfinder: 3D AMR ray-tracing in simulations

Magrathea-Pathfinder propagates photons within cosmological simulations to construct observables. This high-performance framework uses a 3D Adaptive-Mesh Refinement and is built on top of the MAGRATHEA metalibrary (ascl:2203.023).

[ascl:2203.023] MAGRATHEA: Multi-processor Adaptive Grid Refinement Analysis for THEoretical Astrophysics

MAGRATHEA (Multi-processor Adaptive Grid Refinement Analysis for THEoretical Astrophysics) is a foundational cosmological library and a relativistic raytracing code. Classical linear algebra libraries come with their own operations and can be difficult to leverage for new data types. Instead of providing basic types, MAGRATHEA provides tools to generate base types such as scalar quantities, points, vectors, or tensors.

[ascl:2203.022] Vetting: Stand-alone tools for vetting transit signals in Kepler, K2 and TESS data

vetting contains simple, stand-alone Python tools for vetting transiting signals in NASA's Kepler, K2, and TESS data. The code performs a centroid test to look for significant changes in the centroid of a star during a transit or eclipse. vetting requires an installation of Python 3.8 or higher.

[ascl:2203.021] MG-MAMPOSSt: Test gravity with the mass profiles of galaxy clusters

MG-MAMPOSSt extends the MAMPOSSt code (ascl:2203.020), which performs Bayesian fits of models of mass and velocity anisotropy profiles to the distribution of tracers in projected phase space, to handle modified gravity models and constrain its parameters. It implements two distinct types of gravity modifications: general chameleon (including $f(\mathcal{R})$ models), and beyond Horndeski gravity (Vainshtein screening). MG-MAMPOSSt efficently explores the parameter space either by computing the likelihood over a multi-dimensional grid of points or by performing a simple Metropolis-Hastings MCMC. The code requires a Fortran90 compiler or higher and makes use of the getdist package (ascl:1910.018) to plot the marginalized distributions in the MCMC mode.

[ascl:2203.020] MAMPOSSt: Mass/orbit modeling of spherical systems

MAMPOSSt (Modeling Anisotropy and Mass Profiles of Observed Spherical Systems) is a Bayesian code to perform mass/orbit modeling of spherical systems. It determines marginal parameter distributions and parameter covariances of parametrized radial distributions of dark or total matter, as well as the mass of a possible central black hole, and the radial profiles of density and velocity anisotropy of one or several tracer components, all of which are jointly fit to the discrete data in projected phase space. It is based upon the MAMPOSSt likelihood function for the distribution of individual tracers in projected phase space (projected radius and line-of-sight velocity) and the CosmoMC Markov Chain Monte Carlo code (ascl:1106.025), run in generic mode. MAMPOSSt is not based on the 6D distribution function (which would require triple integrals), but on the assumption that the local 3D velocity distribution is an (anisotropic) Gaussian (requiring only a single integral).

[ascl:2203.019] agnpy: Modeling jetted Active Galactic Nuclei radiative processes with Python

agnpy focuses on the numerical computation of the photon spectra produced by leptonic radiative processes in jetted Active Galactic Nuclei (AGN). It includes classes describing the galaxy components responsible for line and thermal emission and calculates the absorption due to gamma-gamma pair production on soft (IR-UV) photon fields.

[ascl:2203.018] sympy2c: Generating fast C/C++ functions and ODE solvers from symbolic expressions

The Python package sympy2c allows creation and compilation of fast C/C++ based extension modules from symbolic representations. It can create fast code for the solution of high dimensional ODEs, or numerical evaluation of integrals where sympy fails to compute an anti-​derivative. Based on the symbolic formulation of a stiff ODE, sympy2c analyzes sparsity patterns in the Jacobian matrix of the ODE, and generates loop-​less fast code by unrolling loops in the internally used LU factorization algorithm and by avoiding unnecessary computations involving known zeros.

[ascl:2203.017] MaNGA-DAP: MaNGA Data Analysis Pipeline

The MaNGA data analysis pipeline (MaNGA DAP) analyzes the data produced by the MaNGA data-reduction pipeline (ascl:2203.016) to produced physical properties derived from the MaNGA spectroscopy. All survey-provided properties are currently derived from the log-linear binned datacubes (i.e., the LOGCUBE files).

[ascl:2203.016] MaNGA-DRP: MaNGA Data Reduction Pipeline

The MaNGA Data Reduction Pipeline (DRP) processes the raw data to produce flux calibrated, sky subtracted, coadded data cubes from each of the individual exposures for a given galaxy. The DRP consists of two primary parts: the 2d stage that produces flux calibrated fiber spectra from raw individual exposures, and the 3d stage that combines multiple flux calibrated exposures with astrometric information to produce stacked data cubes. These science-grade data cubes are then processed by the MaNGA Data Analysis Pipeline (ascl:2203.017), which measures the shape and location of various spectral features, fits stellar population models, and performs a variety of other analyses necessary to derive astrophysically meaningful quantities from the calibrated data cubes.

[ascl:2203.015] easyFermi: Fermi-LAT data analyzer

easyFermi provides a user-friendly graphical interface for basic to intermediate analysis of Fermi-LAT data in the framework of Fermipy (ascl:1812.006). The code can measure the gamma-ray flux and photon index, build spectral energy distributions, light curves, test statistic maps, test for extended emission, and relocalize the coordinates of gamma-ray sources. Tutorials for easyFermi are available on YouTube and GitHub.

[ascl:2203.014] AutoSourceID-Light: Source localization in optical images

AutoSourceID-Light (ASID-L) analyzes optical imaging data using computer vision techniques that can naturally deal with large amounts of data. The framework rapidly and reliably localizes sources in optical images.

[ascl:2203.013] PetroFit: Petrosian properties calculator and galaxy light profiles fitter

PetroFit calculates Petrosian properties, such as radii and concentration indices; it also fits galaxy light profiles. The package, built on Photutils (ascl:1609.011), includes tools for performing accurate photometry, segmentations, Petrosian properties, and fitting.

[ascl:2203.012] pyobs: Python framework for autonomous astronomical observatories

pyobs enables remote and fully autonomous observation control of astronomical telescopes. It provides an abstraction layer over existing drivers and a means of communication between different devices (called modules in pyobs). The code can also act as a hardware driver for all the devices used at an observatory. In addition, pyobs offers non-hardware-related modules for automating focusing, acquisition, guiding, and other routine tasks.

[ascl:2203.011] SATCHEL: Pipeline to search for long-period exoplanet signals

SATCHEL (Search Algorithm for Transits in the Citizen science Hunt for Exoplanets in Lightcurves) searches for individual signals of interest in time-series data classified through crowdsourcing. The pipeline was built for the purpose of finding long-period exoplanet transit signals in Kepler photometric time-series data, but may be adapted for searches for any kind of one-dimensional signals in crowdsourced classifications.

[ascl:2203.010] D2O: Distributed Data Object

D2O acts as a layer of abstraction between algorithm code and data-distribution logic to manage cluster-distributed multi-dimensional numerical arrays; this provides usability without losing numerical performance and scalability. D2O's global interface makes the cluster node's local data directly accessible for use in customized high-performance modules. D2O is written in Python; the code is portable and easy to use and modify. Expensive operations are carried out by dedicated external libraries like numpy and mpi4py and performance scales well when moving to an MPI cluster. In combination with NIFTy, D2O enables supercomputer based astronomical imaging via RESOLVE (ascl:1505.028) and D3PO (ascl:1504.018).

[ascl:2203.009] fleck: Fast starspot rotational modulation light curves

fleck simulates rotational modulation of stars due to starspots and is used to overcome the degeneracies and determine starspot coverages accurately for a sample of young stars. The code simulates starspots as circular dark regions on the surfaces of rotating stars, accounting for foreshortening towards the limb, and limb darkening. Supplied with the latitudes, longitudes, and radii of spots and the stellar inclinations from which each star is viewed, fleck takes advantage of efficient array broadcasting with numpy to return approximate light curves. For example, the code can compute rotational modulation curves sampled at ten points throughout the rotation of each star for one million stars, with two unique spots each, all viewed at unique inclinations, in about 10 seconds on a 2.5 GHz Intel Core i7 processor. This rapid computation of light curves en masse makes it possible to measure starspot distributions with techniques such as Approximate Bayesian Computation.

[ascl:2203.008] MIRaGe: Multi Instrument Ramp Generator

MIRaGe creates simulated exposures for NIRCam’s imaging and wide field slitless spectroscopy (WFSS) modes, NIRISS’s imaging, WFSS, and aperture masking interferometery (AMI) modes, and FGS’s imaging mode. It supports sidereal as well as non-sidereal tracking; for example, sources can be made to move across the field of view within an observation.

[ascl:2203.007] GAMERA: Source modeling in gamma astronomy

GAMERA handles spectral modeling of non-thermally emitting astrophysical sources in a simple and modular way. It allows the user to devise time-dependent models of leptonic and hadronic particle populations in a general astrophysical context (including SNRs, PWNs and AGNs) and to compute their subsequent photon emission. GAMERA can calculate the spectral evolution of a particle population in the presence of time-dependent or constant injection, energy losses and particle escape; it also calculates the radiation spectrum from a parent particle population.

[ascl:2203.006] starry_process: Interpretable Gaussian processes for stellar light curves

starry_process implements an interpretable Gaussian process (GP) for modeling stellar light curves. The code's hyperparameters are physically interpretable, and include the radius of the spots, the mean and variance of the latitude distribution, the spot contrast, and the number of spots, among others. The rotational period of the star, the limb darkening parameters, and the inclination (or marginalize over the inclination if it is not known) can also be specified.

[ascl:2203.005] pygacs: Toolkit to manipulate Gaia catalog tables

pygacs manipulates Gaia catalog tables hosted at ESA's Gaia Archive Core Systems (GACS). It provides python modules for the access and manipulation of tables in GACS, such as a basic query on a single table or crossmatch between two tables. It employs the TAP command line access tools described in the Help section of the GACS web pages. Both public and authenticated access have been implemented.

[ascl:2203.004] imexam: IMage EXAMination and plotting

imexam performs simple image examination and plotting, with similar functionality to IRAF's (ascl:9911.002) imexamine. It is a lightweight library that enables users to explore data from a command line interface, through a Jupyter notebook, or through a Jupyter console. imexam can be used with multiple viewers, such as DS9 (scl:0003.002) or Ginga (ascl:1303.020), or without a viewer as a simple library to make plots and grab quick photometry information. It has been designed so that other viewers may be easily attached in the future.

[ascl:2203.003] NIMBLE: Non-parametrIc jeans Modeling with B-spLinEs

NIMBLE (Non-parametrIc jeans Modeling with B-spLinEs) inferrs the cumulative mass distribution of a gravitating system from full 6D phase space coordinates of its tracers via spherical Jeans modeling. It models the Milky Way's dark matter halo using Gaia and Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) data. NIMBLE includes a basic inverse modeling Jeans routine that assumes perfect and complete data is available and a more complex forward modeling Jeans routine that deconvolves observational effects (uncertainties and limited survey volume) characteristic of Gaia and the DESI-MWS. It also includes tools for generating simple equilibrium model galaxies using Agama (ascl:1805.008) and imposing mock Gaia+DESI errors on 6D phase space input data.

[ascl:2203.002] exoVista: Planetary systems generator

exoVista generates a "universe" of planetary systems, creating thousands of models of quasi-self-consistent planetary systems around known nearby stars at scattered light wavelengths. It efficiently records the position, velocity, spectrum, and physical parameters of all bodies as functions of time. exoVista models can be used for simulating surveys using the direct imaging, transit, astrometric, and radial velocity techniques.

[ascl:2203.001] SISTER: Starshade Imaging Simulation Toolkit for Exoplanet Reconnaissance

SISTER (Starshade Imaging Simulations Toolkit for Exoplanet Reconnaissance) predicts how an exoplanet system would look in an instrument that utilizes an Starshade to block the light from the host star. The tool allows for controlling a set of parameters of the whole instrument for: (1) the Starshade design, (2) the exoplanetary system, (3) the telescope and (4) the camera. SISTER includes plotting software, and can also store simulations on disk for plotting with other software.

[submitted] RCETC: Roman Coronagraph Exposure Time Calculator

The Roman Coronagraph Exposure Time Calculator (Roman_Coronagraph_ETC for short) is the public version of the exposure time calculator of the Coronagraph Instrument aboard the Nancy Grace Roman Space Telescope funded by NASA. The methods used to estimate the integration times are based upon peer reviewed research articles (see Bibliography) and a collection of instrumental and modeling parameters of both the Coronagraph Instrument and the Nancy Grace Roman Space Telescope. The code is written in python. Visit https://github.com/hsergi/Roman_Coronagraph_ETC for more information.

[ascl:2202.026] topoaccel: Topological acceleration scripts

topoaccel calculates topological acceleration for several of the S^3 quotient spaces considered 'regular', in that they have a Platonic solid as one of their fundamental domain shapes, and are globally homogeneous. The topoaccel scripts can be run using the free-licensed software package Maxima (https://maxima.sourceforge.io/documentation.html).

[ascl:2202.025] INSANE: INflationary potential Simulator and ANalysis Engine

INSANE (INflationary potential Simulator and ANalysis Engine) takes either a numeric inflationary potential or a symbolic one, calculates the background evolution and then, using the Mukhanov-Sasaki equations, calculates the primordial power spectrum it yields. The package can analyze the results to extract the spectral index n_s, the index running alpha, the running of running and possibly higher moments. The package contains two main modules: BackgroundSolver solves the background equations, and the MsSolver module solves and analyses the MS equations.

[ascl:2202.024] SunnyNet: Neural network framework for solving 3D NLTE radiative transfer in stellar atmospheres

SunnyNet learns the mapping the between LTE and NLTE populations of a model atom and predicts the NLTE populations based on LTE populations for an arbitrary 3D atmosphere. To use SunnyNet, one must already have a set of LTE and NLTE populations computed in 3D, to train the network. These must come from another code, as SunnyNet is unable to solve the formal problem. Once SunnyNet is trained, one can feed it LTE populations from a different 3D atmosphere, and obtain predicted NLTE populations. The NLTE populations can then be used to synthesize any spectral line that is included in the model atom. SunnyNet's output is a file with predicted NLTE populations. SunnyNet itself does not calculate synthetic spectra, but a sample script written in the Julia language that quickly computes Hα spectra is included.

[ascl:2202.023] Starduster: Radiative transfer and deep learning multi-wavelength SED model

The deep learning model Starduster emulates dust radiative transfer simulations, which significantly accelerates the computation of dust attenuation and emission. Starduster contains two specific generative models, which explicitly take into account the features of the dust attenuation curves and dust emission spectra. Both generative models should be trained by a set of characteristic outputs of a radiative transfer simulation. The obtained neural networks can produce realistic galaxy spectral energy distributions that satisfy the energy balance condition of dust attenuation and emission. Applications of Starduster include SED-fitting and SED-modeling from semi-analytic models.

[ascl:2202.022] ASPIRED: Automated SpectroPhotometric Image REDuction

ASPIRED reduces 2D spectral data from raw image to wavelength and flux calibrated 1D spectrum automatically without any user input (quicklook quality), and provides a set of easily configurable routines to build pipelines for long slit spectrographs on different telescopes (science quality). It delivers near real-time data reduction, which can facilitate automated or interactive decision making, allowing "on-the-fly" modification of observing strategies and rapid triggering of other facilities.

[ascl:2202.021] popsynth: Observed surveys from latent population models

Popsynth provides an abstract way to generate survey populations from arbitrary luminosity functions and redshift distributions. Additionally, auxiliary quantities can be sampled and stored. Populations can be saved and restored via an HDF5 files for later use, and population synthesis routines can be created via classes or structured YAML files. Users can construct their own classes for spatial, luminosity, and other distributions, all of which can be connected to arbitrarily complex selection functions.

[ascl:2202.020] distance-omnibus: Distance estimation method for molecular cloud clumps in the Milky Way

distance-omnibus computes posterior DPDFs for catalog sources using the Bayesian application of kinematic distance likelihoods derived from a Galactic rotation curve with prior Distance Probability Density Functions (DPDFs) derived from ancillary data. The methodology and code base are generalized for use with any (sub-)millimeter survey of the Galactic plane.

[ascl:2202.019] Contaminante: Identify blended targets in Kepler, TESS, and K2 data

contaminante helps find the contaminant transiting source in NASA's Kepler, K2 or TESS data. When hunting for transiting planets, sometimes signals come from neighboring contaminants. This package helps users identify where the transiting signal comes from in their data. The code uses pixel level modeling of the TargetPixelFile data from NASA's astrophysics missions that are processed with the Kepler pipeline. The output of contaminante is a Python dictionary containing the source location and transit depth, and a contaminant location and depth. It can also output a figure showing where the main target is centered in all available TPFs, what the phase curve looks like for the main target, where the transiting source is centered in all available TPFs, if a transiting source is located outside the main target, or the transiting source phase curve, if a transiting source is located outside the main target.

[ascl:2202.018] Sculptor: Interactive modeling of astronomical spectra

Sculptor manipulates, models and analyzes spectroscopic data; the code facilitates reproducible scientific results and easy to inspect model fits. A built-in graphical user interface around LMFIT (ascl:1606.014) offers interactive control to set up and combine multiple spectral models to fully fit the spectrum of choice. Alternatively, all core functionality can be scripted to facilitate the design of spectral fitting and analysis pipelines.

[ascl:2202.017] GALLUMI: GALaxy LUMInosity function pipeline

GALLUMI (GALaxy LUMInosity) is a likelihood code that extracts cosmological and astrophysical parameters from the UV galaxy luminosity function. The code is implemented in the MCMC sampler MontePython (ascl:1307.002) and can be readily run in conjunction with other likelihood codes.

[ascl:2202.016] Find_Orb: Orbit determination from observations

Find_Orb takes a set of observations of an asteroid, comet, or natural or artificial satellite given in the MPC (Minor Planet Center) format, the ADES astrometric format, and/or the NEODyS or AstDyS formats, and finds the corresponding orbit.

[ascl:2202.015] SPARTAN: SPectroscopic And photometRic fiTting tool for Astronomical aNalysis

SPARTAN fits the spectroscopy and photometry of distant galaxies. The code implements multiple interfaces to help in the configuration of the fitting and the inspection of the results. SPARTAN relies on pre-computed input files (such as stellar population and IGM extinction), available for download, to save time in the fitting process.

[submitted] Mean Motion Resonances

Site with collection of codes and fundamental references on mean motion resonances.

[ascl:2202.014] Citlalicue: Create and manipulate stellar light curves

Citlalicue allows you to create synthetic stellar light curves (transits, stellar variability and white noise) and detrend light curves using Gaussian Processes (GPs). Transits are implemented using PyTransit (ascl:1505.024). Python notebooks are provided to demonstrate using Citlalicue for both functions.

[ascl:2202.013] PSLS: PLATO Solar-like Light-curve Simulator

PSLS simulates solar-like oscillators representative of PLATO targets. It includes planetary transits, stochastically-excited oscillations, granulation and activity background components, as well as instrumental systematic errors and random noises representative for PLATO.

[ascl:2202.012] fiducial_flare: Spectra and lightcurves of a standardized far ultraviolet flare

fiducial_flare generates a reasonable approximation of the UV emission of M dwarf stars over a single flare or a series of them. The simulated radiation is resolved in both wavelength and time. The intent is to provide consistent input for applications requiring time-dependent stellar UV radiation fields that balances simplicity with realism, namely for simulations of exoplanet atmospheres.

[ascl:2202.011] RFEP: Residual Feature Extraction Pipeline

Residual Feature Extraction Pipeline carries out feature extraction of residual substructure within the residual images produced by popular galaxy structural-fitting routines such as GALFIT (ascl:1104.010) and GIM2D (ascl:1004.001). It extracts faint low surface brightness features by isolating flux-wise and area-wise significant contiguous pixels regions by rigorous masking routine. The code accepts the image cubes (original image, model image, residual image) and generates several data products, such as an image with extracted features, a source extraction based segmentation map, and the background sky mask and the residual extraction mask. It uses a Monte Carlo approach-based area threshold above which the extracted features are identified. The pipeline also creates a catalog entry indicating the surface brightness and its error.

[ascl:2202.010] EDIVU: Exoplanet Detection Identifier Vetter Unplugged

The EDI (Exoplanet Detection Identifier) Vetter Unplugged software identifies false positive transit signals using Transit Least Squares (TLS) information and has been simplified from the full EDI-Vetter algorithm (ascl:2202.009) for easy implementation with the TLS output.

[ascl:2202.009] EDIV: Exoplanet Detection Identifier Vetter

EDI (Exoplanet Detection Identifier) Vetter identifies false positive transit signal in the K2 data set. It combines the functionalities of Terra (ascl:2202.008) and RoboVetter (ascl:2012.006) and is optimized to test single transiting planet signals. An easily implemented suite of vetting metrics built to run alongside TLS of EDI Vetter, EDI-Vetter Unplugged (ascl:2202.010), is also available.

[ascl:2202.008] TERRA: Transit detection code

TERRA (Transiting Exoearth Robust Reduction Algorithm) identifies and removes instrumental noise in Kepler photometry. This transit detection code is optimized to detect small planets around photometrically quiet stars. TERRA calculates photometry in the time domain, combs the calibrated photometry for periodic, box-shaped signals, fits promising signals, and rejects signals inconsistent with exoplanet transits.

[ascl:2202.007] SciCatalog: Tools for scientific data catalogs

SciCatalog handles catalogs of scientific data in a way that is easily extensible, including the ability to create nicely formatted AASTex deluxe tables for use in AAS Publishing manuscripts. It handles catalogs of values, their positive and negative uncertainties, and references for those values with methods for easily adding columns and changing values. The catalog is also backed up every time it is loaded under the assumption that it is about to be modified.

[ascl:2202.006] FIRE Studio: Movie making utilities for the FIRE simulations

FIRE Studio is a Python interface for C libraries that project Smoothed Particle Hydrodynamic (SPH) datasets. These C libraries can, in principle, be applied to any SPH dataset; the Python interface is specialized to conveniently load and format Gadget-derivative datasets such as GIZMO (ascl:1410.003). FIRE Studio is fast, memory efficient, and parallelizable. In addition to producing "1-color" projection maps for SPH datasets, the interface can produce "2-color" maps, where the pixel saturation is set by one projected quantity and the hue is set by another, and "3-color" maps, where three quantities are projected simultaneously and remapped into an RGB colorspace. FIRE Studio can model stellar emission and dust extinction to produce mock Hubble images (by default) or to model surface brightness maps for thirteen of the most common bands (plus the bolometric luminosity). It produces publication quality static images of simulation datasets and provides interpolation scripts to create movies that smoothly evolve in time (provided multiple snapshots in time of the data exist), view the dataset from different perspectives (taking advantage of shared memory buffers to allow massive parallelization), or both.

[ascl:2202.005] palettable: Color palettes for Python

Palettable is a library of color palettes for Python. The code is written in pure Python with no dependencies; it can be used to supply color maps for matplotlib plots, customize matplotlib plots, and to supply colors for a web application.

[ascl:2202.004] SUPPNet: Spectrum normalization neural network

SUPPNet performs fully automated precise continuum normalization of merged echelle spectra and offers flexible manual fine-tuning, if necessary. The code uses a fully convolutional deep neural network (SUPP Network) trained to predict a pseudo-continuum. The post-processing step uses smoothing splines that give access to regressed knots, which are useful for optional manual corrections. The active learning technique controls possible biases that may arise from training with synthetic spectra and extends the applicability of the method to features absent in this kind of spectra.

[ascl:2202.003] Zwindstroom: Cosmological growth factors from fluid calculations

Zwindstroom computes background quantities and scale-dependent growth factors for cosmological models with free-streaming species, such as massive neutrinos. Following the earlier REPS code (ascl:1612.022), the code uses a Newtonian fluid approximation with external neutrino sound speed to close the Boltzmann hierarchy. Zwindstroom supports multi-fluid models with distinct transfer functions and sound speeds. A flexible python interface facilitates interaction with CLASS (ascl:1106.020) through classy. There is also a Zwindstroom plugin for the cosmological initial conditions generator monofonIC (ascl:2008.024) that allows for higher-order LPT ICs for massive neutrino simulations in a single step.

[ascl:2202.002] NWelch: Spectral analysis of time series with nonuniform observing cadence

NWelch uses Welch's method to estimate the power spectra, complex cross-spectrum, magnitude-squared coherence, and phase spectrum of bivariate time series with nonuniform observing cadence. For univariate time series, users can apply the Welch's power spectrum estimator or compute a nonuniform fast Fourier transform-based periodogram. Options include tapering in the time domain and computing bootstrap false alarm levels. Users may choose standard 50%-overlapping Welch's segments or apply a custom-made segmentation scheme. NWelch was designed for Doppler planet searches but may be applied to any type of time series.

[submitted] frbmclust: Model-independent classification of events from the first CHIME/FRB Fast Radio Burst catalog

CHIME/FRB instrument has recently published a catalog containing about half of thousand fast radio bursts (FRB) including their spectra and several reconstructed properties, like signal widths, amplitudes, etc. We have developed a model-independent approach for the classification of these bursts using cross-correlation and clustering algorithms applied to one-dimensional intensity profiles, i.e. to amplitudes as a function of time averaged over the frequency. This approach is implemented in frbmclust package, which is used for classification of bursts featuring different waveform morphology.

[ascl:2202.001] GA Galaxy: Interacting galaxies model fitter

GA Galaxy fits models of interacting galaxies to synthetic data using a genetic algorithm and custom fitness function. The genetic algorithm is real-coded and uses a mixed Gaussian kernel for mutation. The fitness function incorporates 1.) a direct pixel-to-pixel comparison between the target and model images and 2.) a comparison of the degree of tidal distortion present in the target and model image such that target-model pairs which are similarly distorted will have a higher relative fitness. The genetic algorithm is written in Python 2.7 while the simulation code (SPAM: Stellar Particle Animation Module) is written in Fortran 90.

[ascl:2201.014] nProFit: n-Profile Fitting tool

nProFit analyzes surface brightness profiles. It obtains the best-fit structural, scale, and shape parameters of star clusters in Hubble Space Telescope images of nearby galaxies. The code fits dynamical models and can derive physically-relevant parameters. Among these are central volume and luminosity densities, total masses and luminosities, central velocity dispersions, core radius, half-light radius, tidal radius, and binding energy.

[ascl:2201.013] disnht: Absorption spectrum solver

disnht computes the absorption spectrum for a user-defined distribution of column densities. The input is a file including the array of column density values; a python routine is provided that can make logarithmic distribution of column density that can be used as an input. Other optional inputs are a cross-section file that includes the 2-d array [energy, cross-section]; a script is provided for computing cross sections for different abundance model for the interstellar medium (solar values). Other boolean flags can be used for input and output description, rebin, plot or save.

[ascl:2201.012] MAGRATHEA: Planet interior structure code

MAGRATHEA solves planet interiors and considers the case of fully differentiated interiors. The code integrates the hydrostatic equation in order to determine the correct planet radius given the mass in each layer. The code returns the pressure, temperature, density, phase, and radius at steps of enclosed mass. The code support four layers: core, mantle, hydrosphere, and atmosphere. Each layer has a phase diagram with equations of state chosen for each phase.

[ascl:2201.011] COWS: Cosmic web filament finder

COWS (COsmic Web Skeleton) implements the cosmic filament finder COsmic Web Skeleton (COWS). Written in Python, the cosmic filament finder works on Hessian-based cosmic web identifiers (such as the V-web) and returns a catalogue of filament spines. The code identifies the medial axis, or skeleton, of cosmic web filaments and then separates this skeleton into individual filaments.

[ascl:2201.010] statmorph: Non-parametric morphological diagnostics of galaxy images

statmorph calculates non-parametric morphological diagnostics of galaxy images (e.g., Gini-M_{20} and CAS statistics), and fits 2D Sérsic profiles. Given a background-subtracted image and a corresponding segmentation map indicating the source(s) of interest, statmorph calculates the following morphological statistics for each source:
- Gini-M20 statistics;
- Concentration, Asymmetry and Smoothness (CAS) statistics;
- Multimode, Intensity and Deviation (MID) statistics;
- outer asymmetry and shape asymmetry;
- Sérsic index; and,
- several shape and size measurements associated to the above statistics, such as ellipticity, Petrosian radius, and half-light radius, among others.

[ascl:2201.009] AltaiPony: Flare finder for Kepler, K2, and TESS light curves

AltaiPony de-trend light curves from Kepler, K2, and TESS missions, and searches them for flares. The code also injects and recovers synthetic flares to account for de-trending and noise loss in flare energy and determines energy-dependent recovery probability for every flare candidate. AltaiPony uses K2SC (ascl:1605.012), AstroPy (ascl:1304.002) and lightkurve (ascl:1812.013) in addition to other common codes, and extensive documentation and tutorials are provided for the software.

[ascl:2201.008] fermi-gce-flows: Infer the Galactic Center gamma-ray excess

fermi-gce-flows uses a machine learning-based technique to characterize the contribution of modeled components, including unresolved point sources, to the GCE. It can perform posterior parameter estimation while accounting for pixel-to-pixel spatial correlations in the gamma-ray map. On application to Fermi data, the method generically attributes a smaller fraction of the GCE flux to unresolved point source-like emission when compared to traditional approaches.

[ascl:2201.007] tellrv: Radial velocities for low-resolution NIR spectra

tellrv measures absolute radial velocities for low-resolution NIR spectra. It uses telluric features to provide absolute wavelength calibration, and then cross-correlates with a standard star. Observations of a standard star are included for convenience; the code also requires both the telluric and non-telluric-corrected spectra.

[ascl:2201.006] dark-photons-perturbations: Dark photon conversions in our inhomogeneous Universe

dark-photons-perturbations determines constraints from Cosmic Microwave Background photons oscillating into dark photons, and from heating of the primordial plasma due to dark photon dark matter converting into low-energy photons in an inhomogeneous universe.

[ascl:2201.005] AllStarFit: R package for source detection, PSF and multi-component galaxy fitting

AllStarFit analyzes optical and infrared images and includes functions for:
- object detection and image segmentation using the ProFound package (ascl:1804.006);
- PSF determination using the ProFit package (ascl:1612.004) to fit multiple stars in the field simultaneously; and
- galaxy modelling with ProFit, using the previously determined PSF and user-specified models.

AllStarFit supports a variety of optimization methods (provided by external packages), including maximum-likelihood and Markov chain Monte Carlo (MCMC).

[ascl:2201.004] FitsMap: Interactive astronomical image and catalog data visualizer

FitsMap visualizes astronomical image and catalog data. Implemented in Python, the software is a simple, lightweight tool, requires only a simple web server, and can scale to over gigapixel images with tens of millions of sources. Further, the web-based visualizations can be viewed performantly on mobile devices.

[ascl:2201.003] BLOSMapping: Determine line-of-sight magnetic fields of molecular clouds

BLOSMapping determines the line-of-sight component of magnetic fields associated with molecular clouds. The code uses Faraday rotation measure catalogs along with an on-off approach based on relative measurements to estimate the rotation measure caused by molecular clouds. It then uses the outputs from a chemical evolution code along with extinction maps to determine the line-of-sight magnetic field strength and direction.

[ascl:2201.002] AstroToolBox: Java tools for identifying and classifying astronomical objects

AstroToolBox identifies and classifies astronomical objects with a focus on low-mass stars and ultra-cool dwarfs. It can search numerous catalogs, including SIMBAD (measurements & references), AllWISE, Gaia, SDSS, among others, evaluates spectral type for main sequence stars including brown dwarfs, and provides SED fitting for ultra-cool and white dwarfs. AstroToolBox draws Gaia color-magnitude diagrams (CMD) with overplotted M0-M9 spectral types, and can draw Montreal Cooling Sequences on the white dwarf branch of the Gaia CMD. The tool can also blink images from different epochs in an image viewer, thus allowing visual identification of the motion or variability of objects. The software displays time series (static or animated) using infrared and optical images of various surveys and contains a photometric classifier. It also includes astrometric calculators and converters, an ADQL query interface (IRSA, VizieR, NOAO) and a batch spectral type lookup feature that uses a CSV file with object coordinates as input. The ToolBox also has a file browser linked to the image viewer, which makes it possible to check a large list of objects in a convenient way, and can save interesting finds in an object collection for later use.

[ascl:2201.001] EzTao: Easier CARMA Modeling

EzTao models time series as a continuous-time autoregressive moving-average (CARMA) process. EzTao utilizes celerite (ascl:1709.008), a fast and scalable Gaussian Process Regression library, to evaluate the likelihood function. On average, EzTao is ten times faster than other tools relying on a Kalman filter for likelihood computation.

[ascl:2112.027] JexoSim 2.0: JWST Exoplanet Observation Simulator

JexoSim 2.0 (JWST Exoplanet Observation Simulator) simulates exoplanet transit observations using all four instruments of the James Webb Space Telescope, and is designed for the planning and validation of science cases for JWST. The code generates synthetic spectra that capture the full impact of complex noise sources and systematic trends, allowing for assessment of both accuracy and precision in the final spectrum. JexoSim does not contain all known systematics for the various instruments, but is a good starting point to investigate the effects of systematics, and has the framework to incorporate more systematics in the future.

[ascl:2112.026] HoloSim-ML: Analyzing radio holography measurements of complex optical systems

HoloSim-ML performs beam simulation and analysis of radio holography data from complex optical systems. The code uses machine learning to efficiently determine the position of hundreds of mirror adjusters on multiple mirrors with few micron accuracy.

[ascl:2112.025] FTP: Fast Template Periodogram

The Fast Template Periodogram extends the Generalised Lomb Scargle periodogram (Zechmeister and Kurster 2009) for arbitrary (periodic) signal shapes. A template is first approximated by a truncated Fourier series of length H. The Nonequispaced Fast Fourier Transform NFFT is used to efficiently compute frequency-dependent sums. Template fitting can now be done in NlogN time, improving existing algorithms by an order of magnitude for even small datasets. The FTP can be used in conjunction with gradient descent to accelerate a non-linear model fit, or be used in place of the multi-harmonic periodogram for non-sinusoidal signals with a priori known shapes.

[ascl:2112.024] l1p: Python implementation of the l1 periodogram

The l1 periodogram searches for periodicities in unevenly sampled time series. It can be used similarly as a Lomb-Scargle periodogram, and retrieves a figure which has a similar aspect but has fewer peaks due to aliasing. It is primarily designed for the search of exoplanets in radial velocity data, but can be also used for other purposes. The principle of the algorithm is to search for a representation of the input signal as a sum of a small number of sinusoidal components, that is a representation which is sparse in the frequency domain. Here, "small number" means small compared to the number of observations.

[ascl:2112.023] wpca: Weighted Principal Component Analysis in Python

wpca, written in Python, offers several implementations of Weighted Principal Component Analysis and uses an interface similar to scikit-learn's sklearn.decomposition.PCA. Implementations include a direct decomposition of a weighted covariance matrix to compute principal vectors, and then a weighted least squares optimization to compute principal components, and an iterative expectation-maximization approach to solve simultaneously for the principal vectors and principal components of weighted data. It also includes a standard non-weighted PCA implemented using the singular value decomposition, primarily to be useful for testing.

[ascl:2112.022] hankl: Python implementation of the FFTLog algorithm for cosmology

hankl implements the FFTLog algorithm in lightweight Python code. The FFTLog algorithm can be thought of as the Fast Fourier Transform (FFT) of a logarithmically spaced periodic sequence (= Hankel Transform). hankl consists of two modules, the General FFTLog module and the Cosmology one. The latter is suited for modern cosmological application and relies heavily on the former to perform the Hankel transforms. The accuracy of the method usually improves as the range of integration is enlarged; FFTlog prefers an interval that spans many orders of magnitude. Resolution is important, as low resolution introduces sharp features which in turn causes ringing.

[ascl:2112.021] GRIT: Gravitational Rigid-body InTegrators for simulating coupled dynamics

GRIT (Gravitational Rigid-body InTegrators) simulaties the coupled dynamics of both spin and orbit of N gravitationally interacting rigid bodies. The code supports tidal forces and general relativity correction are supported, and multiple schemes with different orders of convergences and splitting strategies are available. Multiscale splittings boost the simulation speed, and force evaluations can be parallelized. In addition, each body can be set to be a rigid body or just a point mass, and the floating-point format can be customized as float, double, or long double globally.

[ascl:2112.020] BayesicFitting: Model fitting and Bayesian evidence calculation package

BayesicFitting fits models to data. Data in this context means a set of (measured) points x and y. The model provides some (mathematical) relation between the x and y. Fitting adapts the model such that certain criteria are optimized. The BayesicFitting toolbox also determines whether one model fits the data better than another, making the toolbox particularly powerful. The package consists of more than 100 Python classes, of which one third are model classes. Another third are fitters in one guise or another along with additional tools, and the remaining third is used for Nested Sampling.

[ascl:2112.019] O'TRAIN: Optical TRAnsient Identification NEtwork

The O'TRAIN package identifies transients in astronomical images based on a Convolutional Neural Network (CNN). It works on images from different telescopes and, through the use of Docker, can be deployed on different operating systems. O'TRAIN uses image cutouts containing real and false transients provided by the user to train a CNN algorithm implemented with Keras. Built-in diagnostics help to characterize the accuracy of the training, and a trained model is used to classify any new cutouts.

[ascl:2112.018] Optab: Ideal-gas opacity tables generator

Optab, written in Fortran90, generates ideal-gas opacity tables. It computes opacity based on user-provided chemical equilibrium abundances, and outputs mean opacities as well as monochromatic opacities, thus providing opacity tables that are consistent with one's equation of state for radiation hydrodynamics simulations. For convenience, Optab also provides interfaces for FastChem (ascl:1804.025) or TEA (ascl:1505.031) for computing chemical abundances.

[ascl:2112.017] deeplenstronomy: Pipeline for versatile strong lens sample simulations

deeplenstronomy simulates large datasets for applying deep learning to strong gravitational lensing. It wraps the functionalities of lenstronomy (ascl:1804.012) in a convenient yaml-style interface to generate training datasets. The code can use built-in astronomical surveys, realistic galaxy colors, real images of galaxies, and physically motivated distributions of all parameters to train the neural network to create a simulated dataset.

[ascl:2112.016] TESSreduce: Transient focused reduction for TESS data

TESSreduce builds on lightkurve (ascl:1812.013) to reduce TESS data while preserving transient signals. It takes a TPF as input (supplied or constructed with TESScut (https://mast.stsci.edu/tesscut/). The background subtraction accounts for the smooth background and detector straps. In addition to background subtraction, TESSreduce also aligns images, performs difference imaging, detects transient events, and by using PS1 data, can calibrate TESS counts to physical flux or AB magnitudes.

[ascl:2112.015] SAPHIRES: Stellar Analysis in Python for HIgh REsolution Spectroscopy

The SAPHIRES (Stellar Analysis in Python for HIgh REsolution Spectroscopy) suite contains functions for analyzing high-resolution stellar spectra. Though most of its functionality is aimed at deriving radial velocities (RVs), the suite also includes capabilities to measure projected rotational velocities (vsini) and determine spectroscopic flux ratios in double-lined binary systems (SB2s). These measurements are made primarily by computing spectral-line broadening functions. More traditional techniques such as Fourier cross-correlation, and two-dimensional cross-correlation (TODCOR) are also included.

[ascl:2112.014] Qwind3: Modeling UV line-driven winds originating from accretion discs

Qwind3 models radiation-driven winds originating from accretion discs. An improvement over Qwind (ascl:2112.013), it derives the wind initial conditions and has significantly improved ray-tracing to calculate the wind absorption self consistently given the extended nature of the UV emission. It also corrects the radiation flux for relativistic effects, and assesses the impact of this on the wind velocity.

[ascl:2112.013] Qwind: Non-hydrodynamical model for AGN line-drive winds

Qwind simulates the launching and acceleration phase of line-driven winds in the context of AGN accretion discs. The wind is modeled as a set of streamlines originating on the surface of the AGN accretion disc, and evolved following their equation of motion, given by the balance between radiative and gravitational force.

[ascl:2112.012] DiracVsMajorana: Statistical discrimination of sub-GeV Majorana and Dirac dark matter

DiracVsMajorana determines the statistical significance with which a successful electron scattering experiment could reject the Majorana hypothesis -- that dark matter (DM) particles are their own anti-particles, a so-called Majorana fermion -- using the likelihood ratio test in favor of the hypothesis of Dirac DM. The code assumes that the DM interacts with the photon via higher-order electromagnetic moments. It requires tabulated atomic response functions, which can be computed with DarkARC (ascl:2112.011), to compute ionization spectra and predictions for signal event rates.

[ascl:2112.011] DarkARC: Dark Matter-induced Atomic Response Code

DarkARC computes and tabulates atomic response functions for direct sub-GeV dark matter (DM) searches. The tabulation of the atomic response functions is separated into two steps: 1.) the computation and tabulation of three radial integrals, and 2.) their combination into the response function tables. The computations are performed in parallel using the multiprocessing library.

[ascl:2112.010] WIMpy_NREFT: Dark Matter direct detection rates detector

WIMpy_NREFT (also known as WIMpy) calculates Dark Matter-Nucleus scattering rates in the framework of non-relativistic effective field theory (NREFT). It currently supports operators O1 to O11, as well as millicharged and magnetic dipole Dark Matter. It can be used to generate spectra for Xenon, Argon, Carbon, Germanium, Iodine and Fluorine targets. WIMpy_NREFT also includes functionality to calculate directional recoil spectra, as well as signals from coherent neutrino-nucleus scattering (including fluxes from the Sun, atmosphere and diffuse supernovae).

[ascl:2112.009] AsteroGaP: Asteroid Gaussian Processes

The Bayesian-based Gaussian Process model AsteroGaP (Asteroid Gaussian Processes) fits sparsely-sampled asteroid light curves. By utilizing a more flexible Gaussian Process framework for modeling asteroid light curves, it is able to represent light curves in a periodic but non-sinusoidal manner.

[ascl:2112.008] MISTTBORN: MCMC Interface for Synthesis of Transits, Tomography, Binaries, and Others of a Relevant Nature

MISTTBORN can simultaneously fit multiple types of data within an MCMC framework. It handles photometric transit/eclipse, radial velocity, Doppler tomographic, or individual line profile data, for an arbitrary number of datasets in an arbitrary number of photometric bands for an arbitrary number of planets and allows the use of Gaussian process regression to handle correlated noise in photometric or Doppler tomographic data. The code can include dilution due to a nearby unresolved star in the transit fits, and an additional line component due to another star or scattered sun/moonlight in Doppler tomographic or line profile fits. It can also be used for eclipsing binary fits, including a secondary eclipse and radial velocities for both stars. MISTTBORN produces diagnostic plots showing the data and best-fit models and the associated code MISTTBORNPLOTTER produces publication-quality plots and tables.

[ascl:2112.007] NeutrinoFog: Neutrino fog and floor for direct dark matter searches

NeutrinoFog calculates the neutrino floor based on the derivative of a hypothetical experimental discovery limit as a function of exposure, and leads to a neutrino floor that is only influenced by the systematic uncertainties on the neutrino flux normalizations.

[ascl:2112.006] STDPipe: Simple Transient Detection Pipeline

STDPipe is a set of Python routines for astrometry, photometry and transient detection related tasks, intended for quick and easy implementation of custom pipelines, as well as for interactive data analysis. It is implemented as a library of routines covering most common tasks and operates on standard Python objects, including NumPy arrays for images and Astropy (ascl:1304.002) tables for catalogs and object lists. The pipeline does not re-implement code already implemented in other Python packages; instead, it transparently wraps external codes, such as SExtractor (ascl:1010.064), SCAMP (ascl:1010.063), PSFEx (ascl:1301.001), HOTPANTS (ascl:1504.004), and Astrometry.Net (ascl:1208.001), that do not have their own Python interfaces. STDPipe operates on temporary files, keeping nothing after the run unless something is explicitly requested.

[ascl:2112.005] Interferopy: Analyzing datacubes from radio-to-submm observations

Interferopy analyzes datacubes from radio-to-submm observations. It provides a homogenous interface to common tasks, making it easy to go from reduced datacubes to essential measurements and publication-quality plots. Its core functionalities are widely applicable and have been successfully tested on (but are not limited to) ALMA, NOEMA, VLA and JCMT data.

[ascl:2112.004] Defringe: Fringe artifact correction

Defringe corrects fringe artifacts in near-infrared astronomical images taken with old generation CCD cameras. It essentially solves a robust PCA problem, masking out astrophysical sources, and models the contaminants as a linear superposition of (unknown) modes, with (unknown) projection coefficients. The problem uses nuclear norm regularization, which acts as a convex proxy for rank minimization. The code is written in python, using cupy for GPU acceleration, but will also work on CPUs.

[ascl:2112.003] SCORPIO: Sky COllector of galaxy Pairs and Image Output

The Python package SCORPIO retrieves images and associated data of galaxy pairs based on their position, facilitating visual analysis and data collation of multiple archetypal systems. The code ingests information from SDSS, 2MASS and WISE surveys based on the available bands and is designed for studies of galaxy pairs as natural laboratories of multiple astrophysical phenomena for, among other things, tidal force deformation of galaxies, pressure gradient induced star formation regions, and morphological transformation.

[ascl:2112.002] QUESTFIT: Fitter for mid-infrared galaxy spectra

QUESTFIT fit the Spitzer mid-infrared spectra of the QUEST (Quasar ULIRG and Evolution STudy) sample. It uses two PAH templates atop an extincted and absorbed continuum model to fit the mid-IR spectra of galaxies that are heavily-absorbed. It also fits AGN with silicate models. The current version of QUESTFIT is optimized for processing spectra from the CASSIS (Combined Atlas of Sources with Spitzer IRS Spectra) portal to produce PAH fluxes for heavily absorbed sources.

[ascl:2112.001] pycelp: Python package for Coronal Emission Line Polarization

pyCELP (aka "pi-KELP") calculates Coronal Emission Line Polarization. It forward synthesizes the polarized emission of ionized atoms formed in the solar corona and calculates the atomic density matrix elements for a single ion under coronal equilibrium conditions and excited by a prescribed radiation field and thermal collisions. pyCELP solves a set of statistical equilibrium equations in the spherical statistical tensor representation for a multi-level atom for the no-coherence case. This approximation is useful in the case of forbidden line emission by visible and infrared lines, such as Fe XIII 1074.7 nm and Si X 3934 nm.

[submitted] DIPol-UF: Remote control software for DIPol-UF polarimeter

DIPol-UF provides tools for remote control and operation of DIPol-UF, an optical (BVR) imaging CCD polarimeter. The project contains libraries that handle low-level interoperation with ANDOR SDK (provided by the CCD manufacturer), communication with stepper motors (which perform plate rotations), FITS file serialization/deserialization, over-network communication between different system components (each CCD is connected to a standalone PC), as well as provide GUI (built with WPF).

[submitted] forecaster-plus

An internally overhauled but fundamentally similar version of Forecaster by Jingjing Chen and David Kipping, originally presented in arXiv:1603.08614 and hosted at https://github.com/chenjj2/forecaster.

The model itself has not changed- no new data was included and the hyperparameter file was not regenerated. All functions were rewritten to take advantage of Numpy vectorization and some additional user features were added. Now able to be installed via pip.

[submitted] Caustic Mass Estimator for Galaxy Clusters

The caustic technique is a powerful method to infer cluster mass profiles to clustrocentric distances well beyond the virial radius. It relies in the measure of the escape velocity of the sistem using only galaxy redshift information. This method was introduced by Diaferio & Geller (1997) and Diaferio (1999). This code allows the caustic mass estimation for galaxy clusters, as well as outlier identification as a side effect. However, a pre-cleaning of interlopers is recommended, using e.g., the shifting-gapper technique.

[ascl:2111.018] GWToolbox: Gravitational wave observation simulator

GWToolbox simulates gravitational wave observations for various detectors. The package is composed of three modules, namely the ground-based detectors (and their targets), the space-borne detectors (and their targets) and pulsar timing arrays (PTA). These three modules work independently and have different dependencies on other packages and libraries; failed dependencies met in one module will not influence the usage of another module. GWToolbox can accessed with a web interface (gw-universe.org) or as a python package (https://bitbucket.org/radboudradiolab/gwtoolbox).

[ascl:2111.017] pySYD: Measuring global asteroseismic parameters

pySYD detects solar-like oscillations and measures global asteroseismic parameters. The code is a python-based implementation of the IDL-based SYD pipeline by Huber et al. (2009), which was extensively used to measure asteroseismic parameters for Kepler stars, and adapts the well-tested methodology from SYD and also improves these existing analyses. It also provides additional capabilities, including an automated best-fit background model selection, parallel processing, the ability to samples for further analyses, and an accessible and command-line friendly interface. PySYD provides best-fit values and uncertainties for the granulation background, frequency of maximum power, large frequency separation, and mean oscillation amplitudes.

[ascl:2111.016] SteParSyn: Stellar atmospheric parameters using the spectral synthesis method

SteParSyn infers stellar atmospheric parameters (Teff, log g, [Fe/H], and Vbroad) of FGKM-type stars using the spectral synthesis method. The code uses the MCMC sampler emcee (ascl:1303.002) in conjunction with an spectral emulator that can interpolate spectra down to a precision < 1%. A grid of synthetic spectra that allow the user to characterize the spectra of FGKM-type stars with parameters in the range of 3500 to 7000 K in Teff, 0.0 to 5.5 dex in log g, and −2.0 to 1.0 dex in [Fe/H] is also provided.

[ascl:2111.015] gCMCRT: 3D Monte Carlo Radiative Transfer for exoplanet atmospheres using GPUs

gCMCRT globally processes 3D atmospheric data, and as a fully 3D model, it avoids the biases and assumptions present when using 1D models to process 3D structures. It is well suited to performing the post-processing of large parameter GCM model grids, and provides simple pipelines that convert the 3D GCM structures from many well used GCMs in the community to the gCMCRT format, interpolating chemical abundances (if needed) and performing the required spectra calculation. The high-resolution spectra modes of gCMCRT provide an additional highly useful capability for 3D modellers to directly compare output to high-resolution spectral data.

[ascl:2111.014] UniMAP: Unicorn Multi-window Anomaly Detection Pipeline

The data analysis UniMAP (Unicorn Multi-window Anomaly Detection Pipeline) leverages the Temporal Outlier Factor (TOF) method to find anomalies in LVC data. The pipeline requires a target detector and a start and stop GPS time describing a time interval to analyze, and has three outputs: 1.) an array of GPS times corresponding to TOF detections; 2.) a long q-transform of the entire data interval with visualizations of the TOF detections in the time series; and 3.) q-transforms of the data windows that triggered TOF detections.

[ascl:2111.013] Astrosat: Satellite transit calculator

Astrosat calculates which satellites can be seen by a given observer in a given field of view at a given observation time and observation duration. This includes the geometry of the satellite and observer but also estimates the expected apparent brightness of the satellite to aid astronomers in assessing the impact on their observations.

[ascl:2111.012] flatstar: Make 2d intensity maps of limb-darkened stars

flatstar is an open-source Python tool for drawing stellar disks as numpy.ndarray objects with scientifically-rigorous limb darkening. Each pixel has an accurate fractional intensity in relation to the total stellar intensity of 1.0. It is ideal for ray-tracing simulations of stars and planetary transits. The code is fast, has the most well-known limb-darkening laws, including linear, quadratic, square-root, logarithmic, and exponential, and allows the user to implement custom limb-darkening laws. flatstar also offers supersampling for situations where both coarse arrays and precision in stellar disk intensity (i.e., no hard pixel boundaries) is desired, and upscaling to save on computation time when high-resolution intensity maps are needed, though there is some precision loss in intensities.

[ascl:2111.011] p-winds: Python implementation of Parker wind models for planetary atmospheres

p-winds produces simplified, 1-D models of the upper atmosphere of a planet and performs radiative transfer to calculate observable spectral signatures. The scalable implementation of 1D models allows for atmospheric retrievals to calculate atmospheric escape rates and temperatures. In addition, the modular implementation allows for a smooth plugging-in of more complex descriptions to forward model their corresponding spectral signatures (e.g., self-consistent or 3D models).

[ascl:2111.010] Nii: Multidimensional posterior distributions framework

Nii implements an automatic parallel tempering Markov chain Monte Carlo (APT-MCMC) framework for sampling multidimensional posterior distributions and provides an observation simulation platform for the differential astrometric measurement of exoplanets. Although this code specifically focuses on the orbital parameter retrieval problem of differential astrometry, Nii can be applied to other scientific problems with different posterior distributions and offers many control parameters in the APT part to facilitate the adjustment of the MCMC sampling strategy; these include the number of parallel chains, the β values of different chains, the dynamic range of the sampling step sizes, and frequency of adjusting the step sizes.

[ascl:2111.009] CoLoRe: Cosmological Lofty Realization

CoLoRe (Cosmological Lofty Realization) generates fast mock realizations of a given galaxy sample using a lognormal model or LPT for the matter density. Tt can simulate a variety of cosmological tracers, including photometric and spectroscopic galaxies, weak lensing, and intensity mapping. CoLoRe is a parallel C code, and its behavior is controlled primarily by the input param file.

[ascl:2111.008] COCOPLOT: COlor COllapsed PLOTting software

The COCOPLOT (COlor COllapsed PLOTting) quick-look and context image code conveys spectral profile information from all of the spatial pixels in a 3D datacube as a single image using color. It can also identify and expose temporal behavior and display and highlight solar features. COCOPLOT thus aids in identifying regions of interest quickly. The software is available in Python and IDL, and can be used as a standalone package or integrated into other software.

[ascl:2111.007] LEGWORK: LISA Evolution and Gravitational Wave ORbit Kit

LEGWORK (LISA Evolution and Gravitational Wave ORbit Kit) is a simple package for gravitational wave calculations. It evolves binaries and computes signal-to-noise ratios for binary systems potentially observable with LISA; it also visualizes the results. LEGWORK can also compare different detector sensitivity curves, compute the horizon distance for a collection of sources, and tracks signal-to-noise evolution over time.

[ascl:2111.006] prose: FITS images processing pipeline

prose provides pipelines for performing common tasks, such as automated calibration, reduction and photometry, and makes building custom pipelines easy. The prose framework is instrument-agnostic and makes constructing pipelines easy. It offers a wide range of implemented building blocks and also allows users to define their own.

[ascl:2111.005] CEvNS: Calculate Coherent Elastic Neutrino-Nucleus Scattering cross sections and recoil spectra

CEvNS calculates Coherent Elastic Neutrino-Nucleus Scattering (CEvNS) cross sections and recoil spectra. It includes (among other things) the Standard Model contribution to the CEvNS cross section, along with the contribution from Simplified Models with new vector or scalar mediators. It also covers neutrino magnetic moments and non-standard contact neutrino interactions (NSI).

[ascl:2111.004] NLopt: Nonlinear optimization library

The library NLopt performs nonlinear local and global optimization for functions with and without gradient information. It provides a simple, unified interface and wraps many algorithms for global and local, constrained or unconstrained, optimization, and provides interfaces for many other languages, including C++, Fortran, Python, Matlab or GNU Octave, OCaml, GNU Guile, GNU R, Lua, Rust, and Julia.

[ascl:2111.003] PSwarm: Global optimization solver for bound and linear constrained problems

PSwarm is a global optimization solver for bound and linear constrained problems (for which the derivatives of the objective function are unavailable, inaccurate or expensive). The algorithm combines pattern search and particle swarm. Basically, it applies a directional direct search in the poll step (coordinate search in the pure simple bounds case) and particle swarm in the search step. PSwarm makes no use of derivative information of the objective function. It has been shown to be efficient and robust for smooth and nonsmooth problems, both in serial and in parallel.

[ascl:2111.002] JAX: Autograd and XLA

JAX brings Autograd and XLA together for high-performance machine learning research. It can automatically differentiate native Python and NumPy functions. The code can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. JAX supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order.

[ascl:2111.001] astroDDPM: Realistic galaxy simulation via score-based generative models

astroDDPM uses a denoising diffusion probabilistic model (DDPM) to synthesize galaxies that are qualitatively and physically indistinguishable from the real thing. The similarity of the synthesized images to real galaxies from the Photometry and Rotation curve OBservations from Extragalactic Surveys (PROBES) sample and from the Sloan Digital Sky Survey is quantified using the Fréchet Inception Distance to test for subjective and morphological similarity. The emergent physical properties (such as total magnitude, color, and half light radius) of a ground truth parent and synthesized child dataset are also compared to generate a Synthetic Galaxy Distance metric. The DDPM approach produces sharper and more realistic images than other generative methods such as Adversarial Networks (with the downside of more costly inference), and could be used to produce large samples of synthetic observations tailored to a specific imaging survey. Potential uses of the DDPM include accurate in-painting of occluded data, such as satellite trails, and domain transfer, where new input images can be processed to mimic the properties of the DDPM training set.

[submitted] Data modelling approaches to astronomical data - Mapping large spectral line data cubes to dimensional data models

As a new generation of large-scale telescopes are expected to produce single data products in the range of hundreds of GBs to multiple TBs, different approaches to I/O efficient data interaction and extraction need to be investigated and made available to researchers. This will become increasingly important as the downloading and distribution of TB scale data products will become unsustainable, and researchers will have to take their processing analysis to the data. We present a methodology to extract 3 dimensional spatial-spectral data from dimensionally modelled tables in Parquet format on a Hadoop system. The data is loaded into the Parquet tables from FITS cube files using a dedicated process. We compare the performance of extracting data using the Apache Spark parallel compute framework on top of the Parquet-Hadoop ecosystem with data extraction from the original source files on a shared file system. We have found that the Spark-Parquet-Hadoop solution provides significant performance benefits, particularly in a multi user environment. We present a detailed analysis of the single and multi-user experiments conducted and also discuss the benefits and limitations of the platform used for this study.

[ascl:2110.022] XookSuut: Model circular and noncircular flows on 2D velocity maps

XookSuut models circular and noncircular flows on resolved velocity maps. The code performs nonparametric fits to derive kinematic models without assuming analytical functions on the different velocity components of the models. It recovers the circular and radial motions in galaxies in dynamical equilibrium and can derive the noncircular motions induced by oval distortions, such as that produced by stellar bars. XookSuut explores the full space of parameters on a N-dimensional space to derive their mean values; this combined method efficiently recovers the constant parameters and the different kinematic components.

[ascl:2110.021] PT-REX: Point-to-point TRend EXtractor

PT-REX (Point-to-point TRend EXtractor) performs ptp analysis on every kind of extended radio source. The code exploits a set of different fitting methods to allow study of the spatial correlation, and is structured in a series of tasks to handle the individual steps of a ptp analysis independently, from defining a grid to sample the radio emission to accurately analyzing the data using several statistical methods. A major feature of PT-REX is the use of an automatic, randomly-generated sampling routine to combine several SMptp analysis into a Monte Carlo ptp (MCptp) analysis. By repeating several cycles of SMptp analysis with randomly-generated grids, PT-REX produces a distribution of values of k that describe its parameter space, thus allowing a reliably estimate of the trend (and its uncertainties).

[ascl:2110.020] BCES: Linear regression for data with measurement errors and intrinsic scatter

BCES performs robust linear regression on (X,Y) data points where both X and Y have measurement errors. The fitting method is the bivariate correlated errors and intrinsic scatter (BCES). Some of the advantages of BCES regression compared to ordinary least squares fitting are that it allows for measurement errors on both variables and permits the measurement errors for the two variables to be dependent. Further it permits the magnitudes of the measurement errors to depend on the measurements and other lines such as the bisector and the orthogonal regression can be constructed.

[ascl:2110.019] SELCIE: Screening Equations Linearly Constructed and Iteratively Evaluated

SELCIE (Screening Equations Linearly Constructed and Iteratively Evaluated) investigates the chameleon model that arises from screening a scalar field introduced in some modified gravity models that is coupled to matter. The code provides tools to construct user defined meshes by utilizing the GMSH mesh generation software. These tools include constructing shapes whose boundaries are defined by some function or by constructing it out of basis shapes such as circles, cones and cylinders. The mesh can also be separated into subdomains, each of which having its own refinement parameters. These meshes can then be converted into a format that is compatible with the finite element software FEniCS. SELCIE uses FEniCS (ascl:2110.018) with a nonlinear solving method (Picard or Newton method) to solve the chameleon equation of motion for some parameters and density distribution. These density distributions are constructed by having the density profile of each subdomain being set by a user defined function, allowing for extremely customizable setups that are easy to implement.

[ascl:2110.018] FEniCS: Computing platform for solving partial differential equations

FEniCS solves partial differential equations (PDEs) and enables users to quickly translate scientific models into efficient finite element code. With the high-level Python and C++ interfaces to FEniCS, it is easy to get started, but FEniCS offers also powerful capabilities for more experienced programmers. FEniCS runs on a multitude of platforms ranging from laptops to high-performance clusters, and each component of the FEniCS platform has been fundamentally designed for parallel processing. This framework allows for rapid prototyping of finite element formulations and solvers on laptops and workstations, and the same code may then be deployed on large high-performance computers.

[ascl:2110.017] ThERESA: 3D Exoplanet Cartography

ThERESA retrieves three-dimensional maps of exoplanets. The code constructs 2-dimensional maps for each light given light curve, places those maps vertically in an atmosphere, and runs radiative transfer to calculate emission from the planet over a latitude/longitude grid. ThERESA then integrates over the grid (combined with the visibility function) to generate light curves. These light curves are compared against the input light curves behind MCMC to explore parameter space.

[ascl:2110.016] pyro: Deep universal probabilistic programming with Python and PyTorch

Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. It can represent any computable probability distribution and scales to large data sets with little overhead compared to hand-written code. The library is implemented with a small core of powerful, composable abstractions. Its high-level abstractions express generative and inference models, but also allows experts to customize inference.

[ascl:2110.015] Flux: Julia machine learning library

Flux provides an elegant approach to machine learning. Written in Julia, it provides lightweight abstractions on top of Julia's native GPU and AD support. It has many useful tools built in, but also lets you use the full power of the Julia language where you need it. Flux has relatively few explicit APIs for features like regularization or embeddings; instead, writing down the mathematical form works and is fast. The package works well with Julia libraries from data frames and images to differential equation solvers, so building complex data processing pipelines that integrate Flux models is straightforward.

[ascl:2110.014] swordfish: Information yield of counting experiments

Swordfish studies the information yield of counting experiments. It implements at its core a rather general version of a Poisson point process with background uncertainties described by a Gaussian random field, and provides easy access to its information geometrical properties. Based on this information, a number of common and less common tasks can be performed. Swordfish allows quick and accurate forecasts of experimental sensitivities without time-intensive Monte Carlos, mock data generation and likelihood maximization. It can:

- calculate the expected upper limit or discovery reach of an instrument;
- derive expected confidence contours for parameter reconstruction;
- visualize confidence contours as well as the underlying information metric field;
- calculate the information flux, an effective signal-to-noise ratio that accounts for background systematics and component degeneracies; and
- calculate the Euclideanized signal which approximately maps the signal to a new vector which can be used to calculate the Euclidean distance between points.

[ascl:2110.013] Nauyaca: N-body approach for determining planetary masses and orbital elements

Nauyaca infers planetary masses and orbits from mid-transit times fitting. The code requires transit ephemeris per planet and stellar mass and radius, and uses minimization routines and a Markov chain Monte Carlo method to find planet parameters that best reproduce the transit times based on numerical simulations. The code package provides customized plotting tools for analyzing the results.

[ascl:2110.012] GGCHEMPY: Gas-Grain CHEMical code for interstellar medium in Python3

GGCHEMPY is efficient for building 1-D, 2-D and 3-D simulations of physical parameters of Planck galactic cold clumps; it provides a graphical user interface and can also be invoked by a Python script. The code initializes the reaction network using input parameters, and then computes the reaction rate coefficients for all reactions. It uses the backward-differentiation formulas method to solve the ordinary differential equations for the integration. The modeled results are saved and can be directly passed to a Python dictionary for analysis and plotting.

[ascl:2110.011] GRASS: GRanulation and Spectrum Simulator

The Julia library GRASS produces realistic stellar spectra with time-variable granulation signatures. It is based on real observations of the Sun, and does not rely on magnetohydrodynamic simulations to produce its spectra. GRASS can also compute bisectors for absorption lines or CCF profiles, and provides two methods for calculating bisectors.

[ascl:2110.010] BASTA: BAyesian STellar Algorithm

BASTA determines properties of stars using a pre-computed grid of stellar models. It calculates the probability density function of a given stellar property based on a set of observational constraints defined by the user. BASTA is very versatile and has been used in a large variety of studies requiring robust determination of fundamental stellar properties.

[ascl:2110.009] Quokka: Two-moment AMR radiation hydrodynamics on GPUs for astrophysics

Quokka is a two-moment radiation hydrodynamics code that uses the piecewise-parabolic method, with AMR and subcycling in time. It runs on CPUs (MPI+vectorized) or NVIDIA GPUs (MPI+CUDA) with a single-source codebase. The hydrodynamics solver is an unsplit method, using the piecewise parabolic method for reconstruction in the primitive variables, the HLLC Riemann solver for flux computations, and a method-of-lines formulation for the time integration. The order of reconstruction is reduced in zones where shocks are detected in order to suppress spurious oscillations in strong shocks. Quokka's radiation hydrodynamics formulation is based on the mixed-frame moment equations. The radiation subsystem is coupled to the hydrodynamic subsystem via operator splitting, with the hydrodynamic update computed first, followed by the radiation update, with the latter update including the source terms corresponding to the radiation four-force applied to both the radiation and hydrodynamic variables. A method-of-lines formulation is also used for the time integration, with the time integration done by the same integrator chosen for the hydrodynamic subsystem.

[ascl:2110.008] ParSNIP: Parametrization of SuperNova Intrinsic Properties

ParSNIP learns generative models of transient light curves from a large dataset of transient light curves. It is designed to work with light curves in sncosmo format using the lcdata package to handle large datasets. This code can be used for classification of transients, cosmological distance estimation, and identifying novel transients.

[ascl:2110.007] PISCOLA: Python for Intelligent Supernova-COsmology Light-curve Analysis

PISCOLA (Python for Intelligent Supernova-COsmology Light-curve Analysis) fits supernova light curves and corrects them in a few lines of code. It uses Gaussian Processes to estimate rest-frame light curves of transients without needing an underlying light-curve template. The user can add filters, calculates the light-curves parameters, and obtain transmission functions for the observed filters and the Bessell filters. The correction process can be applied with default settings to obtain restframe light curves and light-curve parameters. PISCOLA can plot the SN light curves, filter transmission functions, light-curves fits results, the mangling function for a given phase, and includes several utilities that can, for example, convert fluxes to magnitudes and magnitudes to fluxes, and trim leading and trailing zeros from a 1-D array or sequence.

[ascl:2110.006] ArtPop: Artificial Stellar Populations generator

ArtPop (Artificial Stellar Populations) synthesizes stellar populations and simulates realistic images of stellar systems. The code is modular, making it possible to use each of its functionalities independently or together. ArtPop can build stellar populations independently from generating mock images, as one might want to do when interested only in calculating integrated photometric properties of the population. The code can also generate stellar magnitudes and artificial galaxies, which can be inject into real imaging data.

[ascl:2110.005] TauRunner: Code to propagate tau neutrinos at very high energies

TauRunner propagates ultra-high-energy neutrinos, with a focus on tau neutrinos. Although it was developed for extremely high energy (EeV+) applications, it is able to propagate neutrinos from 1 to 10^16 GeV. Oscillations are not taken into account at the lowest energies, but they become negligible above 1 TeV.

[ascl:2110.004] TULIPS: Tool for Understanding the Lives, Interiors, and Physics of Stars

TULIPS (Tool for Understanding the Lives, Interiors, and Physics of Stars) creates diagrams of the structure and evolution of stars. It creates plots and movies based on output from the MESA stellar evolution code (ascl:1010.083). TULIPS represents stars as circles of varying size and color. The code can also visualize the size and perceived color of stars, their interior mixing and nuclear burning processes, their chemical composition, and can compare different MESA models.

[ascl:2110.003] PSRDADA: Distributed Acquisition and Data Analysis for Radio Astronomy

PSRDADA supports the development of distributed data acquisition and analysis systems; it provides a flexible and well-managed ring buffer in shared memory with a variety of applications for piping data from device to ring buffer and from ring buffer to device. PSRDADA allows more than one data set to be queued in the ring buffer at one time, and data may be recorded in selected bursts using data validity flags. A variety of clients have been implemented that can write data to the ring buffer and read data from it. The primary write clients can be controlled via a simple, text-based socket interface, and read client software exists for writing data to an array of disks, sending data to an array of nodes, or processing the data directly from RAM. At the highest level of control and configuration, scripts launch the PSRDADA configuration across all nodes in the cluster, monitor all relevant processes, configure and control through a web-based interface, interface with observatory scheduling tools, and manage the ownership and archival of project data. It has been used in the implementation of baseband recording and processing instrumentation for radio pulsar astronomy.

[ascl:2110.002] exodetbox: Finding planet-star projected separation extrema and difference in magnitude extrema

Exodetbox provides mathematical methods for calculating the planet-star separation and difference in magnitude extrema as well as when planets have particular planet-star separations or differences in magnitude. The code also projects the 3D Keplerian Orbit into a reparameterized 2D ellipse in the plane of the sky. Exodetbox is implemented in the EXOSIMS modeling software (ascl:1706.010).

[ascl:2110.001] JWSTSim: Geometric-Focused JWST Deep Field Image Simulation

JWST_Simulation generates a novel geometric-focused deep field simulation of the expected JWST future deep field image. Galaxies are represented by ellipses with randomly-generated positions and orientations. Three scripts are included: a deterministic simulation, an ensemble simulation, and a more-realistic monochrome image simulation. The following initial conditions can be perturbed in these codes: H0, Ωm, ΩΛ, the dark energy equation of state parameter, the number of unseen galaxies in the Hubble Ultra Deep Field Image (HUDF), the increase in effective radius due to the JWST’s higher sensitivity, the anisotropy of dark energy, and the maximum redshift reached by the JWST. Galaxy number densities are estimated using integration over comoving volume with an integration constant calibrated with the Hubble Ultra Deep Field. A galaxy coverage percentage is calculated for each image to determine the percentage of the background occupied by galaxies.

[ascl:2109.030] Snowball: Generalizable atmospheric mass loss calculator

Snowball models atmospheric loss in order to constrain an atmosphere's cumulative impact of historic X-ray and extreme ultraviolet radiation-driven mass loss. The escape model interpolates the BaSTI luminosity evolution grid to the observed mass and luminosity of the host star.

[ascl:2109.029] BiPoS1: Dynamical processing of the initial binary star population

BiPoS1 (Binary Population Synthesizer) efficiently calculates binary distribution functions after the dynamical processing of a realistic population of binary stars during the first few Myr in the hosting embedded star cluster. It is particularly useful for generating a realistic birth binary population as an input for N-body simulations of globular clusters. Instead of time-consuming N-body simulations, BiPoS1 uses the stellar dynamical operator, which determines the fraction of surviving binaries depending on the binding energy of the binaries. The stellar dynamical operator depends on the initial star cluster density, as well as the time until the residual gas of the star cluster is expelled. At the time of gas expulsion, the dynamical processing of the binary population is assumed to effectively end due to the expansion of the star cluster related to that event. BiPoS1 has also a galactic-field mode, in order to synthesize the stellar population of a whole galaxy.

[ascl:2109.028] Healpix.jl: Julia-only port of the HEALPix library

Healpix.jl is a Julia-only port of the C/C++/Fortran/Python HEALPix library (ascl:1107.018), which implements a hierarchical pixelization of the sphere in equal-area pixels. Much like the original library, Healpix.jl supports two enumeration schemes for the pixels (RING and NESTED) and implements an optimized computation of the generalized Fourier transform using spherical harmonics, binding libsharp2 (ascl:1402.033). In addition, Healpix.jl provides four additional features: 1.) it fully supports Windows systems, alongside the usual Linux and MAC OS X machines; 2.) it uses Julia's strong typesystem to prevent several bugs related to mismatches in map ordering (e.g., combining a RING map with a NESTED map); 3.) it uses a versatile memory layout so that map bytes can be stored in shared memory objects or on GPUs; and 4.) it implements an elegant and general way to signal missing values in maps.

[ascl:2109.027] OSPREI: Sun-to-Earth (or satellite) CME simulator

OSPREI simulates the Sun-to-Earth (or satellite) behavior of CMEs. It is comprised of three separate models: ForeCAT, ANTEATR, and FIDO. ForeCAT uses the PFSS background to determine the external magnetic forces on a CME; ANTEATR takes the ForeCAT CME and propagates it to the final satellite distance, and outputs the final CME speed (both propagation and expansion), size, and shape (and their profiles with distance) as well as the arrival time and internal thermal and magnetic properties of the CME. FIDO takes the evolved CME from ANTEATR with the position and orientation from ForeCAT and passes the CME over a synthetic spacecraft. The relative location of the spacecraft within the CME determines the in situ magnetic field vector and velocity. It also calculates the Kp index from these values. OSPREI includes tools for creating figures from the results, including histograms, contour plots, and ensemble correlation plots, and new figures can be created using the results object that contains all the simulation data in an easily accessible format.

[ascl:2109.026] Varstar Detect: Variable star detection in TESS data

Varstar Detect uses several numerical and statistical methods to filter and interpret the data obtained from TESS. It performs an amplitude test to determine whether a star is variable and if so, provides the characteristics of each star through phenomenological analysis of the lightcurve.

[ascl:2109.025] Menura: Multi-GPU numerical model for space plasma simulation

Menura simulates the interaction between a fully turbulent solar wind and various bodies of the solar system using a novel two-step approach. It is an advanced numerical tool for self-consistent modeling that bridges planetary science and plasma physics. Menura is built around a hybrid Particle-In-Cell solver, treating electrons as a charge-neutralising fluid, and ions as massive particles. It solves iteratively the particles’ dynamics, gathers particle moments at the nodes of a grid, at which the magnetic field is also computed, and then solves the Maxwell equations. This solver uses the popular Current Advance Method (CAM).

[ascl:2109.024] BHJet: Semi-analytical black hole jet model

BHJet models steady-state SEDs of jets launched from accreting black holes. This semi-analytical, multi-zone jet model is applicable across the entire black hole mass scale, from black hole X-ray binaries (both low and high mass) to active galactic nuclei of any class (from low-luminosity AGN to flat spectrum radio quasars). It is designed to be more comparable than other codes to GRMHD simulations and/or RMHD semi-analytical solutions.

[ascl:2109.023] gphist: Cosmological expansion history inference using Gaussian processes

gphist performs Bayesian inference on the cosmological expansion history using Gaussian process priors. It is written in Python and includes driver programs to run inference calculations and plot the results. The code infers the cosmological expansion history using a Gaussian process prior, reads these ouputs, and performs checks to ensure they are indeed compatible. gphist then generates a single combined output file to plot expansion history inferences.

[ascl:2109.022] ShapeMeasurementFisherFormalism: Fisher Formalism for Weak Lensing

ShapeMeasurementFisherFormalism is used to study Fisher Formalism predictions on galaxy weak lensing for LSST Dark Energy Science Collaboration. It can create predictions with user-defined parameters for one or two galaxies simulated from GalSim (ascl:1402.009).

[ascl:2109.021] WeakLensingDeblending: Weak lensing fast simulations and analysis of blended objects

WeakLensingDeblending provides weak lensing fast simulations and analysis for the LSST Dark Energy Science Collaboration. It is used to study the effects of overlapping sources on shear estimation, photometric redshift algorithms, and deblending algorithms. Users can run their own simulations (of LSST and other surveys) or download the galaxy catalog and simulation outputs to use with their own code.

[ascl:2109.020] SNEWPY: Supernova Neutrino Early Warning Models for Python

SNEWPY uses simulated supernovae data to generate a time series of neutrino spectral fluences at Earth or the total time-integrated spectral fluence. The code can also process generated data through SNOwGLoBES (ascl:2109.019) and collate its output into the observable channels of each detector. Data from core-collapse, thermonuclear, and pair-instability supernovae simulations are included in the package.

[ascl:2109.019] SNOwGLoBES: SuperNova Observatories with GLoBES

SNOwGLoBES (SuperNova Observatories with GLoBES) computes interaction rates and distributions of observed quantities for supernova burst neutrinos in common detector materials. The code provides a very simple and fast code and data package for tests of observability of physics signatures in current and future detectors, and for evaluation of relative sensitivities of different detector configurations. The event estimates are made using available cross-sections and parameterized detector responses. Water, argon, scintillator and lead-based configurations are included. The package makes use of GLoBES (ascl:2109.018). SNOwGLoBES is not intended to replace full detector simulations; however output should be useful for many types of studies, and simulation results can be incorporated.

[ascl:2109.018] GLoBES: General Long Baseline Experiment Simulator

GLoBES simulates long baseline neutrino oscillation experiments. The package features full incorporation of correlations and degeneracies in the oscillation parameter space, advanced routines for the treatment of arbitrary systematical errors, and user-defined priors, which allowsn for the inclusion of arbitrary external physical information. Its use of AEDL, the Abstract Experiment Definition Language, provides an easy way to define experimental setups. GLoBES also provides an interface for the simulation of non-standard physics, and offers predefined setups for many experiments, including Superbeams, Beta Beams, Neutrino factories, Reactors, and various detector technologies.

[ascl:2109.017] HTOF: Astrometric solutions for Hipparcos and Gaia intermediate data

HTOF parses the intermediate data from Hipparcos and Gaia and fits astrometric solutions to those data. It computes likelihoods and parameter errors in line with the catalog and can reproduce five, seven, and nine (or higher) parameter fits to their astrometry.

[ascl:2109.016] SkyPy: Simulating the astrophysical sky

SkyPy simulates the astrophysical sky. It provides functions that sample realizations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models, while task scheduling and data dependencies are handled internally. The package's modular design, containing a library of physical and empirical models across a range of observables and a command line script to run end-to-end simulations, allows users to interface with external software.

[ascl:2109.015] unpopular: Using CPM detrending to obtain TESS light curves

unpopular is an implementation of the Causal Pixel Model (CPM) de-trending method to obtain TESS Full-Frame Image (FFI) light curves. The code, written in Python, models the systematics in the light curves of individual pixels as a linear combination of light curves from many other distant pixels and removes shared flux variations. unpopular is able to preserve sector-length astrophysical signals, allowing for the extraction of multi-sector light curves from the FFI data.

[ascl:2109.014] HSS: The Hough Stream Spotter

The Hough Stream Spotter (HSS) is a stream finding code which transforms individual positions of stars to search for linear structure in discrete data sets. The code requires only the two-dimensional plane of galactic longitude and latitude as input.

[ascl:2109.013] WimPyDD: WIMP direct–detection rates predictor

WimPyDD calculates accurate predictions for the expected rates in WIMP direct–detection experiments within the framework of Galilean–invariant non–relativistic effective theory. The object–oriented customizable Python code handles different scenarios including inelastic scattering, WIMP of arbitrary spin, and a generic velocity distribution of WIMP in the Galactic halo.

[ascl:2109.012] STAR-MELT: STellar AccrRetion Mapping with Emission Line Tomography

STAR-MELT extracts and identifies emission lines from FITS files by matching to a compiled reference database of lines. Line profiles are fitted and quantified, allowing for calculations of physical properties across each individual observation. Temporal variations in lines can readily be displayed and quantified. STAR-MELT is also useful for different applications of spectral analysis where emission line identification is required. Standard data formats for spectra are automatically compatible, with user-defined custom formats also available. Any reference database (atomic or molecular) can also be used for line identification.

[ascl:2109.011] Rubble: Simulating dust size distributions in protoplanetary disks

Rubble implicitly models the local evolution of dust distributions in size, mass, and surface density by solving the Smoluchowski equation (also known as the coagulation-fragmentation equation) under given disk conditions. The Python package's robustness has been validated by a suite of numerical benchmarks against known analytical and empirical results. Rubble can model prescribed physical processes such as bouncing, modulated mass transfer, regulated dust loss/supply, probabilistic collisional outcomes based on velocity distributions, and more. The package also includes a toolkit for analyzing and visualizing results produced by Rubble.

[ascl:2109.010] Frankenstein: Flux reconstructor

Frankenstein (frank) fits the 1D radial brightness profile of an interferometric source given a set of visibilities. It uses a Gaussian process that performs the fit in <1 minute for a typical protoplanetary disc continuum dataset. Frankenstein can perform a fit in 2 ways, by running the code directly from the terminal or using the code as a Python module.

[ascl:2109.009] pyFFTW: Python wrapper around FFTW

pyFFTW is a pythonic wrapper around FFTW (ascl:1201.015), the speedy FFT library. Both the complex DFT and the real DFT are supported, as well as on arbitrary axes of arbitrary shaped and strided arrays, which makes it almost feature equivalent to standard and real FFT functions of numpy.fft. Additionally, it supports the clongdouble dtype, which numpy.fft does not, and operating FFTW in multithreaded mode.

[ascl:2109.008] pyia: Python package for working with Gaia data

pyia provides tools for working with Gaia data. It accesses Gaia data columns as Quantity objects, i.e., with units (e.g., data.parallax will have units ‘milliarcsecond’)
, constructs covariance matrices for Gaia data, and generates random samples from the Gaia error distribution per source. pyia can also create SkyCoord objects from Gaia data and execute simple (small) remote queries via the Gaia science archive and automatically fetch the results.

[ascl:2109.007] SkyCalc_ipy: SkyCalc wrapper for interactive Python

SkyCalc-iPy (SkyCalc for interactive Python) accesses atmospheric emission and transmission data generated by ESO’s SkyCalc tool interactively with Python. This package is based on the command line tool by ESO for accessing spectra on the ESO SkyCalc server.

[ascl:2109.006] eMCP: e-MERLIN CASA pipeline

The e-MERLIN CASA Pipeline calibrates and processes data from the e-MERLIN radio interferometer. It works on top of CASA (ascl:1107.013) and can convert, concatenate, prepare, flag and calibrate raw to produce advanced calibrated products for both continuum and spectral line data. The main outputs of the data are calibration tables, calibrated data, assessment plots, preliminary images of target and calibrator sources and a summary weblog. The pipeline provides an easy, ready-to-use toolkit that delivers calibrated data in a consistent, clear, and repeatable way. A parameters file is used to control the pipeline execution, so optimization of the algorithms is straightforward and reproducible. Good quality images are usually obtained with minimum human intervention.

[ascl:2109.005] SoFiA 2: An automated, parallel HI source finding pipeline

SoFiA 2 is a fully automated spectral-line source finding pipeline originally intended for the detection of galaxies in large HI data cubes. It is a reimplementation of parts of the original SoFiA pipeline (ascl:1412.001) in the C programming language and uses OpenMP for multithreading, making it substantially faster and more memory-efficient than its predecessor. At its core, SoFiA 2 uses the Smooth + Clip algorithm for source finding which operates by spatially and spectrally smoothing the data on multiple scales and applying a user-defined flux threshold relative to the noise level in each iteration. A wide range of useful preconditioning and post-processing filters is available, including noise normalization, flagging of artifacts and reliability filtering. In addition to global data products and source catalogs in different formats, SoFiA 2 can also generate cutout images and spectra for each individual detection.

[ascl:2109.004] DviSukta: Spherically Averaged Bispectrum calculator

DviSukta calculates the Spherically Averaged Bispectrum (SABS). The code is based on an optimized direct estimation method, is written in C, and is parallelized. DviSukta starts by reading the real space gridded data and performing a 3D Fourier transform of it. Alternatively, it starts by reading the data already in Fourier space. The grid spacing, number of k1 bins, number of n bins, and number of cos(theta) bins need to be specified in the input file.

[ascl:2109.003] VOLKS2: VLBI Observation for transient Localization Keen Searcher

The VOLK2 (VLBI Observation for transient Localization Keen Searcher) pipeline conducts single pulse searches and localization in regular VLBI observations as well as single pulse detections from known sources in dedicated observations. In VOLKS2, the search and localization are two independent steps. The search step takes the idea of geodetic VLBI post processing, which fully utilizes the cross spectrum fringe phase information to maximize the signal power. Compared with auto spectrum based method, it is able to extract single pulses from highly RFI contaminated data. The localization uses the geodetic VLBI solving methods, which derives the single pulse location by solving a set of linear equations given the relation between the residual delay and the offset to a priori position.

[ascl:2109.002] alpconv: Calculating alp-photon conversion

alpconv calculates the alp-photon conversion by calculating the degree of irregularity of the spectrum, in contract to some other methods that fit the source's spectrum with both null and ALP models and then compare the goodness of fit between the two.

[ascl:2109.001] gammaALPs: Conversion probability between photons and axions/axionlike particles

gammaALPs calculates the conversion probability between photons and axions/axion-like particles in various astrophysical magnetic fields. Though focused on environments relevant to mixing between gamma rays and ALPs, this suite, written in Python, can also be used for broader applications. The code also implements various models of astrophysical magnetic fields, which can be useful for applications beyond ALP searches.

[submitted] Pyckles

A super lightweight interface in Python to load spectra from the Pickles 1998 (stellar) and Brown 2014 (galactic) spectral catalogues

[submitted] AnisoCADO

A python package created around Eric Gendron’s code for analytically (and quickly) generating field-varying SCAO PSFs for the ELT.

[submitted] ScopeSim Instrument Reference Database

A reference database for astronomical instrument and telescope characteristics for all types of visual and infrared systems. Instrument packages are used in conjunction with the ScopeSim instrument data simulator.

[submitted] ScopeSim Templates

Templates and helper functions for creating on-sky Source description objects for the ScopeSim instrument data simulation engine.

[submitted] ScopeSim

An attempt at creating a common pythonic framework for visual and infrared telescope instrument data simulators.

[ascl:2108.025] SORA: Stellar Occultation Reduction Analysis

SORA optimally analyzes stellar occultation data. The library includes processes starting on the prediction of such events to the resulting size, shape and position of the Solar System object and can be used to build pipelines to analyze stellar occultation data. A stellar occultation is defined by the occulting body (Body), the occulted star (Star), and the time of the occultation. On the other hand, each observational station (Observer) will be associated with their light curve (LightCurve). SORA has tasks that allow the user to determine the immersion and emersion times and project them to the tangent sky plane, using the information within the Observer, Body and Star Objects. That projection will lead to chords that will be used to obtain the object’s apparent size, shape and position at the moment of the occultation. Automatic processes optimize the reduction of typical events. However, users have full control over the parameters and methods and can make changes in every step of the process.

[ascl:2108.024] iminuit: Jupyter-friendly Python interface for C++ MINUIT2

iminuit is a Jupyter-friendly Python interface for the Minuit2 C++ library maintained by CERN's ROOT team. It can be used as a general robust function minimization method, but is most commonly used for likelihood fits of models to data, and to get model parameter error estimates from likelihood profile analysis.

[ascl:2108.023] CMC-COSMIC: Cluster Monte Carlo code

CMC-COSMIC models dense star clusters using Hénon's method using orbit-averaging collisional stellar dynamics. It includes all the relevant physics for modeling dense spherical star clusters, such as strong dynamical encounters, single and binary stellar evolution, central massive black holes, three-body binary formation, and relativistic dynamics, among others. CMC is parallelized using the Message Passing Interface (MPI), and is pinned to the COSMIC (ascl:2108.022) package for binary population synthesis, which itself was originally based on the version of BSE (ascl:1303.014). COSMIC is currently a submodule within CMC, ensuring that any cluster simulations or binary populations are integrated with the same physics.

[ascl:2108.022] COSMIC: Compact Object Synthesis and Monte Carlo Investigation Code

COSMIC (Compact Object Synthesis and Monte Carlo Investigation Code) generates synthetic populations with an adaptive size based on how the shape of binary parameter distributions change as the number of simulated binaries increases. It implements stellar evolution using SSE (ascl:1303.015) and binary interactions using BSE (ascl:1303.014). COSMIC can also be used to simulate a single binary at a time, a list of multiple binaries, a grid of binaries, or a fixed population size as well as restart binaries at a mid point in their evolution. The code is included in CMC-COSMIC (ascl:2108.023).

[ascl:2108.021] ExoPlaSim: Exoplanet climate simulator

ExoPlaSim extends the PlaSim (ascl:2107.019) 3D general climate model to terrestrial exoplanets. It includes the PlaSim general circulation model and modifications that allow this code to run tidally-locked planets, planets with substantially different surface pressures than Earth, planets orbiting stars with different effective temperatures, super-Earths, and more. ExoPlaSim includes the ability to compute carbon-silicate weathering, dynamic orography through the glacier module (though only accumulation and ablation/evaporation/melting are included; glacial flow and spreading are not), and storm climatology.

[ascl:2108.020] DBSP_DRP: DBSP Data Reduction Pipeline

DBSP_DRP reduces data from the Palomar spectrograph DBSP. Built on top of PypeIt (ascl:1911.004), it automates the reduction, fluxing, telluric correction, and combining of the red and blue sides of one night's data. The pipeline also provides several GUIs for easier control of the reduction, with one for selecting which data to reduce, and verifying the correctness of FITS headers in an editable table. Another GUI manually places traces for a sort of manually "forced" spectroscopy with the -m option, and after manually placing traces, manually selects sky regions and tweaks the FWHM of the manual traces.

[ascl:2108.019] PIPS: Period detection and Identification Pipeline Suite

PIPS analyzes the lightcurves of astronomical objects whose brightness changes periodically. Originally developed to determine the periods of RR Lyrae variable stars, the code offers many features designed for variable star analysis and can obtain period values for almost any type of lightcurve with both speed and accuracy. PIPS determines periods through several different methods, analyzes the morphology of lightcurves via Fourier analysis, estimates the statistical significance of the detected signal, and determines stellar properties based on pre-existing stellar models.

[ascl:2108.018] Cosmic-CoNN: Cosmic ray detection toolkit

Cosmic-CoNN detects cosmic rays (CR) in CCD-captured astronomical images. It offers a PyTorch deep-learning framework to train generic, robust CR detection models for ground- and space-based imaging data as well as spectroscopic observations. Cosmic-CoNN also includes a suite of tools, including console commands, a web app, and Python APIs, to make deep-learning models easily accessible.

[ascl:2108.017] AutoProf: Automatic Isophotal solutions for galaxy images

AutoProf performs basic and advanced non-parametric galaxy image analysis. The pipeline's design allows for fast startup and easy implementation; the package offers a suite of robust default and optional tools for surface brightness profile extractions and related methods. AUTOPROF is highly extensible and can be adapted for a variety of applications, providing flexibility for exploring new ideas and supporting advanced users.

[ascl:2108.016] Chemulator: Thermochemical emulator for hydrodynamical modeling

The neural network-based emulator Chemulator advances the gas temperature and chemical abundances of a single position in an astrophysical gas. It is accurate on a single timestep and stable over many iterations with decreased accuracy, though performs less well at low visual extinctions. The code is useful for applications such as large scale ISM modeling; by retraining the emulator for a given parameter space, Chemulator could also perform more specialized applications such as planetary atmosphere modeling.

[ascl:2108.015] ELISa: Eclipsing binaries Learning Interactive System

ELISa models light curves of close eclipsing binaries. It models surfaces of detached, semi-detached, and over-contact binaries, generates light curves, and generates stellar spots with given longitude, latitude, radius, and temperature. It can also fit radial velocity curves and light curves via the implementation of the non-linear least squares method and also via Markov Chain Monte Carlo method.

[ascl:2108.014] StelNet: Stellar mass and age predictor

StelNet predicts mass and age from absolute luminosity and effective temperature for stars with close to solar metallicity. It uses a Deep Neural Network trained on stellar evolutionary tracks. The underlying model makes no assumption on the evolutionary stage and includes the pre-main sequence phase. A mix of models are trained and bootstrapped to quantify the uncertainty of the model, and data is through all trained models to provide a predictive distribution from which an expectation value and uncertainty level can be estimated.

[ascl:2108.013] AMOEBA: Automated Gaussian decomposition

AMOEBA (Automated Molecular Excitation Bayesian line-fitting Algorithm) employs a Bayesian approach to Gaussian decomposition, resulting in an objective and statistically robust identification of individual clouds along the line-of-sight. It uses the Python implementation of Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler emcee (ascl:1303.002) to sample the posterior probability distribution and numerically evaluate the integrals required to compute the Bayes Factor. Amoeba takes as input a set of OH optical depth spectra and a set of expected brightness temperature spectra that are obtained by measuring the brightness temperature towards the bright background continuum source (the "on-source" observations), and in a pattern surrounding the continuum source (the "off-source" observations). Amoeba can also take as input a set of OH optical depth spectra only, and also allows input of an arbitrary number of spectra to be fit simultaneously.

[ascl:2108.012] NRDD_constraints: Dark Matter interaction with the Standard Model exclusion plot calculator

The NRDD_constraints tool provides simple interpolating functions written in Python that return the most constraining limit on the dark matter-nucleon scattering cross section for a list of non-relativistic effective operators. The package contains four files: the main code, NRDD_constraints.py; a simple driver, NRDD_constraints-example.py; and two data files, NRDD_data1.npy and NRDD_data2.npy

[ascl:2108.011] BOSS-Without-Windows: Window-free analysis of the BOSS DR12 power spectrum and bispectrum

BOSS-Without-Windows analyzes Baryon Oscillation Spectroscopic Survey (BOSS) DR12 data using quadratic and cubic estimators. It contains analysis codes to estimate unwindowed power spectra and unwindowed bispectra. It also supplies the raw power and bispectrum spectrum measurements of BOSS and 999 Patchy simulations, and contains a utility function to generate the background number density, n(r) from the survey mask and n(z) distribution.

[ascl:2108.010] FIREFLY: Chi-squared minimization full spectral fitting code

FIREFLY (Fitting IteRativEly For Likelihood analYsis) derives stellar population properties of stellar systems, whether observed galaxy or star cluster spectra or model spectra from simulations. The code fits combinations of single-burst stellar population models to spectroscopic data following an iterative best-fitting process controlled by the Bayesian Information Criterion without applying priors. Solutions within a statistical cut are retained with their weight, which is arbitrary. No additive or multiplicative polynomia are used to adjust the spectral shape and no regularization is imposed. This fitting freedom allows mapping of the effect of intrinsic spectral energy distribution (SED) degeneracies, such as age, metallicity, dust reddening on stellar population properties, and quantifying the effect of varying input model components on such properties.

[ascl:2108.009] caesar-rest: Web service for the caesar source extractor

caesar-rest is a REST-ful web service for astronomical source extraction and classification with the caesar source extractor [ascl:1807.015]. The software is developed in python and consists of containerized microservices, deployable on standalone servers or on a distributed cloud infrastructure. The core component is the REST web application, based on the Flask framework and providing APIs for managing the input data (e.g. data upload/download/removal) and source finding jobs (e.g. submit, get status, get outputs) with different job management systems (Kubernetes, Slurm, Celery). Additional services (AAI, user DB, log storage, job monitor, accounting) enable the user authentication, the storage and retrieval of user data and job information, the monitoring of submitted jobs, and the aggregation of service logs and user data/job stats.

[ascl:2108.008] CatBoost: High performance gradient boosting on decision trees library

CatBoost is a machine learning method based on gradient boosting over decision trees and can be used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. It supports both numerical and categorical features and computation on CPU and GPU, and is fast and scalable. Visualization tools are also included in CatBoost.

[ascl:2108.007] catwoman: Transit modeling Python package for asymmetric light curves

catwoman models asymmetric transit lightcurves. Written in Python, it calculates light curves for any radially symmetric stellar limb darkening law, and where planets are modeled as two semi-circles of different radii. Catwoman is built on the batman library (ascl:1510.002) and uses its integration algorithm.

[ascl:2108.006] viper: Velocity and IP EstimatoR

viper (Velocity and IP EstimatoR) measures differential radial velocities from stellar spectra taken through iodine or other gas cells. It convolves the product of a stellar template and a gas cell spectrum with an instrumental profile. Via least square fitting, it optimizes the parameters of the instrumental profile, the wavelength solution, flux normalization, and the stellar Doppler shift. viper offers various functions to describe the instrumental profile such as Gaussian, super-Gaussian, skewed Gaussian or mixtures of Gaussians. The code is developed for echelle spectra; it can handle data from CES, CRIRES+, KECK, OES, TCES, and UVES, and additional instruments can easily be added. A graphical interface facilitates the work with numerous flexible options.

[ascl:2108.005] millennium-tap-query: Python tool to query the Millennium Simulation UWS/TAP client

millennium-tap-query is a simple wrapper for the Python package requests to deal with connections to the Millennium TAP Web Client. With this tool you can perform basic or advanced queries to the Millennium Simulation database and download the data products. millennium-tap-query is similar to the TAP query tool in the German Astrophysical Virtual Observatory (GAVO) VOtables package.

[ascl:2108.004] WaldoInSky: Anomaly detection algorithms for time-domain astronomy

WaldoInSky finds anomalous astronomical light curves and their analogs. The package contains four methods: an adaptation of the Unsupervised Random Forest for anomaly detection in light curves that operates on the light curve points and their power spectra; two manifold-learning methods (the t-SNE and UMAP) that operate on the DMDT maps (image representations of the light curves), and that can be used to find analog light curves in the low-dimensional representation; and an Isolation Forest method for evaluating approaches of light curve pre-processing, before they are passed to the anomaly detectors. WaldoInSky also contain code for random sparsification of light curves.

[ascl:2108.003] MAPS: Multi-frequency Angular Power Spectrum estimator

MAPS (Multi-frequency Angular Power Spectrum) extracts two-point statistical information from Epoch of Reionization (EoR) signals observed in three dimensions, with two directions on the sky and the wavelength (or frequency) constituting the third dimension. Rather than assume that the signal has the same statistical properties in all three directions, as the spherically averaged power spectrum (SAPS) does, MAPS does not make these assumptions, making it more natural for radio interferometric observations than SAPS.

[ascl:2108.002] AUM: A Unified Modeling scheme for galaxy abundance, galaxy clustering and galaxy-galaxy lensing

AUM predicts galaxy abundances, their clustering, and the galaxy-galaxy lensing signal, given the halo occupation distribution of galaxies and the underlying cosmological model. In combination with the measurements of the clustering, abundance, and lensing of galaxies, these routines can be used to perform cosmological parameter inference.

[submitted] spectrogrism

This module implements an ad-hoc grism-based spectrograph optical model. It provides a flexible chromatic mapping between the input focal plane and the output detector plane, based on an effective simplified ray-tracing model of the key optical elements defining the spectrograph (collimator, prism, grating, camera), described by a restricted number of physically-motivated distortion parameters.

[ascl:2108.001] HRK: HII Region Kinematics

Generate simulated radio recombination line observations of HII regions with various internal kinematic structure. Fit single Gaussians to each pixel of the simulated observations and generate images of the fitted Gaussian center and full-width half-maximum (FWHM) linewidth.

[submitted] MALU IFS visualisation tool

MALU visualizes integral field spectroscopy (IFS) data such as CALIFA, MANGA, SAMI or MUSE data producing fully interactive plots. The tool is not specific to any instrument. It is available in Python and no installation is required.

[ascl:2107.030] HERMES: High-Energy Radiative MESsengers

The HERMES (High-Energy Radiative MESsengers) computational framework for line of sight integration creates sky maps in the HEALPix-compatibile format of various galactic radiative processes, including Faraday rotation, synchrotron and free-free radio emission, gamma-ray emission from pion-decay, bremsstrahlung and inverse-Compton. The code is written in C++ and provides numerous integrators, including dispersion measure, rotation measure, and Gamma-ray emissions from Dark Matter annihilation, among others.

[ascl:2107.029] PHL: Persistent_Homology_LSS

Persistent_Homology_LSS analyzes halo catalogs using persistent homology to constrain cosmological parameters. It implements persistent homology on a point cloud composed of halos positions in a cubic box from N-body simulations of the universe at large scales. The output of the code are persistence diagrams and images that are used to constrain cosmological parameters from the halo catalog.

[ascl:2107.028] TRINITY: Dark matter halos, galaxies and supermassive black holes empirical model

TRINITY statistically connects dark matter halos, galaxies and supermassive black holes (SMBHs) from z=0-10. Constrained by multiple galaxy (0 < z < 10) and SMBH datasets (0 < z < 6.5), the empirical model finds the posterior probability distributions of the halo-galaxy-SMBH connection and SMBH properties, all of which are allowed to evolve with redshift. TRINITY can predict many observational data, such as galaxy stellar mass functions and quasar luminosity functions, and underlying galaxy and SMBH properties, including SMBH Eddington average Eddington ratios. These predictions are made by different code files. There are basically two types of prediction codes: the first type generates observable data given input redshift or redshift invertals; the second type generates galaxy or SMBH properties as a function of host halo mass and redshift.

[ascl:2107.027] KeplerPORTS: Kepler Planet Occurrence Rate Tools

KeplerPORTS calculates the detection efficiency of the DR25 Kepler Pipeline. It uses a detection contour model to quantify the recoverability of transiting planet signals due to the Kepler pipeline, and accurately portrays the ability of the Kepler pipeline to generate a Threshold Crossing Event (TCE) for a given hypothetical planet.

[ascl:2107.026] K2mosaic: Mosaic Kepler pixel data

K2mosaic stitches the postage stamp-sized pixel masks obtained by NASA's Kepler and K2 missions together into CCD-sized mosaics and movies. The command-line tool's principal use is to take a set of Target Pixel Files (TPF) and turn them into more traditional FITS image files -- one per CCD channel and per cadence. K2mosaic can also be used to create animations from these mosaics. The mosaics produced by K2mosaic also makes the analysis of certain Kepler/K2 targets, such as clusters and asteroids, easier. Moreover such mosaics are useful to reveal the context of single-star observations, e.g., they enable users to check for the presence of instrumental noise or nearby bright objects.

[ascl:2107.025] MCPM: Modified CPM method

MCPM extracts K2 photometry in dense stellar regions; the code is a modification and extension of the K2-CPM package (ascl:2107.024), which was developed for less-crowded fields. MCPM uses the pixel response function together with accurate astrometric grids, combining signals from a few pixels, and simultaneously fits for an astrophysical model to produce extracted more precise K2 photometry.

[ascl:2107.024] K2-CPM: Causal Pixel Model for K2 data

K2-CPM captures variability while preserving transit signals in Kepler data. Working at the pixel level, the model captures very fine-grained information about the variation of the spacecraft. The CPM models the systematic effects in the time series of a pixel using the pixels of many other stars and the assumption that any shared signal in these causally disconnected light curves is caused by instrumental effects. The target star's future and past are used and the data points are separated into training and test sets to ensure that information about any transit is perfectly isolated from the model. The method has four tuning parameters, the number of predictor stars or pixels, the autoregressive window size, and two L2-regularization amplitudes for model components, and consistently produces low-noise light curves.

[ascl:2107.023] cosmic_variance: Cosmic variance calculator

cosmic_variance calculates the cosmic variance during the Epoch of Reionization (EoR) for the UV Luminosity Function (UV LF), Stellar Mass Function (SMF), and Halo Mass Function (HMF). The three functions in the package provide the output as the cosmic variance expressed in percentage. The code is written in Python, and simple examples that show how to use the functions are provided.

[ascl:2107.022] Kd-match: Correspondences of objects between two catalogs through pattern matching

Kd-match matches stellar catalogs for which the transformation between the coordinate systems of the two catalogs is unknown and might include shearing. The code uses the ratio of sides as the invariant under a coordinate transformation and searches for several triangles with similar transformations by building quadrilaterals from sets of four objects in each catalog and calculating the ratio of areas of the triangles that comprise the quadrilaterals. The k-d tree accelerates this quadrilateral search dramatically and is significantly faster than the customary direct search over triangles.

[ascl:2107.021] RePrimAnd: Recovery of Primitives And EOS framework

The RePrimAnd library supports numerical simulations of general relativistic magnetohydrodynamics. It provides methods for recovering primitive variables such as pressure and velocity from the variables evolved in quasi-conservative formulations. Further, it provides a general framework for handling matter equations of state (EOS). Python bindings are automatically built together with the library, provided a Python3 installation containing the pybind11 package is detected. RePrimAnd also provides an (experimental) thorn that builds the library within an Einstein Toolkit (ascl:1102.014) environment using the ExternalLibraries mechanism.

[ascl:2107.020] Chem-I-Calc: Chemical Information Calculator

Chem-I-Calc evaluates the chemical information content of resolved star spectroscopy. It takes advantage of the Fisher information matrix and the Cramér-Rao inequality to quickly calculate the Cramér-Rao lower bounds (CRLBs), which give the best theoretically achievable precision from a set of observations.

[ascl:2107.019] PlaSim: Planet Simulator

PlaSim is a climate model of intermediate complexity for Earth, Mars and other planets. It is written for a university environment, to be used to train the next GCM (general circulation model) developers, to support scientists in understanding climate processes, and to do fundamental research. In addition to an atmospheric GCM of medium complexity, PlaSim includes other compartments of the climate system such as, for example, an ocean with sea ice and a land surface with a biosphere. These other compartments are reduced to linear systems. In other words, PlaSim consists of a GCM with a linear ocean/sea-ice module formulated in terms of a mixed layer energy balance. The soil/biosphere module is introduced analoguously. Thus, working with PlaSim is like testing the performance of an atmospheric or oceanic GCM interacting with various linear processes, which parameterize the variability of the subsystems in terms of their energy (and mass) balances.

[ascl:2107.018] ART: A Reconstruction Tool

ART reconstructs log-probability distributions using Gaussian processes. It requires an existing MCMC chain or similar set of samples from a probability distribution, including the log-probabilities. Gaussian process regression is used for interpolating the log-probability for the rescontruction, allowing for easy resampling, importance sampling, marginalization, testing different samplers, investigating chain convergence, and other operations.

[ascl:2107.017] PyCactus: Post-processing tools for Cactus computational toolkit simulation data

PyCactus contains tools for postprocessing data from numerical simulations performed with the Einstein Toolkit, based on the Cactus computational toolkit. The main package is PostCactus, which provides a high-level Python interface to the various data formats in a simulation folder. Further, the package SimRep allows the automatic creation of html reports for a simulation, and the SimVideo package allows the creation of movies visualizing simulation data.

[ascl:2107.016] shear-stacking: Stacked shear profiles and tests based upon them

shear-stacking calculates stacked shear profiles and tests based upon them, e.g. consistency for different slices of lensed background galaxies. The basic concept is that the lensing signal in terms of surface mass density (instead of shear) should be entirely determined by the properties of the lens sample and have no dependence on source galaxy properties.

[ascl:2107.015] shapelens: Astronomical image analysis and shape estimation framework

The shapelens C++ library provides ways to load galaxies and star images from FITS files and catalogs and to analyze their morphology. The main purpose of this library is to make several weak-lensing shape estimators publicly available. All of them are based on the moments of the brightness distribution. The estimators include DEIMOS, for analytic deconvolution in moment space, DEIMOSElliptical, a practical implemention of DEIMOS with an automatically matched elliptical weight function, DEIMOSCircular, which is identical to DEIMOSElliptical but with a circular weight function, and others.

[ascl:2107.014] Skylens++: Simulation package for optical astronomical observations

Skylens++ implements a Layer-based raytracing framework particularly well-suited for realistic simulations of weak and strong gravitational lensing. Source galaxies can be drawn from analytic models or deep space-based imaging. Lens planes can be populated with arbitrary deflectors, typically either from N-body simulations or analytic lens models. Both sources and lenses can be placed at freely configurable positions into the light cone, in effect allowing for multiple source and lens planes.

[ascl:2107.013] GUBAS: General Use Binary Asteroid Simulator

GUBAS (General Use Binary Asteroid Simulator) predicts binary asteroid system behaviors by implementing the Hou 2016 realization of the full two-body problem (F2BP). The F2BP models binary asteroid systems as two arbitrary mass distributions whose mass elements interact gravitationally and result in both gravity forces and torques. To account for these mass distributions and model the mutual gravity of the F2BP, GUBAS computes the inertia integrals of each body up to a user defined expansion order. This approach provides a recursive expression of the mutual gravity potential and represents a significant decrease in the computational burden of the F2BP when compared to other methods of representing the mutual potential.

[ascl:2107.012] PyROA: Modeling quasar light curves

PyROA models quasar light curves where the variability is described using a running optimal average (ROA), and parameters are sampled using Markov Chain Monte Carlo (MCMC) techniques using emcee (ascl:1303.002). Using a Bayesian approach, priors can be used on the sampled parameters. Currently it has three main uses: 1.) Determining the time delay between lightcurves at different wavelengths; 2.) Intercalibrating light curves from multiple telescopes, merging them into a single lightcurve; and 3.) Determining the time delay between images of lensed quasars, where the microlensing effects are also modeled. PyROA also includes a noise model, where there is a parameter for each light curve that adds extra variance to the flux measurments, to account for underestimated errors; this can be turned off if required. Example jupyter notebooks that demonstrate each of the three main uses of the code are provided.

[ascl:2107.011] AlignBandColors: Inter-color-band image alignment tool

AlignBandColors (ABC) aligns inter-color-band astronomical images to a 100th of a pixel accuracy using surrounding stars as guiding points. It has currently been tested with Sloan Digital Sky Survey (SDSS) Data Release 12 images, but is designed to be survey-independent. The code is part of the SpArcFiRe (ascl:2107.010) method.

[ascl:2107.010] SpArcFiRe: SPiral ARC FInder and REporter

SpArcFiRe takes as input an image of a galaxy in FITS, JPG, or PNG format, identifies spiral arms, and extracts structural information about the spiral arms. Pixels in each arm segment are listed, enabling image analysis on each segment. The automated method also performs a least-squares fit of a logarithmic spiral arc to the pixels in that segment, giving per-arc parameters, such as the pitch angle, arm segment length, and location, and outputs images showing the steps SpArcFire took to detect arm segments.

[ascl:2107.009] Balrog: Astronomical image simulation

The Balrog package of Python simulation code is for use with real astronomical imaging data. Objects are simulated into a survey's images and measurement software is run over the simulated objects' images. Balrog allows the user to derive the mapping between what is actually measured and the input truth. The package uses GalSim (ascl:1402.009) for all object simulations; source extraction and measurement is performed by SExtractor (ascl:1010.064). Balrog facilitates the ease of running these codes en masse over many images, automating useful GalSim and SExtractor functionality, as well as filling in many bookkeeping steps along the way.

[ascl:2107.008] nimbus: A Bayesian inference framework to constrain kilonova models

nimbus is a hierarchical Bayesian framework to infer the intrinsic luminosity parameters of kilonovae (KNe) associated with gravitational-wave (GW) events, based purely on non-detections. This framework makes use of GW 3-D distance information and electromagnetic upper limits from a given survey for multiple events, and self-consistently accounts for finite sky-coverage and probability of astrophysical origin.

[ascl:2107.007] Skymapper: Mapping astronomical survey data on the sky

Skymapper maps astronomical survey data from the celestial sphere onto 2D using a collection of matplotlib instructions. It facilitates interactive work as well as the creation of publication-quality plots with a python-based workflow many astronomers are accustomed to. The primary motivation is a truthful representation of samples and fields from the curved sky in planar figures, which becomes relevant when sizable portions of the sky are observed.

[ascl:2107.006] snmachine: Photometric supernova classification

snmachine reads in photometric supernova light curves, extracts useful features from them, and subsequently performs supervised machine learning to classify supernovae based on their light curves. This python library is also flexible enough to easily extend to general transient classification.

[ascl:2107.005] ReionYuga: Epoch of Reionization neutral Hydrogen field generator

The C code ReionYuga generates the Epoch of Reionization (EoR) neutral Hydrogen (HI) field (successively the redshifted 21-cm signal) within a cosmological simulation box using semi-numerical techniques. The code is based on excursion set formalism and uses a three parameter model. It is designed to work with PMN-body (ascl:2107.003) and FoF-Halo-finder (ascl:2107.004).

[ascl:2107.004] FoF-Halo-finder: Halo location and size

FoF-Halo-finder identifies the location and size of collapsed objects (halos) within a cosmological simulation box. These halos are the host for the luminous objects in the Universe. Written in C, it is based on the friends-of-friends (FoF) algorithm, and is designed to work with PMN-body (ascl:2107.003).

[ascl:2107.003] PMN-body: Particle Mesh N-body code

PMN-body computes the non-linear evolution of the cosmological matter density contrast. It is based on the Particle Mesh (PM) technique. Written in C, the code is parallelized for shared-memory machines using Open Multi-Processing (OpenMP).

[ascl:2107.002] ROA: Running Optimal Average

ROA (Running Optimal Average) describes time series data. This model uses a Gaussian window function that moves through the data giving stronger weights to points close to the center of the Gaussian. Therefore, the width of the window function, delta, controls the flexibility of the model, with a small delta providing a very flexible model. The function also calculates the effective number of parameters, as a very flexible model will correspond to large number of parameters while a rigid model (low delta) has a low effective number of parameters. Knowing the effective number of parameters can be used to optimize the window width, e.g., using the Bayesian information criterion (BIC). An error envelope, which expands appropriately where there are gaps in the data, is also calculated for the model.

[ascl:2107.001] light-curve: Light curve analysis toolbox

light-curve implements the extraction of numerous light curve features suitable for processing alert and archival data for the current ZTF and future Vera Rubin Observatory LSST photometric surveys. These high-performance irregular time series processing tools are written in Rust and Python.

[submitted] GalaXimView

GalaXimView (for Galaxies Simulations Viewer) is a python3+matplotlib tool designed to visualise simulations which use particles, providing notably a rotatable 3D view and corresponding projections in 2D, together with a way of navigating through snapshots of a simulation keeping the same projection.

[ascl:2106.040] IRAGNSEP: Spectral energy distribution fitting code

iragnsep performs IR SED fits separated into AGN and galaxy contributions, and measures host galaxy properties free of AGN contamination. The advantage of iragnsep is that, in addition to fitting observed broadband photometric fluxes, it also incorporates IR spectra in the fits which, if available, improves the robustness of the galaxy-AGN separation. For the galaxy component, iragnsep uses a library of galaxy templates. In terms of the AGN contribution, if the input dataset is a mixture of spectral and photometric data, iragnsep uses a combination of power-laws for the AGN continuum, and some broad features for the silicate emission. If instead the dataset contains photometric data alone, the AGN contribution is accounted for by using a library of AGN templates. The advanced fitting techniques used by iragnsep combined with the powerful model comparison tests allows iragnsep to provide a statistically robust interpretation of IR SEDs in terms of AGN-galaxy contributions, even when the AGN contribution is highly diluted by the host galaxy emission.

[ascl:2106.039] atmos: Coupled climate–photochemistry model

Atmos contains two atmospheric models and scripts to couple them together. One atmospheric model calculates the profiles of chemical species, including both gaseous and aerosol phases, and the second model calculates the temperature profile. Because these profiles depend on each other - kinetic reaction rates are temperature-dependent and radiative transfer is subject to radiatively active gases - atmos alternates the running of these two models until both models have solutions consistent with the other one. While either of these models can be run with time-dependence, most applications of these models are to find steady-state solutions for the atmosphere that would be stable over long (geological/astronomical) time periods, given constant inputs to the atmosphere.

[ascl:2106.038] ehtplot: Plotting functions for the Event Horizon Telescope

ehtplot creates publication quality, elegant, and consistent plots. Written for the Event Horizon Telescope (EHT) Collaboration, it provides a set of easy-to-use plotting functions for EHT and Very-Long-Baseline Interferometry (VLBI) specific figures. This includes plotting visibility and images for both synthetic and real data, adding uv-tracks to the plots, and adding the expected event horizon size to the plots, among other functions.

[ascl:2106.037] PORTA: POlarized Radiative TrAnsfer

PORTA solves three-dimensional non-equilibrium radiative transfer problems with massively parallel computers. The code can be used for modeling the spectral line polarization produced by the scattering of anisotropic radiation and the Hanle and Zeeman effects assuming complete frequency redistribution, either using two-level or multilevel atomic models. The numerical method of solution used to find the self-consistent values of the atomic density matrix at each point of the model’s Cartesian grid is based on Jacobi iterative scheme and on a short-characteristics formal solver of the Stokes-vector transfer equation that uses monotonic Bézier interpolation. The code can also be used to compute the linear polarization of the continuum radiation caused by Rayleigh and Thomson scattering in 3D models of stellar atmospheres, and to solve the simpler 3D radiative transfer problem of unpolarized radiation in multilevel systems. PORTA accepts/produces HDF5 input/output and offers an advanced graphical user interface.

[ascl:2106.036] BiFFT: Fast estimation of the bispectrum

BiFFT uses Fourier transforms to implement the Dirac-Delta function that enforces a closed triangle of three k-vectors; this allows very fast calculations of the bispectrum. Once the C code associated with the package is compiled and the source folder directed to the location of the C code, the user can run the code using the python wrapper.The binning in each function has been tested over the course of many years and the user can use it out of the box without ever touching the underlying C code. However, the cylindrical bispectrum calculation is much more sensitive to sample variance; its default binning is quite coarse and might need adjusting (and testing) for some datasets.

[ascl:2106.035] CalPriorSNIa: Effective calibration prior on the absolute magnitude of Type Ia supernovae

CalPriorSNIa quickly computes the effective calibration prior on the absolute magnitude MB of Type Ia supernovae that corresponds to a given determination of H0.

[ascl:2106.034] ztf-viewer: SNAD ZTF data releases object viewer

The SNAD ZTF DR4 object viewer enables quick expert investigation of objects within the public Zwicky Transient Facility (ZTF) data releases. The viewer allows visualization of raw and folded light curves and metadata, as well as cross-match information with the General Catalog of Variable Stars, the International Variable Stars Index, the ATLAS Catalog of Variable Stars, the ZTF Catalog of Periodic Variable Stars, the Transient Name Server, the Open Astronomy Catalogs, the OGLE III Catalog of Variable Stars, the Simbad Astronomical Data Base, Gaia DR2 distances (Bailer-Jones+, 2018), and Vizier. The viewer is also available for ZTF DR2 and ZTF DR3.

[ascl:2106.033] ZWAD: Anomaly detection pipeline

ZWAD (ZTF anomaly detection pipeline) examines data and performs tailored feature extraction. The code then uses machine learning methods to searches for outliers, and identifies anomalies to be examined for validation by experts. Used with the SNAD ZTF data releases object viewer (ascl:2106.034), the infrastructure helps experts to form global views of specific scientifically interesting candidates.

[ascl:2106.032] DarkSirensStat: Measuring modified GW propagation and the Hubble parameter

DarkSirensStat statistically measures modified gravitational wave (GW) propagation and the Hubble parameter. The package implements a hierarchical Bayesian framework for constraining the Hubble parameter and modified GW propagation with dark sirens and galaxy catalogs. The package downloads the needed data; which include the GLADE galaxy catalog, O2 and O3 skymaps from the LVC official data releases, and O2 and O3 strain sensitivities. The default options are for running inference for H0 on the O3 BBH events, with flat prior between 20 and 140, mask completeness with 9 masks, interpolation between multiplicative and homogeneous completion, B-band luminosity weights, and a completeness threshold of 50%. The selection effects are computed with MC.

[ascl:2106.031] BiHalofit: Fitting formula of non-linear matter bispectrum

BiHalofit fits the matter bispectrum in the nonlinear regime calibrated by high-resolution cosmological N-body simulations of 41 cold dark matter models around the Planck 2015 best-fit parameters. The parameterization is similar to that in Halofit (ascl:1402.032). The simulation volume is sufficiently large to cover almost all measurable triangle bispectrum configurations in the universe, and the function is calibrated using one-loop perturbation theory at large scales. BiHaloFit predicts the weak-lensing bispectrum and will assist current and future weak-lensing surveys and cosmic microwave background lensing experiments.

[ascl:2106.030] DM_statistics: Statistics of the cosmological dispersion measure (DM)

DM_statistics calculates the free-electron power spectrum and the cosmological dispersion measure (DM) statistics (such as its mean and variance, angular power spectrum and correlation function). The default cosmological parameters are consistent with the Planck 2015 LambdaCDM model; the cosmological model can be easily changed by editing a few lines of the C code.

[ascl:2106.029] EMBERS: Experimental Measurement of BEam Responses with Satellites

EMBERS provides a modular framework for radio telescopes and interferometric arrays such as the MWA, HERA, and the upcoming SKA-Low to accurately measure the all sky polarized beam responses of their antennas using weather and communication satellites. This tool enables astronomers and system engineers, all over the world, to characterize the in-situ antenna beam patterns of large arrays with ease.

[ascl:2106.028] FRBSTATS: A web-based platform for visualization of fast radio burst properties

FRBSTATS provides a user-friendly web interface to an open-access catalog of fast radio bursts (FRBs) published up to date, along with a highly accurate statistical overview of the observed events. The platform supports the retrieval of fundamental FRB data either directly through the FRBSTATS API, or in the form of a CSV/JSON-parsed database, while enabling the plotting of parameter distributions for a variety of visualizations. These features allow researchers to conduct more thorough population studies while narrowing down the list of astrophysical models describing the origins and emission mechanisms behind these sources. Lastly, the platform provides a visualization tool that illustrates associations between primary bursts and repeaters, complementing basic repeater information provided by the Transient Name Server.

[ascl:2106.027] MultiModeCode: Numerical exploration of multifield inflation models

MultiModeCode facilitates efficient Monte Carlo sampling of prior probabilities for inflationary model parameters and initial conditions and efficiently generates large sample-sets for inflation models with O(100) fields. The code numerically solves the equations of motion for the background and first-order perturbations of multi-field inflation models with canonical kinetic terms and arbitrary potentials, providing the adiabatic, isocurvature, and tensor power spectra at the end of inflation. For models with sum-separable potentials MultiModeCode also computes the slow-roll prediction via the δN formalism for easy model exploration and validation.

[ascl:2106.026] Katu: Interaction of particles in plasma simulator

Katu evolves the interaction of particles (photons, protons, neutrons, leptons, pions and neutrinos) in plasma. The package comes with wrappers for emcee (ascl:1303.002) and pymultinest (ascl:1606.005) for Bayesian analysis, making the software applicable to blazars and able to extract relevant statistical information from their electromagnetic (and neutrino, if applicable) flux. The code is optimized for fast performance, and can be easily modified and extended.

[ascl:2106.025] ModeChord: Primordial scalar and tensor power spectra solver

ModeChord computes the primordial scalar and tensor power spectra for single field inflationary models. The code solves the inflationary mode equations numerically, avoiding the slow roll approximation. It provides an efficient and robust numerical evaluation of the inflationary perturbation spectrum, and allows the free parameters in the inflationary potential to be estimated. ModeChord also allows the estimation of reheating uncertainties once a potential has been specified.

[ascl:2106.024] RedPipe: Reduction Pipeline

The RedPipe collection of Python scripts performs optical photometric and spectroscopic data reduction. There are scripts on preprocessing, photometry, calibration, spectroscopy, analysis and plotting. The photometry and spectroscopy codes use pyraf (ascl:1207.011) and hence require an already existing installation of Image Reduction and Analysis Facility (IRAF, ascl:9911.002).

[ascl:2106.023] so_noise_models: Simons Observatory N(ell) noise models

so_noise_models is the N(ell) noise curve projection code for the Simons Observatory. The code, written in pure Python, consists of several independent sub-modules, representing each version of the noise code. The usage of the models can vary substantially from version to version. The package also includes demo code that that demonstrates usage of the noise models, such as by producing noise curve plots, effective noise power spectra for SO LAT component-separated CMB T, E, B, and Compton-y maps, and lensing noise curves from SO LAT component-separated CMB T, E, B maps.

[ascl:2106.022] STaRS: Sejong Radiative Transfer through Raman and Rayleigh Scattering with atomic hydrogen

The 3D grid-based Monte Carlo code STaRS (Sejong Radiative Transfer through Raman and Rayleigh Scattering with atomic hydrogen) traces radiative transfer through Raman and Rayleigh scattering. This can be used to investigate line formation of Raman-scattered features in a thick neutral region illuminated by a strong far-UV emission source. Favorable conditions for Raman scattering with atomic hydrogen are easily met in symbiotic stars, young planetary nebulae, and active galactic nuclei.

[ascl:2106.021] aztekas: GRHD numerical code

aztekas solves hyperbolic partial differential equations in conservative form using High Resolution Shock-Capturing (HRSC) schemes. The code can solve the non-relativistic and relativistic hydrodynamic equations of motion (Euler equations) for a perfect fluid. The relativistic part can solve these equations on a background fixed metric, such as for Schwarzschild, Minkowski, Kerr-Schild, and others.

[ascl:2106.020] simple_reg_dem: Differential Emission Measures in the solar corona

simple_reg_dem reconstructs differential emission measures (DEMs) in the solar corona. It overcomes issues, such as complexity, idiosyncratic output, convergence difficulty, and lack of speed, that exists in other methods. Initially written for extreme ultraviolet (EUV) data, the algorithm is notable for its simplicity, and is robust and extensible to any other wavelengths (e.g., X-rays) where the DEM treatment is valid. It is available in the SolarSoft (ascl:1208.013) package.

[ascl:2106.019] GLEMuR: GPU-based Lagrangian mimEtic Magnetic Relaxation

GLEMuR (Gpu-based Lagrangian mimEtic Magnetic Relaxation) is a finite difference Lagrangian code which uses mimetic differential operators and runs on Nvidia GPUs. Its main purpose is to study the relaxation of magnetic relaxation in environments of zero resistivity and viscosity; it preserves the magnetic flux and the topology of magnetic field lines. The use of mimetic operators for the spatial derivatives improve accuracy for high distortions of the grid, and the final state of the simulation approximates a force-free state with a significantly higher accuracy. Note, however, that GLEMuR is not a general purpose equation solver and the full magnetohydrodynamics equations are not implemented.

[ascl:2106.017] redvsblue: Quasar and emission line redshift fitting

redvsblue measures a precise redshift given a broad redshift prior. For each emission line or the full spectrum, the software runs a coarse chi2 scan as a function of redshift, using the input PCA+broadband Legendre polynomials, and finds three local minima, and does a finer chi2 scan in each minima. It then defines the global PCA redshift (ZPCA) from the best minimum of the three; ZPCA is a redshift estimator biased toward the computation of the PCA. The redshift of the line (ZLINE) is defined from the maximum of the best-fit model of the line. ZLINE is a redshift estimator un-biased toward the velocity of the line, but can be biased with respect to the cosmological redshift. The output is a FITS file, with one HDU per redshift type.

[ascl:2106.016] QuasarNET: CNN for redshifting and classification of astrophysical spectra

QuasarNET is a deep convolutional neural network that performs classification and redshift estimation of astrophysical spectra with human-expert accuracy. It is trained on data of low signal-to-noise and medium resolution, typical of current and future astrophysical surveys, and could be easily applied to classify spectra from current and upcoming surveys such as eBOSS, DESI and 4MOST.

[ascl:2106.015] ATES: ATmospheric EScape

The ATES hydrodynamics code computes the temperature, density, velocity and ionization fraction profiles of highly irradiated planetary atmospheres, along with the current, steady-state mass loss rate. ATES solves the one-dimensional Euler, mass and energy conservation equations in
radial coordinates through a finite-volume scheme. The hydrodynamics module is paired with a photoionization equilibrium solver that includes cooling via bremsstrahlung, recombination and collisional excitation/ionization for the case of an atmosphere of primordial composition (i.e., pure atomic hydrogen-helium), while also accounting for advection of the different ion species.

[ascl:2106.014] Lemon: Linear integral Equations' Monte carlo solver based On the Neumann solution

Lemon solves the radiative transfer (RT) processes that contain scattering. These processes are described by differentio-integral equations with given initial or boundary conditions; Lemon solves these differentio-integral equations, which can be converted into the second kind integral equations of Fredholm. The code then obtains the Neumman solution (a series that consists of infinite terms of multiple integrals) from the Fredholm integral equation, and uses the Monte Carlo (MC) method to evaluate these integrals. Lemon is written in Fortran; IDL programs are included for plotting the results.

[ascl:2106.013] Kadath: Spectral solver

The Kadath library implements spectral methods in the context of theoretical physics. It is fully parallel; a sequential version can be installed. The library is written in C++, and solves a wide variety of problems. Several coordinates systems are implemented and additional geometries can be easily encoded. Partial differential equations of various types are discretized by means of spectral methods. The resulting system is solved using a Newton-Raphson iteration, allowing KADATH to deal with strongly non-linear situations. An optimized version of Kadath is available that improves memory management (reducing the number of uses of new and delete), inlines several member functions, and provides better management of the accessors for the arrays.

[ascl:2106.012] StarcNet: Convolutional neural network for classifying galaxy images into morphological classes

StarcNet (STAR Cluster classification NETwork) classifies star clusters from galaxy images taken by the Hubble Space Telescope (HST); it uses a convolutional neural network (CNN) trained to classify five-band galaxy images into four morphological classes. Written in PyTorch, StarcNet runs using mosaics (.fits files with the galaxy photometric information) and catalogs (.tab files with object coordinates), and includes the option to also download the galaxy mosaics from a single .tar.gz file per galaxy (as from the Legacy ExtraGalactic UV Survey).

[ascl:2106.011] MakeCloud: Turbulent GMC initial conditions for GIZMO

MakeCloud makes turbulent giant molecular cloud (GMC) initial conditions for GIZMO (ascl:1410.003). It generates turbulent velocity fields on the fly and stores that data in a user-specified path for efficiency. The code is flexible, allowing the user control through various parameters, including the radius of the cloud, number of gas particles, type of initial turbulent velocity (Gaussian or full), and magnetic energy as a fraction of the binding energy, among other options. With an additional file, it can also create glassy initial conditions.

[ascl:2106.010] Maneage: Managing data lineage

The Maneage (Managing data lineage; ending pronounced like "lineage") framework produces fully reproducible computational research. It provides full control on building the necessary software environment from a low-level C compiler, the shell and LaTeX, all the way up to the high-level science software in languages such as Python without a third-party package manager. Once the software environment is built, adding analysis steps is as easy as defining "Make" rules to allow parallelized operations, and not repeating operations that do not need to be recreated. Make provides control over data provenance. A Maneage'd project also contains the narrative description of the project in LaTeX, which helps prepare the research for publication. All results from the analysis are passed into the report through LaTeX macros, allowing immediate dynamic updates to the PDF paper when any part of the analysis has changed. All information is stored in plain text and is version-controlled in Git. Maneage itself is actually a Git branch; new projects start by defining a new Git branch over it and customizing it for a new project. Through Git merging of branches, it is possible to import infrastructure updates to projects.

[ascl:2106.009] baofit: Fit cosmological data to measure baryon acoustic oscillations

baofit analyzes cosmological correlation functions to estimate parameters related to baryon acoustic oscillations and redshift-space distortions. It has primarily been used to analyze Lyman-alpha forest autocorrelations and cross correlations with the quasar number density in BOSS data. Fit models are fully three-dimensional and include flexible treatments of redshift-space distortions, anisotropic non-linear broadening, and broadband distortions.

[ascl:2106.008] simqso: Simulated quasar spectra generator

simqso generates mock quasar spectra and photometry. Simulated quasar spectra are built from a series of components. Common quasar models are built-in, such as a broken power-law continuum model and Gaussian emission line templates; however, the code allows user-defined features to be included. Mock spectra are generated at arbitrary resolution and can be used to produce broadband photometry representative of a number of surveys.

[ascl:2106.007] CoMover: Bayesian probability of co-moving stars

CoMover determines the probability that two stars are co-moving and thus gravitationally bound. It uses the sky position, proper motion, parallax and optionally the heliocentric radial velocity of a host star (with their respective measurement errors), and compares it to the observables of a potential companion (with their respective measurement errors). The sky position and proper motion of the potential companion star are required, and its heliocentric radial velocity and parallax are facultative inputs to refine its co-moving probability.

If all kinematic observables of the host star are provided, a single spatial-kinematic model is built, consisting of a single 6-dimensional multivariate Gaussian in Galactic coordinates (XYZ) and space velocities (UVW). The observables of the potential companion are then compared to this model and a given field-stars model with Bayes' theorem by marginalizing over any missing kinematic observables of the companion star with analytical integral solutions. The field stars are modeled using a 10-component multivariate Gaussian, accurate for stars within a few hundred parsecs of the Sun. In the case where a heliocentric radial velocity is missing for the host star, the single host-star multivariate Gaussian model is replaced with a series of host star models and numerically marginalized over by taking the numerical sum of the host-star model probabilities.

[ascl:2106.006] Pyshellspec: Binary systems with circumstellar matter

Pyshellspec models binary systems with circumstellar matter (e.g. accretion disk, jet, shell), computes the interferometric observables |V2|, arg T3, |T3|, |dV|, and arg dV, and performs comparisons of light curves, spectro-interferometry, spectra, and SED with observations, and both global and local optimization of system parameters. The code solves the inverse problem of finding the stellar and orbital parameters of the stars and circumstellar medium. Pyshellspec is based on the long-characteristic LTE radiation transfer code Shellspec (ascl:1108.017).

[ascl:2106.005] Marvin: Data access and visualization for MaNGA

Marvin searches, accesses, and visualizes data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. Written in Python, it provides tools for easy efficient interaction with the MaNGA data via local files, files retrieved from the Science Archive Server, or data directly grabbed from the database. The tools come mainly in the form of convenience functions and classes for interacting with the data. Also available is a web app, Marvin-web, offers an easily accessible interface for searching the MaNGA data and visual exploration of individual MaNGA galaxies or of the entire sample, and a powerful query functionality that uses the API to query the MaNGA databases and return the search results to your python session. Marvin-API is the critical link that allows Marvin-tools and Marvin-web to interact with the databases, which enables users to harness the statistical power of the MaNGA data set.

[ascl:2106.004] crowdsource: Crowded field photometry pipeline

crowdsource removes a rough sky (the median), find the brighter peaks and fits these sources, computes centroids, and then computes an improved PSF. With this model of the image, the code then iteratively subtracts it and recomputes the median to get a better sky estimate, finds fainter peaks, and calculates a better PSF. crowdsource performs at least four iterations, evaluates the results, and continues until certain thresholds are met. Once the iterative passes are complete, it makes one last pass. If no sources are detected and positions do not vary, it performs photometry for the existing list of stellar positions.

[ascl:2106.003] PyDoppler: Wrapper for Doppler tomography software

PyDoppler is a python-based wrapper for the Spruit Doppler tomography software dopmap (ascl:2106.002). PyDoppler is designed to study time-resolved spectroscopic datasets of accreting compact binaries. This code can produce a trail spectra of a dataset and create Doppler tomography maps. It is intended to be a light-weight code for single emission line datasets.

[ascl:2106.002] dopmap: Fast Doppler mapping program

dopmap constructs Doppler maps from the orbital variation of line profiles of (mass transferring) binaries. It uses an algorithm related to Richardson-Lucy iteration and includes an IDL-based set of routines for manipulating and plotting the input and output data.

[ascl:2106.001] KOBE: Kepler Observes Bern Exoplanets

KOBE (Kepler Observes Bern Exoplanets) adds the geometrical limitations and the physical detection biases of the transit method to a given population of theoretical planets. In addition, it also adds the completeness and reliability of a transit survey.

[ascl:2105.022] PFITS: Spectra data reduction

PFITS performs data reduction of spectra, including dark removal and flat fielding; this software was a standard 1983 Reticon reduction package available at the University of Texas. It was based on the plotting program PCOSY by Gary Ferland, and in 1985 was updated by Andrew McWilliam.

[ascl:2105.021] Kepler's Goat Herd: Solving Kepler's equation via contour integration

Kepler's Goat Herd solves Kepler's equation using contour integration to solve the "geometric goat problem". The C++ code implements a variety of solution: 1.) Newton-Raphson: The quadratic Newton-Raphson root finder; 2.) Danby: The quartic root; 3.) Series: An elliptical series method; and 4.) Contour: A new method based on contour integration. Given an array of mean anomalies, an eccentricity and a desired precision, the code estimates the eccentric anomaly using each method. The accuracy of each approach is increased until the desired precision is reached, and timing is performed using the C++ chrono package.

[ascl:2105.020] PAP: PHANGS-ALMA pipeline

The PHANGS-ALMA pipeline process data from radio interferometer observations. It uses CASA (ascl:1107.013), AstroPy (ascl:1304.002), and other affiliated packages to process data from calibrated visibilities to science-ready spectral cubes and maps. The PHANGS-ALMA pipeline offers a flexible alternative to the scriptForImaging script distributed by ALMA. The pipeline runs in two separate software environments: CASA 5.6 or 5.7 (staging, imaging and post-processing) and Python 3.6 or later (derived products) with modern versions of several packages.

[ascl:2105.019] RandomQuintessence: Integrate the Klein-Gordon and Friedmann equations with random initial conditions

RandomQuintessence integrates the Klein-Gordon and Friedmann equations for quintessence models with random initial conditions and functional forms for the potential. Quintessence models generically impose non-trivial structure on observables like the equation of state of dark energy. There are three main modules; montecarlo_nompi.py sets initial conditions, loops over a bunch of randomly-initialised models, integrates the equations, and then analyses and saves the resulting solutions for each model. Models are defined in potentials.py; each model corresponds to an object that defines the functional form of the potential, various model parameters, and functions to randomly draw those parameters. All of the equation-solving code and methods to analyze the solution are kept in solve.py under the base class DEModel(). Other files available analyze and plot the data in a variety of ways.

[ascl:2105.018] ClaRAN: Classifying Radio sources Automatically with Neural networks

ClaRAN (Classifying Radio sources Automatically with Neural networks) classifies radio source morphology based upon the Faster Region-based Convolutional Neutral Network (Faster R-CNN). It is capable of associating discrete and extended components of radio sources in an automated fashion. ClaRAN demonstrates the feasibility of applying deep learning methods for cross-matching complex radio sources of multiple components with infrared maps. The promising results from ClaRAN have implications for the further development of efficient cross-wavelength source identification, matching, and morphology classifications for future radio surveys.

[ascl:2105.017] Pyrat Bay: Python Radiative Transfer in a Bayesian framework

Pyrat Bay computes radiative-transfer spectra and fits exoplanet atmospheric properties, and is an efficient, user-friendly Python tool. The package offers transmission or emission spectra of exoplanet transit or eclipses respectively and forward-model or retrieval calculations. The radiative-transfer includes opacity sources from line-by-line molecular absorption, collision-induced absorption, Rayleigh scattering absorption, and more, including Gray aerosol opacities. Pyrat Bay's Bayesian (MCMC) posterior sampling of atmospheric parameters includes molecular abundances, temperature profile, pressure-radius, and Rayleigh and cloud properties.

[ascl:2105.016] CUDAHM: MCMC sampling of hierarchical models with GPUs

CUDAHM accelerates Bayesian inference of Hierarchical Models using Markov Chain Monte Carlo by constructing a Metropolis-within-Gibbs MCMC sampler for a three-level hierarchical model, requiring the user to supply only a minimimal amount of CUDA code. CUDAHM assumes that a set of measurements are available for a sample of objects, and that these measurements are related to an unobserved set of characteristics for each object. For example, the measurements could be the spectral energy distributions of a sample of galaxies, and the unknown characteristics could be the physical quantities of the galaxies, such as mass, distance, or age. The measured spectral energy distributions depend on the unknown physical quantities, which enables one to derive their values from the measurements. The characteristics are also assumed to be independently and identically sampled from a parent population with unknown parameters (e.g., a Normal distribution with unknown mean and variance). CUDAHM enables one to simultaneously sample the values of the characteristics and the parameters of their parent population from their joint posterior probability distribution.

[ascl:2105.015] PyTorchDIA: Difference Image Analysis tool

PyTorchDIA is a Difference Image Analysis tool. It is built around the PyTorch machine learning framework and uses automatic differentiation and (optional) GPU support to perform fast optimizations of image models. The code offers quick results and is scalable and flexible.

[ascl:2105.014] encore: Efficient isotropic 2-, 3-, 4-, 5- and 6-point correlation functions

encore (Efficient N-point Correlator Estimation) estimates the isotropic NPCF multipoles for an arbitrary survey geometry in O(N2) time, with optional GPU support. The code features support for the isotropic 2PCF, 3PCF, 4PCF, 5PCF and 6PCF, with the option to subtract the Gaussian 4PCF contributions at the estimator level. For the 4PCF, 5PCF and 6PCF algorithms, the runtime is dominated by sorting the spherical harmonics into bins, which has complexity O(N_galaxy x N_bins3 x N_ell5) [4PCF], O(N_galaxy x N_bins4 x N_ell8) [5PCF] or O(N_galaxy x N_bins5 x N_ell11) [6PCF]. The higher-point functions are slow to compute unless N_bins and N_ell are small.

[ascl:2105.013] SISPO: Imaging simulator for small solar system body missions

SISPO (Space Imaging Simulator for Proximity Operations) simulates trajectories, light parameters, and camera intrinsic parameters for small solar system body fly-by and terrestrial planet surface missions. The software provides realistic surface rendering and realistic dust- and gas-environment optical models for comets and active asteroids and also simulates common image aberrations such as simple geometric distortions and tangential astigmatism. SISPO uses Blender and its Cycles rendering engine, which provides physically based rendering capabilities and procedural micropolygon displacement texture generation.

[ascl:2105.012] orvara: Orbits from Radial Velocity, Absolute, and/or Relative Astrometry

orvara (Orbits from Radial Velocity, Absolute, and/or Relative Astrometry) fits orbits of bright stars and their faint companions (exoplanets, brown dwarfs, white dwarfs, and low-mass stars). It can use any combination of radial velocity, relative astrometry, and absolute astrometry data and offers a variety of plots from the orbital fit, such as the radial velocity orbit over an extended time baseline, position angle between two companions, and a density plot of the predicted position at a chosen epoch. orvara can also check convergence of fitted parameters in the HDU1 extension, save the results from the fitted and inferred parameters from the HDU1 extension, and plot the results of a three-body or multiple-body fit.

[ascl:2105.011] BlackBOX: BlackGEM and MeerLICHT image reduction software

BlackBOX performs standard CCD image reduction tasks on multiple images from the BlackGEM and MeerLICHT telescopes. It uses the satdet module of ASCtools (ascl:2011.024) and Astro-SCRAPPY (ascl:1907.032). BlackBOX simultaneously uses multi-processing and multi-threading and feeds the reduced images to ZOGY (ascl:2105.010) to ultimately perform optimal image subtraction and detect transient sources.

[ascl:2105.010] ZOGY: Python implementation of proper image subtraction

ZOGY performs optimal image subtraction; the code is designed specifically for the MeerLICHT and BlackGEM pipelines, but should also be useful to apply to images of other telescopes. The module accepts a new and a reference FITS image, runs SExtractor (ascl:1010.064) on them, and finds their WCS solution using Astrometry.net (ascl:1208.001). ZOGY then uses PSFex (ascl:1301.001) to infer the position-dependent PSFs of the images and SWarp (ascl:1010.068) to map the reference image to the new image and performs optimal image subtraction. This produces the subtracted image, the significance image, the corrected significance image, and the PSF photometry image and associated error image. The inferred PSFs are also used to extract optimal photometry of all sources detected by SExtractor.

[ascl:2105.009] MeerCRAB: Transient classifier using a deep learning model

MeerCRAB (MeerLICHT Classification of Real and Bogus Transients using Deep Learning) filters out false detections of transients from true astrophysical sources in the transient detection pipeline of the MeerLICHT telescope. It uses a deep learning model based on Convolutional Neural Network.

[ascl:2105.008] MCALF: Velocity information from spectral imaging observations

MCALF (Multi-Component Atmospheric Line Fitting) accurately constrains velocity information from spectral imaging observations using machine learning techniques. It is useful for solar physicists trying to extract line-of-sight (LOS) Doppler velocity information from spectral imaging observations (Stokes I measurements) of the Sun. A toolkit is provided that can be used to define a spectral model optimized for a particular dataset. MCALF is particularly suited for extracting velocity information from spectral imaging observations where the individual spectra can contain multiple spectral components. Such multiple components are typically present when active solar phenomenon occur within an isolated region of the solar disk. Spectra within such a region will often have a large emission component superimposed on top of the underlying absorption spectral profile from the quiescent solar atmosphere.

[ascl:2105.007] SpheCow: Galaxy and dark matter halo dynamical properties

SpheCow explores the structure and dynamics of any spherical model for galaxies and dark matter haloes. The lightweight and flexible code automatically calculates the dynamical properties, assuming an isotropic or Osipkov-Merritt anisotropic orbital structure, of any model with either an analytical density profile or an analytical surface density profile as a starting point. SpheCow contains readily usable implementations for many standard models, including the Plummer, Hernquist, NFW, Einasto, Sérsic and Nuker models. The code is easily extendable, allowing new models to be added in a straightforward way. The code is publicly available as a set of C++ routines and as a Python module.

[ascl:2105.006] The Sequencer: Detect one-dimensional sequences in complex datasets

The Sequencer reveals the main sequence in a dataset if one exists. To do so, it reorders objects within a set to produce the most elongated manifold describing their similarities which are measured in a multi-scale manner and using a collection of metrics. To be generic, it combines information from four different metrics: the Euclidean Distance, the Kullback-Leibler Divergence, the Monge-Wasserstein or Earth Mover Distance, and the Energy Distance. It considers different scales of the data by dividing each object in the input data into separate parts (chunks), and estimating pair-wise similarities between the chunks. It then aggregates the information in each of the chunks into a single estimator for each metric+scale.

[ascl:2105.005] COMPAS: Rapid binary population synthesis code

COMPAS (Compact Object Mergers: Population Astrophysics & Statistics) draws properties for a binary star system from a set of initial distributions and evolves it from zero-age main sequence to the end of its life as two compact remnants. Evolution prescriptions and model parameters are easily adjustable in the software. COMPAS has been used for inference from observations of gravitational-wave mergers, Galactic neutron stars, X-ray binaries, and luminous red novae.

[ascl:2105.004] TesseRACt: Tessellation-based Recovery of Amorphous halo Concentrations

TesseRACt computes concentrations of simulated dark matter halos from volume information for particles generated using Voronoi tesselation. This technique is advantageous as it is non-parametric, does not assume spherical symmetry, and allows for the presence of substructure. TesseRACt accepts data in a number of formats, including Gadget-2 (ascl:0003.001), Gasoline (ascl:1710.019), and ASCII, and computes concentrations using particles volumes, traditional fitting to an NFW profile, and non-parametric techniques that assume spherical symmetry.

[ascl:2105.003] ATARRI: A TESS Archive RR Lyrae Classifier

ATARRI is a graphical user interface for downloading TESS Full Frame Images (FFIs) and displaying properties of the lightcurves of selected objects. Preliminary analysis is performed assuming the object is an RR Lyrae variable. The raw lightcurve, a Lomb-Scargle analysis (both full and pre-whitened), and a folded lightcurve are presented to the user along with options to select the type of RR Lyrae and data quality flags for output.

[ascl:2105.002] PDM2: Phase Dispersion Minimization

PDM2 (Phase Dispersion Minimization) ddetermines periodic components of data sets with erratic time intervals, poor coverage, non-sine-wave curve shape, and/or large noise components. Essentially a least-squares fitting technique, the fit is relative to the mean curve as defined by the means of each bin; the code simultaneously obtains the best least-squares light curve and the best period. PDM2 allows an arbitrary degree of smoothing and provides improved curve fits, suppressed subharmonics, and beta function statistics.

[ascl:2105.001] BHPToolkit: Black Hole Perturbation Toolkit

The Black Hole Perturbation Toolkit models gravitational radiation from small mass-ratio binaries as well as from the ringdown of black holes. The former are key sources for the future space-based gravitational wave detector LISA. BHPToolkit brings together core elements of multiple scattered black hole perturbation theory codes into a Toolkit that can be used by all; different tools can be installed individually by users depending on need and interest.

[submitted] Py-PDM: A Python wrapper of the Phase Dispersion Minimization (PDM)

Phase Dispersion Minimization (PDM) is a periodical signal detection method, and it is originally implemented by Stellingwerf with C (https://www.stellingwerf.com/rfs-bin/index.cgi?action=PageView&id=34). With the help of Cython, Py-PDM is much faster than other Python implementations.

[ascl:2104.031] Posidonius: N-Body simulator for planetary and/or binary systems

Posidonius is a N-body code based on the tidal model used in Mercury-T (ascl:1511.020). It uses the REBOUND (ascl:1110.016) symplectic integrator WHFast to compute the evolution of positions and velocities, which is also combined with a midpoint integrator to calculate the spin evolution in a consistent way. As Mercury-T, Posidonius takes into account tidal forces, rotational-flattening effects and general relativity corrections. It also includes different evolution models for FGKML stars and gaseous planets. The N-Body code is written in Rust; a Python package is provided to easily define simulation cases in JSON format, which is readable by the Posidonius integrator.

[ascl:2104.030] lofti_gaiaDR2: Orbit fitting with Gaia astrometry

Lofti_gaia fits orbital parameters for one wide stellar binary relative to the other, when both objects are resolved in Gaia DR2. It takes as input only the Gaia DR2 source id of the two components, and their masses. It retrieves the relevant parameters from the Gaia archive, computes observational constraints for them, and fits orbital parameters to those measurements. It assumes the two components are bound in an elliptical orbit.

[ascl:2104.029] TES: Terrestrial Exoplanet Simulator

TES models the evolution of exoplanet systems. This n-body integration package comes in two parts, the C++ TES source code, and the Python-based experiment manager for running experiments and plotting the results. The experiment manager, used as the interface to TES, handles temporary data storage and allows for experiment results to be saved and then loaded later on for plotting. The experiment manager can automatically use multiple threads to run independent experiments in parallel using the mpi4py package. The experiment manager is specifically designed to enable HPC to be performed as easily as possible.

[ascl:2104.028] globalemu: Global (sky-averaged) 21-cm signal emulation

globalemu emulates the Global or sky averaged 21-cm signal and the associated neutral fraction history. The code can train a network on your own Global 21-cm signal or neutral fraction simulations using the built-in globalemu pre-processing techniques. It also features a GUI that can be invoked from the command line and used to explore how the structure of the Global 21-cm signal varies with the values of the astrophysical inputs.

[ascl:2104.027] linemake: Line list generator

linemake generates formatted and curated atomic and molecular line lists suitable for spectral synthesis work. It is lightweight and easy-to-use. The code requires that the requested beginning and ending wavelengths not bridge the divide between two files of atomic line data; in such cases, run the code twice, once on either side of the divide, to generate the desired lists.

[ascl:2104.026] Skye: Equation of state for fully ionized matter

The Skye framework develops and prototypes new EOS physics; it is not tied to a specific set of physics choices and can be extended for new effects by writing new terms in the free energy. It takes into account the effects of positrons, relativity, electron degeneracy, and non-linear mixing effects and more, and determines the point of Coulomb crystallization in a self-consistent manner. It is available in the MESA (ascl:1010.083) EOS module and as a standalone package.

[ascl:2104.025] SpaceHub: High precision few-body and large scale N-body simulations

SpaceHub uses unique algorithms for fast precise and accurate computations for few-body problems ranging from interacting black holes to planetary dynamics. This few-body gravity integration toolkit can treat black hole dynamics with extreme mass ratios, extreme eccentricities and very close encounters. SpaceHub offers a regularized Radau integrator with round off error control down to 64 bits floating point machine precision and can handle extremely eccentric orbits and close approaches in long-term integrations.

[ascl:2104.024] GAMMA: Relativistic hydro and local cooling on a moving mesh

GAMMA models relativistic hydrodynamics and non-thermal emission on a moving mesh. It uses an arbitrary Lagrangian-Eulerian approach only in the dominant direction of fluid motion to avoid mesh entanglement and associated computational costs. Shock detection, particle injection and local calculation of their evolution including radiative cooling are done at runtime. The package is modular; though it was designed with GRB physics applications in mind, new solvers and geometries can be implemented easily, making GAMMA suitable for a wide range of applications.

[ascl:2104.023] PyBird: Python code for biased tracers in redshift space

PyBird evaluates the multipoles of the power spectrum of biased tracers in redshift space. In general, PyBird can evaluate the power spectrum of matter or biased tracers in real or redshift space. The code uses FFTLog (ascl:1512.017) to evaluate the one-loop power spectrum and the IR resummation. PyBird is designed for a fast evaluation of the power spectra, and can be easily inserted in a data analysis pipeline. It is a standalone tool whose input is the linear matter power spectrum which can be obtained from any Boltzmann code, such as CAMB (ascl:1102.026) or CLASS (ascl:1106.020). The Pybird output can be used in a likelihood code which can be part of the routine of a standard MCMC sampler. The design is modular and concise, such that parts of the code can be easily adapted to other case uses (e.g., power spectrum at two loops or bispectrum). PyBird can evaluate the power spectrum either given one set of EFT parameters, or independently of the EFT parameters. If the former option is faster, the latter is useful for subsampling or partial marginalization over the EFT parameters, or to Taylor expand around a fiducial cosmology for efficient parameter exploration.

[ascl:2104.022] RadioFisher: Fisher forecasting for 21cm intensity mapping and spectroscopic galaxy surveys

RadioFisher is a Fisher forecasting code for cosmology with intensity maps of the redshifted 21cm emission line of neutral hydrogen. It uses CAMB (ascl:1102.026) to produce a high-resolution P(k) for the fiducial cosmology when the code is first run and caches the results, making subsequent runs faster and more efficient. It includes specifications for a large number of experiments, as well as survey parameters and the fiducial cosmological parameters, and can run a forecast for a galaxy redshift survey rather than an IM survey. RadioFisher also contains a number of options for plotting results.

[ascl:2104.021] cmblensplus: Cosmic microwave background tools

cmblensplus reconstructs lensing potential, cosmic bi-refringence, and patchy reionization from cosmic microwave background anisotropies (CMB) in full and flat sky. This Fortran wrapper for Python also includes modules for delensing and bi-spectrum calculations. cmblensplus contains a module of basic routines such as analytic calculation of delensed B-mode spectrum and lensing bispectrum. Two additional main modules are for curved sky and flat sky analyses, and measure lensing, bi-refringence, patchy tau, bias-hardening, bi-spectrum, delensing and analytic reconstruction normalization. The package also contains simple Python utility and demonstration scripts. cmblensplus uses FFTW (ascl:1201.015), HEALPix (ascl:1107.018), LAPACK (ascl:2104.020), CFITSIO (ascl:1010.001), and LensPix (ascl:1102.025).

[ascl:2104.020] LAPACK: Linear Algebra PACKage

LAPACK provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related computations such as reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision. The list of LAPACK Contributors is available online.

[ascl:2104.019] SpectRes: Simple spectral resampling

SpectRes efficiently resamples spectra and their associated uncertainties onto an arbitrary wavelength grid. The Python function works with any grid of wavelength values, including non-uniform sampling, and preserves the integrated flux. This may be of use for binning data to increase the signal to noise ratio, obtaining synthetic photometry, or resampling model spectra to match the sampling of observational data.

[ascl:2104.018] GGchem: Fast thermo-chemical equilibrium code

GGchem is a fast thermo-chemical equilibrium code with or without equilibrium condensation down to 100K. It can handle up to 40 elements (H, ..., Zr, and W), up to 1155 molecules, and up to 200 condensates (solids and liquids) from NIST-JANAF and SUPCRTBL. It offers a customized selection of elements, molecules, and condensates. The Fortran-90 code is very fast, and has a stable iterative solution scheme based on Newton-Raphson.

[ascl:2104.017] Bagpipes: Bayesian Analysis of Galaxies for Physical Inference and Parameter EStimation

Bagpipes generates realistic model galaxy spectra and fits these to spectroscopic and photometric observations.

[ascl:2104.016] Skyoffset: Sky offset optimization and mosaicing toolkit

Skyoffset makes wide-field mosaics of FITS images. Principal features of Skyoffset are the ability to produce a mosaic with a continuous background level by solving for sky offsets that minimize the intensity differences between overlapping images, and its handling of hierarchies, making it ideal for optimizing backgrounds in large mosaics made with array cameras (such as CFHT’s MegaCam and WIRCam). Skyoffset uses MongoDB in conjunction with Mo’Astro (ascl:2104.012) to store metadata about each mosaic and SWarp (ascl:1010.068) to handle image combination and propagate uncertainty maps. Skyoffset can be integrated into Python pipelines and offers a convenient API and metadata storage in MongoDB. It was developed originally for the Andromeda Optical and Infrared Disk Survey (ANDROIDS).

[ascl:2104.015] dense_basis: Dense Basis SED fitting

dense_basis implements the Dense Basis method tailored to SED fitting, in particular, the task of recovering accurate star formation history (SFH) information from galaxy spectral energy distributions (SEDs). The code's original use-case was simultaneously fitting specific large catalogs of galaxies; it is adapted to a general purpose SED fitting code, and acts as a module to compress and decompress SFHs and other time-series.

[ascl:2104.014] SSSpaNG: Stellar Spectra as Sparse Non-Gaussian Processes

SSSpaNG is a data-driven Gaussian Process model of the spectra of APOGEE red clump stars, whose parameters are inferred using Gibbs sampling. By pooling information between stars to infer their covariance it permits clear identification of the correlations between spectral pixels. Harnessing this correlation structure, a complete spectrum for each red clump star can be inferred, inpainting missing regions and de-noising by a factor of at least 2-3 for low-signal-to-noise stars.

[ascl:2104.013] pfits: PSRFITS-format data file processor

pfits reads, manipulates and processes PSRFITS format search- and fold-mode pulsar astronomy data files. It summerizes the header information in a PSRFITS file, reproduces some of fv's (ascl:1205.005) functionality, and allows the user to obtain detailed information about the file. It can determine whether the data is search mode or fold mode and plot the profile, color scale image, frequency time, sum in frequency, and 4-pol data, as appropriate. pfits can also read in a search mode file, dedisperses, and frequency-sums (if requested), and offers an option to output multiple dispersed data files, among other tasks.

[ascl:2104.012] Mo'Astro: MongoDB framework for observational astronomy

Mo’Astro is a MongoDB framework for observational astronomy pipelines. Mo'Astro sets up a MongoDB collection of a survey's image set, keeping FITS metadata readily available, and providing a place in the reduction pipeline to persist metadata. Mo’Astro also provides facilities for batch processing images with the Astromatic tool suite, and for hosting a local 2MASS star catalog with spatial-search built-in.

[ascl:2104.011] Freeture: Free software to capTure meteors

FreeTure monitors images from GigE all-sky cameras to detect and record falling stars and fireball. Originally, it was developed for the FRIPON (Fireball Recovery and InterPlanetary Observation Network) project, which sought to cover all of France with 100 fish eyes cameras, but can be used by any station that has a GigE camera.

[submitted] Ulula: a lightweight 2D hydro code for teaching

Ulula is an ultra-lightweight 2D hydro code for teaching purposes. The code is written in pure python and is designed to be as short and easy to understand as possible, while not compromising on performance. The latter is achieved with a simple Godunov solver and by using numpy for all array operations.

[ascl:2104.010] OpTool: Command-line driven tool for creating complex dust opacities

Optool computes dust opacities and scattering matrices, for specific grain sizes or averaged over size distributions. It is derived from OpacityTool (ascl:2104.009) and implements the Distribution of Hollow Spheres (DHS) statistical method to approximate irregular and low porosity grains. Mie theory is available as a limiting case of DHS. It also implements the Tazaki Modified Mean Field Theory (MMF) to treat fractal and highly porous aggregates. The refractive index data for many astronomically relevant materials are compiled into the code, and external refractive index data can be used as well. A compact and intuitive command line interface makes it easy to construct complex particles on the fly. Available output formats are ASCII and FITS, including files directly readable by RADMC-3D (ascl:1202.015). A python interface to the FORTRAN program is included.

[ascl:2104.009] OpacityTool: Dust opacities for disk modeling

OpacityTool computes dust opacities for disc modelling; it includes a number of robust facts obtained from observations and theory and goes beyond astronomical silicates. It provides output files with κext(λ),κabs(λ),κsca(λ) as a function of wavelength λ, and the 6 scattering matrix elements for randomly oriented particles, F11(λ,θ), F12(λ,θ), F22(λ,θ), F33(λ, θ), F34(λ, θ), F44(λ, θ) as functions of wavelength and scattering angle θ.

This code is superseded by optool (ascl:2104.010).

[ascl:2104.008] LaFuLi: NASA Langley Fu-Liou radiative transfer code

The NASA Langley Fu-Liou radiative transfer code (also known as Ed4 LaRC Fu-Liou) computes broadband solar shortwave and thermal long wave profiles of down-welling and up-welling flux accounting for gas absorption by H2O, CO2, O3, O2, CH4, N2O and CFCs and absorption and scattering by clouds and aerosols. Longwave has options of a four-stream or 2/4 stream solver, while shortwave has options for two-stream, four-stream or Gamma weighted two-stream (GWTSA) which treats the inhomogeniety of cloud optical depth. A delta-Eddington approximation is used to treat the forward scattering peak. Water cloud properties are based on Mie calculations and ice cloud properties or the ice particle aspect ratio. Aerosol properties are given for 25 types.

[ascl:2104.007] EPIC5: Lindblad orbits in ovally perturbed potentials

EPIC5 computes positions, velocities and densities along closed orbits of interstellar matter, including frictional forces, in a galaxy with an arbitrary perturbing potential. Radial velocities are given for chosen lines of sight. These are analytic gas orbits in an arbitrary rotating galactic potential using the linear epicyclic approximation

[ascl:2104.006] RJObject: Reversible Jump Objects

RJObject provides a general approach to trans-dimensional Bayesian inference problems, using trans-dimensional MCMC embedded within a Nested Sampling algorithm. This allows exploration of the posterior distribution and calculattion of the marginal likelihood (summed over N) even if the problem contains a phase transition or other difficult features such as multimodality.

[ascl:2104.005] CTR: Coronal Temperature Reconstruction

CTR (Coronal Temperature Reconstruction) reconstructs differential emission measures (DEMs) in the solar corona. Written in IDL, the code guarantees positivity of the recovered DEM, enforces an explicit smoothness constraint, returns a featureless (flat) solution in the absence of information, and converges quickly. The algorithm is robust and can be extended to other wavelengths where the DEM treatment is valid.

[ascl:2104.004] Spectractor: Spectrum extraction tool for slitless spectrophotometry

Spectractor extracts spectra from slitless spectrophotometric images and measures the atmospheric transmission on the line of sight if standard stars are targeted. It has been optimized on CTIO images but can be configured to analyze any kind of slitless data that contains the order 0 and the order 1 of a spectrum. In particular, it can be used to estimate the atmospheric transmission of the Vera Rubin Observatory site using the dedicated Auxiliary Telescope.

[ascl:2104.003] Hilal-Obs: Authentication agorithm for new moon visibility report

Hilal-Obs authenticates lunar crescent first visibility reports. The code, written in Python, uses PyEphem (ascl:1112.014) for astrometrics, and takes into account all the factors that affect lunar crescent visibility, including atmospheric extinction, observer physiology, sky and lunar brightness, contrast threshold, and the type of observation.

[ascl:2104.002] Librarian: The HERA Librarian

The HERA Librarian system keeps track of all the primary data products for the telescope at a given site. The Librarian supports large data volumes and automated data processing capabilities. A web-based application handles human user and automatic requests and interfaces with a backing database and data storage servers. The system supports the long-term data storage of all relevant telescope data, as well as staging data to individual users' directories for processing.

[ascl:2104.001] hera_opm: The HERA Online Processing Module

The hera_opm package provides a convenient and flexible framework for developing data analysis pipelines for operating on a sequence of input files. Though developed for application to the Hydrogen Epoch of Reionization Array (HERA), it is a general package that can be applied to any workflow designed to apply a series of analysis steps to any type of files. It is also portable, operating both on a diversity of computer clusters with batch submission systems and local machines.

[ascl:2103.031] CARTA: Cube Analysis and Rendering Tool for Astronomy

CARTA (Cube Analysis and Rendering Tool for Astronomy) is a image visualization and analysis tool designed for the ALMA, VLA, SKA pathfinders, and the ngVLA. If offers catalog support, shared region analytics, profile smoothing, and spectral line query, and more. CARTA adopts a client-server architecture suitable for visualizing images with large file sizes (GB to TB) easily obtained from ALMA, VLA, or SKA pathfinder observations; computation and data storage are handled by remote enterprise-class servers or clusters with high performance storage, while processed products are sent to clients only for visualization with modern web features, such as GPU-accelerated rendering. This architecture also enables users to interact with the ALMA and VLA science archives by using CARTA as an interface. CARTA provides a desktop version and a server version. The former is suitable for single-user usage with a laptop, a desktop, or a remote server in the "remote" execution mode. The latter is suitable for institution-wide deployment to support multiple users with user authentication and additional server-side features.

[ascl:2103.030] DIAPHANE: Library for radiation and neutrino transport in hydrodynamical simulations

DIAPHANE provides a common platform for application-independent radiation and neutrino transport in astrophysical simulations. The library contains radiation and neutrino transport algorithms for modeling galaxy formation, black hole formation, and planet formation, as well as supernova stellar explosions. DIAPHANE is written in C and C++, but as many hydrodynamic codes use Fortran, the library includes examples of how to interface the library from the Fortran codes SPHYNX (ascl:1709.001) and RAMSES (ascl:1011.007).

[ascl:2103.029] SparseBLS: Box-Fitting Least Squares implementation for sparse data

SparseBLS uses the Box-fitting Least Squares (BLS) algorithm to detect transiting exoplanets in photometric data. SparseBLS does not bin data into phase bins and does not use a phase grid. Because its detection efficiency does not depend on the transit phase, it is significantly faster than BLS for sparse data and is well-suited for large photometric surveys producing unevenly-sampled sparse light curves, such as Gaia.

[ascl:2103.028] Astro-Fix: Correcting astronomical bad pixels in Python

astrofix is an astronomical image correction algorithm based on Gaussian Process Regression. It trains itself to apply the optimal interpolation kernel for each image, performing multiple times better than median replacement and interpolation with a fixed kernel.

[ascl:2103.027] GalLenspy: Reconstruction of mass profile in disc-like galaxies from the gravitational lensing effect

Gallenspy uses the gravitational lensing effect (GLE) to reconstruct mass profiles in disc-like galaxies. The algorithm inverts the lens equation for gravitational potentials with spherical symmetry, in addition to the estimation in the position of the source, given the positions of the images produced by the lens. Gallenspy also computes critical and caustic curves and the Einstein ring.

[ascl:2103.026] PyPion: Post-processing code for PION simulation data

PyPion reads in Silo (ascl:2103.025) data files from PION (ascl:2103.024) simulations and plots the data. This library works for 1D, 2D, and 3D data files and for any amount of nested-grid levels. The scripts contained in PyPion save the options entered into the command line when the python script is run, open the silo file and save all of the important header variables, open the directory in the silo (or vtk, or fits) file and save the requested variable data (eg. density, temp, etc.), and set up the plotting function and the figure.

[ascl:2103.025] Silo: Saving scientific data to binary disk files

Silo reads and writes a wide variety of scientific data to binary disk files. The files Silo produces and the data within them can be easily shared and exchanged between wholly independently developed applications running on disparate computing platforms. Consequently, Silo facilitates the development of general purpose tools for processing scientific data. One of the more popular tools that process Silo data files is the VisIt visualization tool (ascl:1103.007).

Silo supports gridless (point) meshes, structured meshes, unstructured-zoo and unstructured-arbitrary-polyhedral meshes, block structured AMR meshes, constructive solid geometry (CSG) meshes, piecewise-constant (e.g., zone-centered) and piecewise-linear (e.g. node-centered) variables defined on the node, edge, face or volume elements of meshes as well as the decomposition of meshes into arbitrary subset hierarchies including materials and mixing materials. In addition, Silo supports a wide variety of other useful objects to address various scientific computing application needs. Although the Silo library is a serial library, it has features that enable it to be applied quite effectively and scalable in parallel.

[ascl:2103.024] PION: Computational fluid-dynamics package for astrophysics

PION (PhotoIonization of Nebulae) is a grid-based fluid dynamics code for hydrodynamics and magnetohydrodynamics, including a ray-tracing module for calculating the attenuation of radiation from point sources of ionizing photons. It also has a module for coupling fluid dynamics and the radiation field to microphysical processes such as heating/cooling and ionization/recombination. PION models the evolution of HII regions, photoionized bubbles that form around hot stars, and has been extended to include stellar wind sources so that both wind bubbles and photoionized bubbles can be simulated at the same time. It is versatile enough to be extended to other applications.

[ascl:2103.023] DRAKE: Relic density in concrete models prediction

DRAKE (Dark matter Relic Abundance beyond Kinetic Equilibrium) predicts the dark matter relic abundance in situations where the standard assumption of kinetic equilibrium during the freeze-out process may not be satisfied. The code comes with a set of three dedicated Boltzmann equation solvers that implement, respectively, the traditionally adopted equation for the dark matter number density, fluid-like equations that couple the evolution of number density and velocity dispersion, and a full numerical evolution of the phase-space distribution.

[ascl:2103.022] nestle: Nested sampling algorithms for evaluating Bayesian evidence

nestle is a pure Python implementation of nested sampling algorithms for evaluating Bayesian evidence. Nested sampling integrates posterior probability in order to compare models in Bayesian statistics. It is similar to Markov Chain Monte Carlo (MCMC) in that it generates samples that can be used to estimate the posterior probability distribution. Unlike MCMC, the nature of the sampling also allows one to calculate the integral of the distribution. It is also a pretty good method for robustly finding global maxima.

[ascl:2103.021] Carsus: Atomic database for astronomy

Carsus manages atomic datasets. It requires Chianti (ascl:9911.004), and can read data from a variety of sources and output them to file formats readable by radiative transfer codes such as TARDIS (ascl:1402.018).

[ascl:2103.020] ARTIS: 3D Monte Carlo radiative transfer code for supernovae

ARTIS is a 3D radiative transfer code for Type Ia supernovae using the Monte Carlo method with indivisible energy packets. It incorporates polarization and virtual packets and non-LTE physics appropriate for the nebular phase of Type Ia supernovae.

[ascl:2103.019] SUPERNU: Radiative transfer code for explosive outflows using Monte Carlo methods

SuperNu simulates time-dependent radiation transport in local thermodynamic equilibrium with matter. It applies the methods of Implicit Monte Carlo (IMC) and Discrete Diffusion Monte Carlo (DDMC) for static or homologously expanding spatial grids. The radiation field affects material temperature but does not affect the motion of the fluid. SuperNu may be applied to simulate radiation transport for supernovae with ejecta velocities that are not affected by radiation momentum. The physical opacity calculation includes elements from Hydrogen up to Cobalt. SuperNu is motivated by the ongoing research into the effect of variation in the structure of progenitor star explosions on observables: the brightness and shape of light curves and the temporal evolution of the spectra. Consequently, the code may be used to post-process data from hydrodynamic simulations. SuperNu does not include any capabilities or methods that allow for non-trivial hydrodynamics.

[ascl:2103.018] GalacticDNSMass: Bayesian inference determination of mass distribution of Galactic double neutron stars

GalacticDNSMass performs Bayesian inference on Galactic double neutron stars (DNS) to investigate their mass distribution. Each DNS is comprised of two neutron stars (NS), a recycled NS and a non-recycled (slow) NS. It compares two hypotheses: A - recycled NS and non-recycled NS follow an identical mass distribution, and B - they are drawn from two distinct populations. Within each hypothesis it also explore three possible functional models: Gaussian, two-Gaussian (mixture model), and uniform mass distributions.

[ascl:2103.017] CRIME: Cosmological Realizations for Intensity Mapping Experiments

CRIME (Cosmological Realizations for Intensity Mapping Experiments) generates mock realizations of intensity mapping observations of the neutral hydrogen distribution. It contains three separate tools, GetHI, ForGet, and JoinT. GetHI generates realizations of the temperature fluctuations due to the 21cm emission of neutral hydrogen. Optionally it can also generate a realization of the point-source continuum emission (for a given population) by sampling the same density distribution, though using this feature greatly affects performance. ForGet generates realizations of the different galactic and extra-galactic foregrounds relevant for intensity mapping experiments using some external datasets (e.g. the Haslam 408 MHz map) stored in the "data"folder. JoinT is provided for convenience; it joins the temperature maps generated by GetHI and ForGet and includes several instrument-dependent effects (in an overly simplistic way).

[ascl:2103.016] RAiSERed: Analytic AGN model based code for radio-frequency redshifts

The RAiSERed (Radio AGN in Semi-analytic Environments: Redshifts) code implements the RAiSE analytic model for Fanaroff-Riley type II sources, using a Bayesian prior for their host cosmological environments, to measure the redshift of active galactic nuclei lobes based on radio-frequency observations. The Python code provides a class for the user to store measured attributes for each radio source, and to which model derived redshift probability density functions are returned. Systematic uncertainties in the analytic model can be calibrated by specifying a subset of radio sources with spectroscopic redshifts. Functions are additionally provided to plot the redshift probability density functions and assess the success of the model calibration.

[ascl:2103.015] LPF: Real-time detection of transient sources in radio data streams

LPF (Live Pulse Finder) provides real-time automated analysis of the radio image data stream at multiple frequencies. The fully automated GPU-based machine-learning backed pipeline performs source detection, association, flux measurement and physical parameter inference. At the end of the pipeline, an alert of a significant detection of a transient event can be sent out and the data saved for further investigation.

[ascl:2103.014] QuickCBC: Rapid and reliable inference for binary mergers

QuickCBC is a robust end-to-end low-latency Bayesian parameter estimation algorithm for binary mergers. It reads in calibrated strain data, performs robust on-source spectral estimation, executes a rapid search for compact binary coalescence (CBC) signals, uses wavelet de-noising to subtract any glitches from the search residuals, produces low-latency sky maps and initial parameter estimates, followed by full Bayesian parameter estimation.

[ascl:2103.013] schNell: Fast calculation of N_ell for GW anisotropies

schNell computes basic map-level noise properties for generic networks of gravitational wave interferometers, primarily the noise power spectrum "N_ell", but this lightweight python module that can also be used for, for example, antenna patterns, overlap functions, and inverse variance maps, among other tasks. The code has three main classes; detectors contain information about each individual detector of the network, such as their positions, noise properties, and orientation. NoiseCorrelations describes the noise-level correlation between pairs of detectors, and the MapCalculators class combines a list of Detectors into a network (potentially together with a NoiseCorrelation object) and computes the corresponding map-level noise properties arising from their correlations.

[ascl:2103.012] AstroNet-Triage: Neural network for TESS light curve triage

AstroNet-Triage contains TensorFlow models and data processing code for identifying exoplanets in astrophysical light curves; this is the triage version of two TESS neural networks. For the vetting version, see AstroNet-Vetting (ascl:2103.011). The TensorFlow code downloads and pre-processes TESS data, builds different types of neural network classification models, trains and evaluates new models, and generates new predictions using a trained model. Utilities that operate on light curves are provided; these reading TESS data from .h5 files, and perform phase folding, splitting, binning, and other tasks. C++ implementations of some light curve utilities are also included.

[ascl:2103.011] AstroNet-Vetting: Neural network for TESS light curve vetting

AstroNet-Vetting identifies exoplanets in astrophysical light curves. This is the vetting version of two TESS neural networks; for the triage version, see AstroNet-Triage (ascl:2103.012). The package contains TensorFlow code that downloads and pre-processes TESS data, builds different types of neural network classification models, trains and evaluates a new model, and uses a trained model to generate new predictions. It includes utilities for operating on light curves, such as for reading TESS data from .h5 files, phase folding, splitting, and binning. In addition, C++ implementations of light curve utilities are also provided.

[ascl:2103.010] TransitFit: Exoplanet transit fitting package for multi-telescope datasets

TransitFit fits exoplanetary transit light-curves for transmission spectroscopy studies. The code uses nested sampling for efficient and robust multi-epoch, multi-wavelength fitting of transit data obtained from one or more telescopes. TransitFit allows per-telescope detrending to be performed simultaneously with parameter fitting, including the use of user-supplied detrending alogorithms. Host limb darkening can be fitted either independently ("uncoupled") for each filter or combined ("coupled") using prior conditioning from the PHOENIX stellar atmosphere models. For this, TransitFit uses the Limb Darkening Toolkit (ascl:1510.003) together with filter profiles, including user-supplied filter profiles.

[ascl:2103.009] DarkEmulator: Cosmological emulation code for halo clustering statistics

The cosmology code DarkEmulator calculates summary statistics of large scale structure constructed as a part of Dark Quest Project. The “dark_emulator” python package enables fast and accurate computations of halo clustering quantities. The code supports the halo mass function, halo-matter cross-correlation, and halo auto-correlation as a function of halo masses, redshift, separations and cosmological models.

[submitted] MRS: The MOS Reduction Software

The MRS (The MOS Reduction Software) suite reduces the spectra taken with the multi-object spectrograph spectra used as the focal plane instrument of RTT150 telescope in the TÜBİTAK National Observatory.

[submitted] ObsPlanner

Simple program for planning and managing astronomical observations as observational diary or logs.

[ascl:2103.008] Pyedra: Python implementation for asteroid phase curve fitting

Pyedra performs asteroid phase curve fitting. From a simple table containing the asteroid MPC number, phase angle and reduced magnitude, Pyedra estimates the parameters of the phase function using the least squares method. The user can choose from three different models for the phase curve fit: H-G model, H-G1-G2 model and the Shevchenko model. The output in all cases is a table containing the adjusted parameters and their corresponding errors. This package allows carrying out phase function analysis for a few asteroids as well as to process large volumes of data such as those released by current large surveys.

[ascl:2103.007] TFF: Template Fourier Fitting

TFF derives the Fourier decomposition of period-folded RR Lyrae light curves with gaps. The method can be used for the same purpose on any other types of variables, assuming that the the template database is changed to the proper type of variables.

[ascl:2103.006] ggm: Gaussian gradient magnitude filtering of astronomical images

Ggm contains useful utilities for Gaussian gradient filtering of astronomical FITS images. It applies the Gaussian gradient magnitude filter to an input fits image, using a particular scale, sigma, in pixels. ggm cosmetically hides point sources in fits images by filling point sources with random values from the surrounding pixel region. It also provides an interactive tool to combine FITS images filtered on different scales.

[ascl:2103.005] satcand: Orbital stability and tidal migration constraints for KOI exomoon candidates

satcand applies theoretical constraints of orbital stability and tidal migration to KOI exomoon candidates. The package can evaluate the tidal migration within a Sun-Earth-Moon system, plot angular velocity over time, and calculate the migration time scale (T1) and the total migration time scale, among other things. In addition to the theoretical constraints, observational constraints can be applied.

[submitted] Deep Embedded Clustering for Open Cluster Characterization with Gaia DR2 Data

Characterize and understandOpen Clusters(OCs) allow us to understand better properties and mechanisms about the Universe such as stellar formation and the regions where these events occur. They also provide information about stellar processes and the evolution of the galactic disk.

In this paper, we present a novel method to characterize OCs. Our method employs a model built on Artificial Neural Networks(ANNs). More specifically, we adapted a state of the art model, the Deep Embedded Clustering(DEC) model for our purpose. The developed method aims to improve classical state of the arts techniques. We improved not only in terms of computational efficiency (with lower computational requirements), but inusability (reducing the number of hyperparameters to get a good characterization of the analyzed clusters). For our experiments, we used the Gaia DR2 database as the data source, and compared our model with the clustering technique K-Means. Our method achieves good results, becoming even better (in some of the cases) than current techniques.

[ascl:2103.004] redshifts: Spectroscopic redshifts search tool

redshifts collects all unique spectroscopic redshifts from online databases such as VizieR and NED. It can perform a flexible search within a radius of a given set of (RA, DEC) coordinates and uses column names and descriptions (including UCD keywords) to identify columns containing spectroscopic redshifts or velocities. It weeds out photometric redshifts and duplicates and returns a unique list of best spectroscopic redshift measurements. redshifts can be used standalone from the terminal, and can take a number of optional command line arguments, or from Python.

[ascl:2103.003] spalipy: Detection-based astronomical image registration

spalipy performs detection-based astronomical image registration in Python. A source image is transformed to the pixel-coordinate system of a template image using their respective detections as tie-points by finding matching quads of detections. spalipy also includes an optional additional warping of the initial affine transformation via splines to achieve accurate registration in the case of non-homogeneous coordinate transforms. This is particularly useful in the case of optically distorted or wide field-of-view images.

[ascl:2103.002] hfs_fit: Atomic emission spectral line hyperfine structure fitting

hfs_fit performs parameter optimization in the analysis of emission line hyperfine structure (HFS). The code uses a simulated annealing algorithm to optimize the magnetic dipole interaction constants, electric quadrupole interaction constants, Voigt profile widths and the center of gravity wavenumber for a given emission line profile. The fit can be changed visually with sliders for parameters, which is useful when HFS constants are unknown.

[ascl:2103.001] 21cmDeepLearning: Matter density map extractor

21cmDeepLearning extracts the underlying matter density map from a 21 cm intensity field by making use of a convolutional neural network (CNN) with the U-Net architecture; the software is implemented in Pytorch. The astrophysical parameters of the simulations can be predicted with a secondary CNN. The simulations of matter density and 21 cm maps are performed with the code 21cmFAST (ascl:1102.023).

[submitted] synchrofit: Python-based synchrotron spectral fitting

The synchrofit (synchrotron fitter) package implements a reduced dimensionality parameterisation of standard synchrotron spectrum models, and provides fitting routines applicable for active galactic nuclei and supernova remnants. The Python code includes the Jaffe-Parola model (JP), Kardashev-Pacholczyk model (KP), and continuous injection models (CI/KGJP) for both constant or Maxwell-Boltzmann magnetic field distributions. An adaptive maximum likelihood algorithm is invoked to fit these models to multi-frequency radio observations; the adaptive mesh is customisable for either optimal precision or computational efficiency. Functions are additionally provided to plot the fitted spectral model with its confidence interval, and to derive the spectral age of the synchrotron emitting particles.

[submitted] U.S. Naval Observatory Ephemerides of the Largest Asteroids (USNO/AE98)

USNO/AE98 contains ephemerides for fifteen of the largest asteroids that The Astronomical Almanac has used since its 2000 edition. These ephemerides are based on the Jet Propulsion Laboratory (JPL) planetary ephemeris DE405 and, thus, aligned to the International Celestial Reference System (ICRS). The data cover the period from 1799 November 16 (JD 2378450.5) through 2100 February 1 (JD 2488100.5). The internal uncertainty in the mean longitude at epoch, 1997 December 18, ranges from 0.05 arcseconds for 7 Iris through 0.22 arcseconds for 65 Cybele, and the uncertainty in the mean motion varies from 0.02 arcseconds per century for 4 Vesta to 0.14 arcseconds per century for 511 Davida.

The Astronomical Almanac has published ephemerides for 1 Ceres, 2 Pallas, 3 Juno, and 4 Vesta since its 1953 edition. Historically, these four asteroids have been observed more than any of the others. Ceres, Pallas, and Vesta deserve such attention because as they are the three most massive asteroids, the source of significant perturbations of the planets, the largest in linear size, and among the brightest main belt asteroids. Studying asteroids may provide clues to the origin and primordial composition of the solar system, data for modeling the chaotic dynamics of small solar system bodies, and assessments of potential collisions. Therefore, USNO/AE98 includes more than the traditional four asteroids.

The following criteria were used to select main belt asteroids for USNO/AE98:

Diameter greater than 300 km, presumably among the most massive asteroids
Excellent observing history and discovered before 1850
Largest in their taxonomic class
The massive asteroids included may be studied for their perturbing effects on the planets while those with detailed observing histories may be used to evaluate the accuracy limits of asteroid ephemerides. The fifteen asteroids that met at least one of these criteria are

1 Ceres (new mass determination)
2 Pallas (new mass determination)
3 Juno
4 Vesta (new mass determination)
6 Hebe
7 Iris
8 Flora
9 Metis
10 Hygiea
15 Eunomia
16 Psyche
52 Europa
65 Cybele
511 Davida
704 Interamnia
The refereed paper by Hilton (1999, Astron. J. 117, 1077) describes the USNO/AE98 asteroid ephemerides in detail. The associated USNO/AA Tech Note 1998-12 includes residual plots for all fifteen asteroids and a comparison between these ephemerides and those used in The Astronomical Almanac through 1999.

Software to compact, read, and interpolate the USNO/AE98 asteroid ephemerides is also available. It is written in C and designed to work with the C edition of the Naval Observatory Vector Astrometry Software (NOVAS). The programs could be used with tabular ephemerides of other asteroids as well. The associated README file provides the details of this system.

[submitted] FLARE: Synthetic Fast Radio Burst catalog generator

FLARE, a parallel code written in Python, generates 100,000 Fast Radio Bursts (FRB) using the Monte Carlo method. The FRB population is diverse and includes sporadic FRBs, repeaters, and periodic repeaters. However, less than 200 FRBs have been detected to date, which makes understanding the FRB population difficult. To tackle this problem, FLARE uses a Monte Carlo method to generate 100,000 realistic FRBs, which can be analyzed later on for further research. It has the capability to simulate FRB distances (based on the observed FRB distance range), energies (based on the "flaring magnetar model" of FRBs), fluences, multi-wavelength counterparts (based on x-ray to radio fluence ratio of FRB 200428), and other properties. It analyzes the resulting synthetic FRB catalog and displays the distribution of their properties. It is fast (as a result of parallel code) and requires minimal human interaction. FLARE is, therefore, able to give a broad picture of the FRB population.

[ascl:2102.030] GLEAM: Galaxy Line Emission and Absorption Modeling

GLEAM (Galaxy Line Emission and Absorption Modeling) fits Gaussian models to emission and absorption lines in large samples of 1D galaxy spectra. The code is tailored to work well without much human interaction on optical and infrared spectra in a wide range of instrument setups and signal-to-noise regimes. gleam will create a fits table with Gaussian line measurements, including central wavelength, width, height and amplitude, as well as estimates for the continuum under the line and the line flux, luminosity, equivalent width and velocity width. gleam will also, optionally, make plots of the spectrum with fitted lines overlaid.

[ascl:2102.029] BALRoGO: Bayesian Astrometric Likelihood Recovery of Galactic Objects

BALRoGO (Bayesian Astrometric Likelihood Recovery of Galactic Objects) handles data from the Gaia space mission. It extracts galactic objects such as globular clusters and dwarf galaxies from data contaminated by interlopers using a combination of Bayesian and non-Bayesian approaches. It fits proper motion space, surface density, and the object center. It also provides confidence regions for the color-magnitude diagram and parallaxes.

[ascl:2102.028] PyAutoFit: Classy probabilistic programming

PyAutoFit supports advanced statistical methods such as massively parallel non-linear search grid-searches, chaining together model-fits and sensitivity mapping. It is a Python-based probabilistic programming language which composes and fits models using a range of Bayesian inference libraries, such as emcee (ascl:1303.002) and dynesty (ascl:1809.013). It performs model composition and customization, outputting results, model-specific visualization and posterior analysis. Built for big-data analysis, results are output as a database which can be loaded after model-fitting is complete.

[ascl:2102.027] PyFstat: Continuous gravitational-wave data analysis

PyFstat performs F-statistic-based continuous gravitational wave (CW) searches and other CW data analysis tasks. It is built on top of the LALSuite library (ascl:2012.021), making that library's functionality more accessible through a Python interface; it also provides MCMC-based followup of promising candidates from wide-parameter-space searches.

[ascl:2102.026] extinction: Dust extinction laws

extinction is an implementation of fast interstellar dust extinction laws in Python. It contains Cython-optimized implementations of empirical dust extinction laws found in the literature. Flux values can be reddened or dereddened using included functions, and all extinction laws accept a unit keyword to change the interpretation of the wavelength array from Angstroms to inverse microns. Part of this code originated in the specutils package (ascl:1902.012).

[ascl:2102.025] binaryoffset: Detecting and correcting the binary offset effect in CCDs

binaryoffset identifies the binary offset effect in images from any detector. The easiest input to work with is a dark or bias image that is spatially flat. The code can also be run on images that are not spatially flat, assuming that there is some model of the signal on the CCD that can be used to produce a residual image.

[ascl:2102.024] Piff: PSFs In the Full FOV

Piff models the point-spread function (PSF) across multiple detectors in the full field of view (FOV). Models can be built in chip coordinates or in sky coordinates if needed to account for the effects of astrometric distortion. The software can fit in either real or Fourier space, and can identify and excise outlier stars that are poor exemplars of the PSF according to some metric.

[ascl:2102.023] Multi_CLASS: Cross-tracer angular power spectra of number counts using CLASS

Multi_CLASS modifies the Boltzmann code CLASS (ascl:1106.020) to compute of the cross-tracer angular power spectra of the number count fluctuations for two different tracers of the underlying dark matter density field. In other words, it generalizes the standard nCl output option of CLASS to the case of two different tracers, for example, two different galaxy populations with their own redshift distribution, and galaxy and magnification bias parameters, among others.

Multi_CLASS also includes an implementation of the effect of primordial non-Gaussianities of the local type, parametrized by the parameter f_NL (following the large-scale structure convention), on the effective bias of the tracers. There is also the possibility of having a tilted non-Gaussian correction, parametrized by n_NG, with a pivot scale determined by k_pivot_NG. The package includes galaxy redshift distributions for forthcoming galaxy surveys, with the ease of choosing between them (or an input file) from the parameters input file (e.g., multi_explanatory.ini). In addition, Multi_CLASS includes the possibility of using resolved gravitational wave events as a tracer.

[ascl:2102.022] RASSINE: Normalizing 1D stellar spectra

RASSINE normalizes merged 1D spectra using the concept of convex hulls. The code uses six parameters that can be fine-tuned, and provides an interactive interface, including graphical feedback, for easily choosing the parameters. RASSINE can also provide a first guess for the parameters that are derived directly from the merged 1D spectrum based on previously performed calibrations.

[ascl:2102.021] lensingGW: Lensing of gravitational waves

lensingGW simulates lensed gravitational waves in ground-based interferometers from arbitrary compact binaries and lens models. Its algorithm resolves strongly lensed images and microimages simultaneously, such as the images resulting from hundreds of microlenses embedded in galaxies and galaxy clusters. It is based on Lenstronomy (ascl:1804.012),

[ascl:2102.020] MOSAIC: Multipole operator generator for Fast Multipole Method operators

MOSAIC (Multipole Operators in Symbols, Automatically Improved and Condensed) automatically produces, verifies, and optimizes computer code for Fast Multipole Method (FMM) operators. It is based on a symbolic algebra library, and can produce code for any expansion order and be extended to use any basis or kernel function. The code applies algebraic modifications to reduce the number of floating-point operations and can symbolically verify correctness.

[ascl:2102.019] HUAYNO: Hierarchically split-Up AstrophYsical N-body sOlver N-body code

HUAYNO implements integrators derived from second order Hamiltonian splitting for N-body dynamics. This integration scheme conserves energy and momentum with little or no systematic drift. The code uses an explicit but approximate formula for the time symmetrization that is compatible with the use of individual time steps, making an iterative scheme unnecessary. HUAYNO is available as part of the AMUSE package (ascl:1107.007).

[ascl:2102.018] DaMaSCUS-SUN: Dark Matter Simulation Code for Underground Scatterings - Sun Edition

DaMaSCUS-SUN is a Monte Carlo tool simulating the process of solar reflection of dark matter (DM) particles. It provides precise estimates of the DM particle flux reflected by the Sun and passing through a direct detection experiment on Earth. One application is to compute exclusion limits for low DM masses based on nuclear and electron recoil experiments.

[ascl:2102.017] mirkwood: SED modeling using machine learning

mirkwood uses supervised machine learning to model non-linearly mapping galaxy fluxes to their properties. Multiple models are stacked to mitigate poor performance by any individual model in a given region of the parameter space. The code accounts for uncertainties arising both from intrinsic noise in observations and from finite training data and incorrect modeling assumptions, and provides highly accurate physical properties from observations of galaxies as compared to traditional SED fitting.

[ascl:2102.016] OPUS: Interoperable access to analysis and simulation codes

OPUS (Observatoire de Paris UWS System) provides interoperable access to analysis and simulation codes on local machines or work clusters. This job control system was developed using the micro-framework bottle.py, and executes jobs asynchronously to better manage jobs with a long execution duration. The software follows the proposed IVOA Provenance Data Model to capture and expose the provenance information of jobs and results.

[ascl:2102.015] ForwardDiff: Forward mode automatic differentiation for Julia

ForwardDiff implements methods to take derivatives, gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really) using forward mode automatic differentiation (AD).While performance can vary depending on the functions you evaluate, the algorithms implemented by ForwardDiff generally outperform non-AD algorithms in both speed and accuracy.

[ascl:2102.014] nway: Bayesian cross-matching of astronomical catalogs

nway is a source cross-matching tool for arbitrarily many astronomical catalogs. It features Bayesian match probabilities based on astronomical sky coordinates (RA, DEC), works with arbitrarily many catalogs, and can handle varying errors. nway can also incorporate additional prior information, such as the magnitude or color distributions of the sources to match, and works accurately and fast in small areas and all-sky catalogs.

[ascl:2102.013] GalRotpy: Parametrize the rotation curve and gravitational potential of disk-like galaxies

GalRotpy models the dynamical mass of disk-like galaxies and makes a parametric fit of the rotation curve by means of the composed gravitational potential of the galaxy. It can be used to check the presence of an assumed mass type component in a observed rotation curve, to determine quantitatively the main mass contribution in a galaxy by means of the mass ratios of a given set of five potentials, and to bound the contribution of each mass component given its gravitational potential parameters.

[ascl:2102.012] MUSE-PSFR: PSF reconstruction for MUSE WFM-AO mode

MUSE-PSFR reconstructs a PSF for the MUSE WFM-AO mode using telemetry data from SPARTA. The algorithm conducts a Fourier analysis of the laser-assisted ground layer adaptive optics (GLAO) residual phase statistics and has been test in end-to-end simulations. A sensitivity analysis was conducted to determine the required accuracy in terms of input parameters. MUSE-PSFR is capable of reconstructing the critical parameters of a PSF and can be used with MUSE 3D data by all MUSE users.

[ascl:2102.011] polgraw-allsky: All-sky almost-monochromatic gravitational-wave pipeline

polgraw-allsky searches for almost monochromatic gravitational wave signals. This pipeline searches for continuous gravitational wave signals in time-domain data using the F-statistic on data from a network of detectors. The software generates a parameter space grid, conducts a coherent search for candidate signals in narrowband time segments, and searches for coincidences among different time segments. The pipeline also estimates the false alarm probability of coincidences and follows up on interesting outliers.

[ascl:2102.010] hardCORE: Exoplanet core radius fractions calculator

hardCORE calculates the minimum, maximum, and marginal core radius fractions (CRFmin, CRFmax, CRFmarg) for a solid exoplanet using only its mass and radius. Written in Python, the code is an efficient tool that is extremely fast to execute and perform inversions.

[ascl:2102.009] EqTide: Equilibrium Tide calculations

EqTide calculates the evolution of 2 bodies experiencing tidal evolution according to the "equilibrium tide" framework's "constant-phase-lag" and "constant-time-lag" models. The input file contains a list of options that can be set, as well as output parameters that print to a file during an integration. The example input files provide a guide for the syntax and grammar of EqTide.

[ascl:2102.008] CMasher: Scientific colormaps for making accessible, informative plots

CMasher provides a curated collection of scientific colormaps that are perceptually uniform sequential using the viscm package (ascl:2102.007). Most of them are color-vision deficiency friendly; they cover a wide range of different color combinations to accommodate for most applications. The package provides several alternatives to commonly used colormaps, such as chroma and rainforest for jet, sunburst for hot, neutral for binary, and fusion and redshift for coolwarm.

[ascl:2102.007] viscm: Colormaps analyzer and creator

viscm is a Python tool for visualizing and designing colormaps using colorspacious and matplotlib.

[ascl:2102.006] Lightbeam: Simulate light through weakly-guiding waveguides

Lightbeam simulates the 3D propagation of light through waveguides of arbitrary geometries. This code package is based off of the finite-differences beam propagation method, and employs a transverse adaptive mesh for extra computational efficiency. Also included are tools to simulate adaptive optics systems for use in conjunction with waveguides, useful in astronomical contexts for simulating coupling devices which transfer telescope light to the science instrument.

[submitted] The NASA Goddard Exoplanet Modeling and Analysis Center

The Exoplanet Modeling and Analysis Center (EMAC) is a website which serves as a catalog, repository and integration platform for modeling and analysis resources focused on the study of exoplanet characteristics and environments. EMAC hosts user-submitted software ranging in category from planetary interior models to data visualization tools. Other features of EMAC include integrated web tools developed by the EMAC team in collaboration with the tools' original authors and video demonstrations of a growing number of hosted tools. EMAC aims to be a comprehensive repository for researchers to access a variety of exoplanet resources that can assist them in their work, and currently hosts a growing number of code bases, models, and tools. EMAC is a key project of the NASA GSFC Sellers Exoplanet Environments Collaboration (SEEC).

[ascl:2102.005] X-PSI: X-ray Pulse Simulation and Inference

X-PSI simulates rotationally-modified (pulsed) surface X-ray emission from neutron stars, taking into account relativistic effects on the emitted radiation. This can then be used to perform Bayesian statistical inference on real or simulated astronomical data sets. Model parameters of interest may include neutron star mass and radius (useful to constrain the properties of ultradense nuclear matter) or the system geometry and properties of the hot emitting surface-regions. To achieve this, X-PSI couples code for likelihood functionality (simulation) with existing open-source software for posterior sampling (inference).

[ascl:2102.004] ThumbStack: Map and profile stacking pipeline

ThumbStack produces stacked maps and profiles, given catalogs of object positions and maps. It is designed for thermal and kinematic Sunyaev-Zel'dovich measurements. Based on Pixell (ascl:2102.003), it outputs 2D stacked maps and radial profiles for different filters (e.g., aperture photometry filters), as well as their covariances, estimated through several methods including bootstrap.

[ascl:2102.003] Pixell: Rectangular pixel map manipulation and harmonic analysis library

Pixell loads, manipulates, and analyzes maps stored in rectangular pixelization. It is mainly targeted for use with maps of the sky (e.g., CMB intensity and polarization maps, stacks of 21 cm intensity maps, binned galaxy positions or shear) in cylindrical projection, but its core functionality is more general. It extends numpy's ndarray to an ndmap class that associates a World Coordinate System (WCS) with a numpy array. It includes tools for Fourier transforms (through numpy or pyfft) and spherical harmonic transforms (through libsharp2 (ascl:1402.033)) of such maps and tools for visualization (through the Python Image Library).

[ascl:2102.002] MST: Minimum Spanning Tree algorithm for identifying large-scale filaments

MST (Minimum Spanning Tree) identifies velocity coherent large-scale filaments through ATLASGAL clumps. It can also isolate filaments embedded in a crowded position–position–velocity (PPV) space. One strength of this method is its repeatability compared to manual approaches.

[ascl:2102.001] spinOS: SPectroscopic and INterferometric Orbital Solution finder

spinOS calculates binary orbital elements. Given a set of radial velocity measurements of a spectroscopic binary and/or relative position measurement of an astrometric binary, spinOS fits an orbital model by minimizing a chi squared metric. These routines are neatly packaged in a graphical user interface, developed using tkinter, facilitating use. Minimization is achieved by default using a Levenberg-Marquardt algorithm from lmfit [ascl:1606.014]. A Markov Chain Monte Carlo option is available to sample the posterior probability distribution in order to estimate errors on the orbital elements.

[ascl:2101.018] stratsi: Stratified streaming instability

Stratsi calculates stratified and vertically-shearing streaming instabilities. It solves one- and two-fluid linearized equations, and, for two-fluid models, also provides the parameters and analytic vertical structure and solves for equilibrium horizontal velocity profiles. It offers utilities and various plotting options, including plots to compare one- and two-fluid results, viscous results to inviscid results, and results from two different stokes numbers or two different metallicities. stratsi requires Dedalus (ascl:1603.015) and Eigentools (ascl:2101.017).

[ascl:2101.017] Eigentools: Tools for studying linear eigenvalue problems

Eigentools is a set of tools for studying linear eigenvalue problems. The underlying eigenproblems are solved using Dedalus (ascl:1603.015), which provides a domain-specific language for partial differential equations. Eigentools extends Dedalus's EigenvalueProblem object and provides automatic rejection of unresolved eigenvalues, simple plotting of specified eigenmodes and of spectra, and computation of $\epsilon$-pseudospectra for any Differential-Algebraic Equations with user-specifiable norms. It includes tools to find critical parameters for linear stability analysis and is able to project eigenmode onto 2- or 3-D domain for visualization. It can also output projected eigenmodes as Dedalus-formatted HDF5 file to be used as initial conditions for Initial Value Problems, and provides simple plotting of drift ratios (both ordinal and nearest) to evaluate tolerance for eigenvalue rejection.

[ascl:2101.016] pyUPMASK: Unsupervised clustering method for stellar clusters

pyUPMASK is an unsupervised clustering method for stellar clusters that builds upon the original UPMASK (ascl:1504.001) package. Its general approach makes it applicable to analyses that deal with binary classes of any kind, as long as the fundamental hypotheses are met. The core of the algorithm follows the method developed in UPMASK but introducing several key enhancements that make it not only more general, they also improve its performance.

[ascl:2101.015] DarpanX: X-ray reflectivity of multilayer mirrors

DarpanX computes reflectivity and other specular optical functions of a multilayer or single layer mirror for different energy and angles as well as to fit the XRR measurements of the mirrors. It can be used as a standalone package. It has also been implemented as a local module for XSPEC (ascl:9910.005), which is accessible through and requires PyXspec (ascl:2101.014), and can accurately fit experimentally measured X-ray reflectivity data. DarpanX is implemented as a Python 3 module and an API is provided to access the underlying algorithms.

[ascl:2101.014] PyXspec: Python interface to XSPEC spectral-fitting program

PyXspec is an object oriented Python interface to the XSPEC (ascl:9910.005) spectral-fitting program. It provides an alternative to Tcl, the sole scripting language for standard Xspec usage. With PyXspec loaded, a user can run Xspec with Python language scripts or interactively at a Python shell prompt; everything in PyXspec is accessible by importing the package xspec into your Python script. PyXspec can be utilized in a Python script or from the command line of the plain interactive Python interpreter. PyXspec does not implement its own command handler, so it is not intended to be run as the Python equivalent of a traditional interactive XSPEC session (which is really an enhanced interactive Tcl interpreter).

[ascl:2101.013] Curvit: Create light curves from UVIT data

Curvit produces light curves from UVIT (Ultraviolet Imaging Telescope) data. It uses the events list from the official UVIT L2 pipeline (version 6.3 onwards) as input. The makecurves function of curvit automatically detects sources from events list and creates light curves. Curvit provides source coordinates only in the instrument coordinate system. If you already have the source coordinates, the curve function of curvit can be used to create light curves. The package has several parameters that can be set by the user; some of these parameters have default values. Curvit is available on PyPI.

[ascl:2101.012] Octo-Tiger: HPX parallelized 3-D hydrodynamic code for stellar mergers

Octo-Tiger models mass transfer in binary systems using a Cartesian adaptive mesh refinement grid. It simulates the evolution of star systems based on a modified fast multipole method (FMM) on adaptive octrees. The code takes shock heating into account and uses the dual energy formalism with an ideal gas equation of state; it also conserves linear and angular momenta to machine precision. Octo-Tiger is implemented in C++ and is parallelized using the High Performance ParalleX (HPX) runtime system.

[ascl:2101.011] Nigraha: Find and evaluate planet candidates from TESS light curves

Nigraha identifies and evaluates planet candidates from TESS light curves. Using a combination of high signal to noise ratio (SNR) shallow transits, supervised machine learning, and detailed vetting, the neural network-based pipeline identifies planet candidates missed by prior searches. The pipeline runs in four stages. It first performs period finding using the Transit Least Squares (TLS) package and runs sector by sector to build a per-sector catalog. It then transforms the flux values in .fits lightcurve files to global/local views and write out the output in .tfRecords files, builds a model on training data, and saves a checkpoint. Finally, it loads a previously saved model to generate predictions for new sectors. Nigraha provides helper scripts to generate candidates in new sectors, thus allowing others to perform their own analyses.

[ascl:2101.010] apogee: Tools for APOGEE data

The apogee package works with SDSS-III APOGEE and SDSS-IV APOGEE-2 data. It reads various data products and applies cuts, works with APOGEE bitmasks, and plots APOGEE spectra. It can generate model spectra for APOGEE spectra, and APOGEE model grids can be used to fit spectra. apogee includes some simple stacking functions and implements the effective selection function for APOGEE.

[ascl:2101.009] cFS: core Flight System

cFS is a platform and project independent reusable software framework and set of reusable applications developed by NASA Goddard Space Flight Center. There are three key aspects to the cFS architecture: a dynamic run-time environment, layered software, and a component based design, making it suitable for reuse on NASA flight projects and/or embedded software systems. This framework is used as the basis for the flight software for satellite data systems and instruments, but can also be used on other embedded systems. Modules of this package are used in NICER (Neutron star Interior Composition Explorer). The modules are available as separate downloads from SourceForge through the NASA cFS website.

[ascl:2101.008] EphemMatch: Ephemeris matching of DR25 TCEs, KOIs, and EBs for false positive identification

EphemMatch reads in the period, epoch, positional, and other information of all the Kepler DR25 TCEs, as well as the cumulative KOI list, and lists of EBs from the Kepler Eclipsing Binary Working Group (http://keplerebs.villanova.edu) as well as several catalogs of EBs known from ground-based surveys. The code then performs matching to identify two different objects that have a statistically identical period and epoch (within some tolerance) and perform logic to identify which is the real source (the parent) and which is a false positive due to contamination from the parent (a child).

[ascl:2101.007] Mask galaxy: Machine learning pipeline for morphological segmentation of galaxies

Mask galaxy is an automatic machine learning pipeline for detection, segmentation and morphological classification of galaxies. The model is based on the Mask R-CNN Deep Learning architecture. This model of instance segmentation also performs image segmentation at the pixel level, and has shown a Mean Average Precision (mAP) of 0.93 in morphological classification of spiral or elliptical galaxies.

[ascl:2101.006] ptemcee: A parallel-tempered version of emcee

ptemcee, pronounced "tem-cee", is fork of Daniel Foreman-Mackey's emcee (ascl:1303.002) to implement parallel tempering more robustly. As far as possible, it is designed as a drop-in replacement for emcee. It is helpful for characterizing awkward, multi-modal probability distributions.

[ascl:2101.005] Avocado: Photometric classification of astronomical transients and variables with biased spectroscopic samples

Avocado produces classifications of arbitrary astronomical transients and variable objects. It addresses the problem of biased spectroscopic samples by generating many lightcurves from each object in the original spectroscopic sample at a variety of redshifts and with many different observing conditions. The "augmented" samples of lightcurves that are generated are much more representative of the full datasets than the original spectroscopic samples.

[ascl:2101.004] radiowinds: Radio emission from stellar winds

radiowinds calculates the radio emission produced by the winds around stars. The code calculates thermal bremsstrahlung that is emitted from the wind, which depends directly on the density and temperature of the stellar wind plasma. The program takes input data in the form of an interpolated 3d grid of points (of the stellar wind) containing position, temperature and density data. From this it calculates the thermal free-free emission expected from the wind at a range of user-defined frequencies.

[ascl:2101.003] whereistheplanet: Predicting positions of directly imaged companions

whereistheplanet predicts the locations of directly imaged companions (mainly exoplanets and brown dwarfs) based on past orbital fits to the data. This tool helps coordinate follow-up observations to characterize their properties, as precise pointing of the instrument is often needed. It uses orbitize! (ascl:1910.009) as a backend. whereistheplanet is available as a Python API, a command line tool, and a web form at whereistheplanet.com.

[ascl:2101.002] BAYES-LOSVD: Bayesian framework for non-parametric extraction of the LOSVD

BAYES-LOSVD performs non-parametric extraction of the Line-Of-Sight Velocity Distributions in galaxies. Written in Python, it uses Stan (ascl:1801.003) to perform all the computations and provides reliable uncertainties for all the parameters of the model chosen for the fit. The code comes with a large number of features, including read-in routines for some of the most popular IFU spectrographs and surveys, such as ATLAS3D, CALIFA, MaNGA, MUSE-WFM, SAMI, and SAURON.

[ascl:2101.001] 3LPT-init: Initial conditions with third-order Lagrangian perturbation for cosmological N-body simulations

In cosmological N-body simulations, higher-order Lagrangian perturbation on the initial condition affects the formation of nonlinear structure. Using this code, the initial condition generated by Zel'dovich approximation (Lagrangian linear perturbation) for Gadget-2 code to initial condition with second- or third-order Lagrangian perturbation (2LPT, 3LPT).

[ascl:2012.026] EinsteinPy: General Relativity and gravitational physics problems solver

EinsteinPy performs General Relativity and gravitational physics tasks, including geodesics plotting for Schwarzschild, Kerr and Kerr Newman space-time models, calculation of Schwarzschild radius, and calculation of event horizon and ergosphere for Kerr space-time. It can perform symbolic manipulations of various tensors such as Metric, Riemann, Ricci and Christoffel symbols. EinsteinPy also features hypersurface embedding of Schwarzschild space-time, and includes other utilities and functions. It is a community-developed package and is written in Python.

[ascl:2012.025] Magritte: 3D radiative transfer library

Magritte performs 3D radiative transfer modeling; though focused on astrophysics and cosmology, the techniques can also be applied more generally. The code uses a deterministic ray-tracer with a formal solver that currently focuses on line radiative transfer. Magritte can either be used as a C++ library or as a Python package.

[ascl:2012.024] DRAGraces: Reduction pipeline for GRACES spectra

DRAGraces (Data Reduction and Analysis for GRACES) reduces GRACES spectra taken with the Gemini North high-resolution spectrograph. It finds GRACES frames in a given directory, determines the list of bias, flat, arc and science frames, and performs the reduction and extraction. Written in IDL, DRAGraces is straightforward and easy to use.

[ascl:2012.023] HCGrid: Mapping non-uniform radio astronomy data onto a uniformly distributed grid

HCGrid maps non-uniform radio astronomy data onto a uniformly distributed grid using a convolution-based algorithm on CPU-GPU heterogeneous platforms. The package has three modules; the initialization module initializes parameters needed for the calculation process, such as setting the size of the sampling space and output resolution. The gridding module uses a parallel ordering algorithm to pre-order the sampling points based on HEALPix on the CPU platform and uses an efficient two-level lookup table to speed up the acquisition of sampling points; it then accelerates convolution by using the high parallelism of GPU and through related performance optimization strategies based on CUDA architecture to further improve the gridding performance. The third module processes the results; it visualizes the gridding and exports the final products as FITS files.

[ascl:2012.022] SWIGLAL: Access LALSuite libraries with Python and Octave scripts

SWIGLAL, a wrapper for and component of the LALSuite (ascl:2012.021) gravitational wave detection and analysis libraries, which are primarily written in C, makes LALSuite routines directly accessible to Python and Octave scripts.

[ascl:2012.021] LALSuite: LIGO Scientific Collaboration Algorithm Library Suite

LALSuite contains numerous gravitational wave analysis libraries. Written primarily in C, the libraries include math and signal analysis packages such as for vector manipulation, FFT, statistics, time-domain filtering, and numerical and signal injection routines. The libraries also include date and time and datatype factory routines, in addition to general and support tools and a variety of Python packages. Also included are packages for gravitational waveform and noise generation, burst gravitational wave data analysis, inspiral and ringdown CBC gravitational wave data analysis, pulsar and continuous wave gravitational wave data analysis, and Bayesian inference data analysis. Various wrappers and other tools are also included.

[ascl:2012.020] BlackHawk: Black hole evaporation calculator

BlackHawk calculates the Hawking evaporation spectra of any black hole distribution. Written in C, the program enables users to compute the primary and secondary spectra of stable or long-lived particles generated by Hawking radiation of the distribution of black holes, and to study their evolution in time.

[ascl:2012.019] PyXel: Astronomical X-ray imaging data modeling

PyXel models astronomical X-ray imaging data; it provides a common set of image analysis tools for astronomers working with extended X-ray sources. PyXel can model surface brightness profiles from X-ray satellites using a variety of models and statistics. PyXel can, for example, fit a broken power-law model to a surface brightness profile, and fit a constant to the sky background level in the direction of the merging galaxy cluster.

[ascl:2012.018] SimCADO: Observations simulator for infrared telescopes and instruments

SimCADO simulates observations with any NIR/Vis imaging system. Though the package was originally designed to simulate images for the European Extremely Large Telescope (ELT) and MICADO, with the proper input, it is capable of simulating observations from many different telescope and instrument configurations.

[ascl:2012.017] SLIT: Sparse Lens Inversion Technique

SLIT (Sparse Lens Inversion Technique) provides a method for inversion of lensed images in the frame of strong gravitational lensing. The code requires the input image along with lens mass profile and a PSF. The user then has to chose a maximum number of iterations after which the algorithm will stop if not converged and a image size ratio to the input image to set the resolution of the reconstructed source. Results are displayed in pyplot windows.

[ascl:2012.016] Pomegranate: Probabilistic model builder

Pomegranate builds probabilistic models in Python that is implemented in Cython for speed. The code merges the easy-to-use API of scikit-learn with the modularity of probabilistic modeling, including general mixture and hidden Markov models and Bayesian networks, to allow users to specify complicated models without the need to be concerned about implementation details. The models are built from the ground up and natively support features such as multi-threaded parallelism and out-of-core processing.

[ascl:2012.015] seaborn: Statistical data visualization

Seaborn provides a high-level interface for drawing attractive statistical graphics. Written in Python, it builds on matplotlib and integrates closely with pandas data structures. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API allows the user to focus on what the different elements of the plots mean, rather than on the details of how to draw them.

[ascl:2012.014] dolphin: Automated pipeline for lens modeling

Dolphin uniformly models large lens samples. It is a wrapper for Lenstronomy (ascl:1804.012), and features semi-automated modeling of a large sample of quasar and galaxy-galaxy lenses. Dolphin, written in Python, provides easy portability between local and MPI environments.

[ascl:2012.013] sedop: Optimize discrete versions of common SEDs

sedop is a Monte-Carlo minimization code designed to optimally construct spectral energy distributions (SEDs) for sources of ultraviolet and X-ray radiation employed in numerical simulations of reionization and radiative feedback.

[ascl:2012.012] TRAN_K2: Planetary transit search

TRAN_K2 searches for periodic transits in the photometric time series of the Kepler K2 mission. The search is made by considering stellar variability and instrumental systematics. TRAN_K2 is written in Fortran 77 and has a single input parameter file that can be edited by the user depending on the type of run and parameter ranges to be used.

[ascl:2012.011] Skye: Excess clustering of transit times detection

Skye detects a statistically significant excess clustering of transit times, indicating that there are likely systematics at specific times that cause many false positive detections, for the Kepler DR25 planet candidate catalog. The technique could be used for any survey looking to statistically cull false alarms.

[ascl:2012.010] MADLens: Differentiable lensing simulator

MADLens produces non-Gaussian cosmic shear maps at arbitrary source redshifts. A MADLens simulation with only 256^3 particles produces convergence maps whose power agree with theoretical lensing power spectra up to scales of L=10000. The code is based on a highly parallelizable particle-mesh algorithm and employs a sub-evolution scheme in the lensing projection and a machine-learning inspired sharpening step to achieve these high accuracies.

[ascl:2012.009] HydroCode1D: 1D finite volume code

HydroCode1D is a 1D finite volume code that can run any problem with 1D or 2D/3D spherical symmetry including external gravity or self-gravity. The program provides, depending on the configuration, output files that contain the midpoint position, density, velocity and pressure for each cell in the grid (in SI units). The program will by default use all available threads (as given by the environment variable OMP_NUM_THREADS). This can be overwritten by giving the desired number of threads as a command line argument to the program.

[ascl:2012.008] LIFELINE: LIne proFiles in massivE coLliding wInd biNariEs

LIFELINE (LIne proFiles in massivE coLliding wInd biNariEs) simulates the X-ray lines profile in colliding wind binaries. The code is self-consistent and computes the distribution of the wind velocity, the characterization of the wind shock region, and the line profile. In addition to perform the overall computation, LIFELINE can use a pre-computed velocity distribution to compute the shock characteristics and the line profile, or use pre-computed shock characteristics and velocity distributions to compute only the line profile.

[ascl:2012.007] EOS: Equation of State for planetary impacts

EOS is an analytical equation of state which models high pressure theory and fits well to the experimental data of ∊-Fe, SiO2, Mg2SiO4, and the Earth. The cold part of the EOS is modeled after the Varpoly EOS. The thermal part is based on a new formalism of the Gruneisen parameter, which improves behavior from earlier models and bridges the gap between elasticity and thermoelasticity. The EOS includes an expanded state model, which allows for the accurate modeling of material vapor curves.

[ascl:2012.006] Robovetter: Automatic vetting of Threshold Crossing Events (TCEs)

The DR25 Kepler Robovetter is a robotic decision-making code that dispositions each Threshold Crossing Event (TCE) from the final processing (DR 25) of the Kepler data into Planet Candidates (PCs) and False Positives (FPs). The Robovetter provides four major flags to designate each FP TCE as Not Transit-Like (NTL), a Stellar Eclipse (SS), a Centroid Offset (CO), and/or an Ephemeris Match (EM). It produces a score ranging from 0.0 to 1.0 that indicates the Robovetter's disposition confidence, where 1.0 indicates strong confidence in PC, and 0.0 indicates strong confidence in FP. Finally, the Robovetter provides comments in a text string that indicate the specific tests each FP TCE fails and provides supplemental information on all TCEs as necessary.

[ascl:2012.005] MLC_ELGs: Machine Learning Classifiers for intermediate redshift Emission Line Galaxies

MLC_EPGs classifies intermediate redshift (z = 0.3–0.8) emission line galaxies as star-forming galaxies, composite galaxies, active galactic nuclei (AGN), or low-ionization nuclear emission regions (LINERs). It uses four supervised machine learning classification algorithms: k-nearest neighbors (KNN), support vector classifier (SVC), random forest (RF), and a multi-layer perceptron (MLP) neural network. For input features, it uses properties that can be measured from optical galaxy spectra out to z < 0.8—[O III]/Hβ, [O II]/Hβ, [O III] line width, and stellar velocity dispersion—and four colors (u−g, g−r, r−i, and i−z) corrected to z = 0.1.

[ascl:2012.004] BinaryStarSolver: Orbital elements of binary stars solver

Given a series of radial velocities as a function of time for a star in a binary system, BinaryStarSolver solves for various orbital parameters. Namely, it solves for eccentricity (e), argument of periastron (ω), velocity amplitude (K), long term average radial velocity (γ), and orbital period (P). If the orbital parameters of a primary star are already known, it can also find the orbital parameters of a companion star, with only a few radial velocity data points.

[ascl:2012.003] Sengi: Interactive viewer for spectral outputs from stellar population synthesis models

Sengi enables online viewing of the spectral outputs of stellar population synthesis (SPS) codes. Typical SPS codes require significant disk space or computing resources to produce spectra for simple stellar populations with arbitrary parameters, making it difficult to present their results in an interactive, web-friendly format. Sengi uses Non-negative Matrix Factorisation (NMF) and bilinear interpolation to estimate output spectra for arbitrary values of stellar age and metallicity; this reduces the disk requirements and computational expense, allowing Sengi to serve the results in a client-based Javascript application.

[ascl:2012.002] NSCG: NOIRLab Source Catalog Generator

The NOIRLab Source Catalog Generator generates the NOIRLab Source Catalog (NSC), a catalog of all publicly available imagining data in the NOIRLab Astro Data Archive. The second data release (DR2) of the archive contains over 3.9 billion unique objects, 68 billion individual source measurements, covers 35,000 square degrees of the sky, has depths of 23rd magnitude in most broadband filters with 1-2% photometric precision, and astrometric accuracy of 7 mas. NSCG is written in Python and IDL. Three main steps generate the NSC: (1) Source Extractor (ascl:1010.064) is used to detect and measure sources in individual images; (2) astrometrics are calibrated with Gaia DR2 and photometric calibration using large public photometric catalogs such as Pan-STARRS1 and ATLAS-Refcat2; and, (3) measurements are clustered into unique objects, averaging photometric and morphological properties, and calculating proper motions and photometric variability indices.

[ascl:2012.001] getsf: Multi-scale, multi-wavelength sources and filaments extraction

getsf extracts sources and filaments in astronomical images by separating their structural components, and is designed to handle multi-wavelength sets of images and very complex filamentary backgrounds. The method spatially decomposes the original images and separates the structural components of sources and filaments from each other and from their backgrounds, flattening their resulting images. It spatially decomposes the flattened components, combines them over wavelengths, and detects the positions of sources and skeletons of filaments. Finally, getsf measures the detected sources and filaments and creates the output catalogs and images. This universal and fully automated method has a single user-definable free parameter, which reduces to a minimum dependence of its results on the human factor.

[submitted] ExoPix: Exoplanet Imaging with JWST

ExoPix is a collection of tutorials aimed at illustrating the imaging of exoplanets with the James Webb Space Telescope (JWST). ExoPix tutorials are meant to demonstrate the application of the PSF-subtraction algorithm pyKLIP (ascl:1506.001) to simulated JWST NIRCAM data. We provide simple walkthroughs of pyKLIP’s ability to reveal exoplanets, compute contrast curves, and measure exoplanet astrometry and photometry in imaged extrasolar systems.

[ascl:2011.030] DDCalc: Dark matter direct detection phenomenology package

DDCalc performs various dark matter direct detection calculations, including signal rate predictions, constraints on light DM, and likelihoods for several experiments. It offers eighteen non-relativistic effective operators to describe velocity and momentum transfer, and elastic scattering of DM particles off nucleons, and has an extended detector interface.

[ascl:2011.029] DarkBit: Dark matter constraints calculator

DarkBit computes dark matter constraints on extensions to the Standard Model of particle physics. Written in the GAMBIT (ascl:1708.030) framework, it seamlessly integrates with other tools in the statistical fitting framework; it is also available as a standalone tool. It offers a signal yield calculator for gamma-ray observations, provides likelihoods for arbitrary combinations of spin-independent and spin-dependent scattering processes, and provides a general solution for studying complex particle physics models that predict dark matter annihilation to a multitude of final states.

[ascl:2011.028] CWITools: Tools for Cosmic Web Imager data

CWITools analyzes integral field spectroscopy data from the Palomar and Keck Cosmic Web Imagers, and can be adapted for any three-dimensional integral field spectroscopy data. The package is modular, allowing users to construct data analysis pipelines to suit their own scientific needs, and includes tools for reducing data cubes, extracting a target signal, making emission maps, spectra, and other products. It also fits emission line and radial profiles and obtains final scalar quantities such as size and luminosity, among other tasks. It also contains helper functions that can, for example, obtain the wavelength axis from a 3D header, and create an auto-populated list of nebular emission lines or sky lines.

[ascl:2011.027] kiauhoku: Stellar model grid interpolation

Kiauhoku interacts with, manipulates, and interpolates between stellar evolutionary tracks in a model grid. It was built for interacting with YREC models, but other stellar evolution model grids, including MIST, Dartmouth, and GARSTEC, are also available.

[ascl:2011.026] DeepShadows: Finding low-surface-brightness galaxies in survey images

DeepShadows uses a convolutional neural networks (CNNs) to separate low-surface-brightness galaxies (LSBGs) from artifacts (such as Galactic cirrus and star-forming regions) in survey images. The model is trained and tested on labeled LSBGs and artifacts from the Dark Energy Survey and demonstrates that CNNs offer a promising path in the quest to study the low-surface-brightness universe.

[ascl:2011.025] PNICER: Extinction estimator

PNICER estimates extinction for individual sources and creates extinction maps using unsupervised machine learning algorithms. Extinction towards single sources is determined by fitting Gaussian Mixture Models along the extinction vector to (extinction-free) control field observations. PNICER also offers access to the well-established NICER technique in a simple unified interface and is capable of building extinction maps including the NICEST correction for cloud substructure.

[ascl:2011.024] ACStools: Python tools for Hubble Space Telescope Advanced Camera for Surveys data

The ACStools package contains Python tools to work with data from the Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS). The package has several calibration utilities and a zeropoints calculator, can detect satellite trails, and offers destriping, polarization, and photometric tools.

[ascl:2011.023] reproject: Python-based astronomical image reprojection

reproject implements image reprojection (resampling) methods for astronomical images using various techniques via a uniform interface. Reprojection re-grids images from one world coordinate system to another (for example changing the pixel resolution, orientation, coordinate system). reproject works on celestial images by interpolation, as well as by finding the exact overlap between pixels on the celestial sphere. It can also reproject to/from HEALPIX projections by relying on the astropy-healpix package.

[ascl:2011.022] GPCAL: Instrumental polarization calibration in VLBI data

GPCAL performs instrumental polarization calibration in very long baseline interferometry (VLBI) data. It enhances the calibration accuracy by enabling users to fit the model to multiple calibrators data simultaneously and to take into account the calibrators linear polarization structures instead of using the conventional similarity assumption. GPCAL is based on AIPS (ascl:9911.003) and uses ParselTongue (ascl:1208.020) to run AIPS tasks.

[ascl:2011.021] HSTCosmicrays: Analyzing cosmic rays in HST calibration data

HSTCosmicrays finds and characterizes cosmic rays found in dark frames (exposures taken with the shutter closed) taken with instruments on the Hubble Space Telescope (HST). Dark exposures are obtained routinely by all the Hubble Space Telescope instruments for calibration. The main processing pipeline runs locally or in the cloud on AWS utilizing the HST Public Dataset.

[ascl:2011.020] REBOUNDx: Adding effects in REBOUND N-body integrations

REBOUNDx incorporates additional physics into REBOUND (ascl:1110.016) simulations. Users can add effects from a list of pre-implemented astrophysical forces or contribute new ones. The main code is written in C, and a Python wrapper is provided for interfacing with other libraries. The REBOUNDx source code is machine independent and a binary format to save REBOUNDx configurations interfaces with the SimulationArchive class in REBOUND, making it possible to share and reproduce results bit by bit.

[ascl:2011.019] Scintools: Pulsar scintillation data tools

SCINTOOLS (SCINtillation TOOLS) simulates and analyzes pulsar scintillation data. The code can be used for processing observed dynamic spectra, computing secondary spectra and ACFs, measuring scintillation arcs, simulating dynamic spectra, and modeling pulsar transverse velocities through scintillation arcs or diffractive timescales.

[ascl:2011.018] Clustering: Code for clustering single pulse events

Clustering is a modified version of the single-pulse sifting algorithm RRATrap (ascl:2011.017) combined with DBSCAN codes to cluster single pulse events.

[ascl:2011.017] RRATtrap: Rotating Radio Transient identifier

RRATtrap is a single-pulse sifting algorithm to identify Rotating Radio Transients (RRATs) and transients using output from the PRESTO (ascl:1107.017) routine single_pulse_search.py. It can be integrated into pulsar survey data analysis pipelines and, in addition to finding RRATs, it can also identify Fast Radio Bursts.

[ascl:2011.016] GoFish: Molecular line detections in protoplanetary disks

GoFish exploits the known rotation of a protoplanetary disk to shift all emission to a common line center in order to stack them, increasing the signal-to-noise of the spectrum, detecting weaker lines, or super-sampling the spectrum to better resolve the line profile.

[ascl:2011.015] EvapMass: Minimum mass of planets predictor

EvapMass predicts the minimum masses of planets in multi-planet systems using the photoevaporation-driven evolution model. The planetary system requires both a planet above and below the radius gap to be useful for this test. EvapMass includes an example Jupyter notebook for the Kepler-36 system. EvalMass can be used to identify TESS systems that warrant radial-velocity follow-up to further test the photoevaporation model.

[ascl:2011.014] SEDkit: Spectral energy distribution construction and analysis tools

SEDkit constructs and analyzes simple spectral energy distributions (SED). This collection of pure Python modules creates individual SEDs or SED catalogs from spectra and/or photometry and calculates fundamental parameters (fbol, Mbol, Lbol, Teff, mass, log(g)).

[ascl:2011.013] TLC: Tidally Locked Coordinates

Tidally Locked Coordinates converts global climate model (GCM) output from standard/Earth-like coordinates into a tidally locked coordinate system. The transformations in Tidally Locked Coordinates are useful for plotting and analyzing GCM simulations of slowly rotating tidally locked planets such as Earth-like planets inside the habitable zone of small stars. They can be used to leverage the fact that a slowly rotating planet's climate will start to look approximately symmetric about the axis of insolation.

[ascl:2011.012] wobble: Time-series spectra analyzer

wobble analyzes time-series spectra. It was designed with stabilized extreme precision radial velocity (EPRV) spectrographs in mind, but is highly flexible and extensible to a variety of applications. It takes a data-driven approach to deriving radial velocities and requires no a priori knowledge of the stellar spectrum or telluric features.

[ascl:2011.011] frbcat: Fast Radio Burst CATalog querying package

frbcat queries and downloads Fast Radio Burst (FRB) data from the FRBCAT Catalogue web page, the CHIME-REPEATERS web page and the Transient Name Server (TNS). It is written in Python and can be installed using pip.

[ascl:2011.010] ARES: Accelerated Reionization Era Simulations

The Accelerated Reionization Era Simulations (ARES) code rapidly generates models for the global 21-cm signal. It can also be used as a 1-D radiative transfer code, stand-alone non-equilibrium chemistry solver, or global radiation background calculator.

[ascl:2011.009] HaloGen: Modular halo model code

HaloGen computes all auto and cross spectra and halo model trispectrum in simple configurations. This modular halo model code computes 3d power spectra, and the corresponding projected 2d power spectra in the Limber and flat sky approximations. The observables include matter density, galaxy lensing, CMB lensing, thermal Sunyaev-Zel'dovich, cosmic infrared background, tracers with any dn/dz, b(z) and HOD.

[ascl:2011.008] GOTHIC: Double nuclei galaxy detector

GOTHIC (Graph-bOosTed iterated HIll Climbing) detects whether a given image of a galaxy has characteristic features of a double nuclei galaxy (DNG). Galaxy interactions and mergers play a crucial role in the hierarchical growth of structure in the universe; galaxy mergers can lead to the formation of elliptical galaxies and larger disk galaxies, as well as drive galaxy evolution through star formation and nuclear activity. During mergers, the nuclei of the individual galaxies come closer and finally form a double nuclei galaxy. Although mergers are common, the detection of double-nuclei galaxies (DNGs) is rare and fairly serendipitous. Their properties can help us understand the formation of supermassive black hole (SMBH) binaries, dual active galactic nuclei (DAGN) and the associated feedback effects. GOTHIC provides an automatic and systematic way to survey data for the discovery of double nuclei galaxies.

[ascl:2011.007] DYNAMITE: DYnamics, Age and Metallicity Indicators Tracing Evolution

DYNAMITE (DYnamics, Age and Metallicity Indicators Tracing Evolution) is a triaxial dynamical modeling code for stellar systems and is based on existing codes for Schwarzschild modeling in triaxial systems. DYNAMITE provides an easy-to-use object oriented Python wrapper that extends the scope of pre-existing triaxial Schwarzschild codes with a number of new features, including discrete kinematics, more flexible descriptions of line-of-sight velocity distributions, and modeling of stellar population information. It also offers more efficient steps through parameter space, and can use GPU acceleration.

[ascl:2011.006] tlpipe: Data processing pipeline for the Tianlai experiment

tlpipe processes the drift scan survey data from the Tianlai experiment; the Tainlai project is a 21cm intensity mapping experiment aimed at detecting dark energy by measuring the baryon acoustic oscillation (BAO) features in the large scale structure power spectrum. tlpipe performs offline data processing tasks such as radio frequency interference (RFI) flagging, array calibration, binning, and map-making, in addition to other tasks. It includes utility functions needed for the data analysis, such as data selection, transformation, visualization and others. tlpipe implements a number of new algorithms are implemented, including the eigenvector decomposition method for array calibration and the Tikhnov regularization for m-mode analysis.

[ascl:2011.005] DarkCapPy: Dark Matter Capture and Annihilation

DarkCapPy calculates rates associated with dark matter capture in the Earth, annihilation into light mediators, and observable decay of the light mediators near the surface of the Earth. This Python/Jupyter package can calculate the Sommerfeld enhancement at the center of the Earth and the timescale for capture-annihilation equilibrium, and can be modified for other compact astronomical objects and mediator spins.

[ascl:2011.004] MCMCDiagnostics: Markov Chain Monte Carlo convergence diagnostics

MCMCDiagnostics contains two diagnostics, written in Julia, for Markov Chain Monte Carlo. The first is potential_scale_reduction(chains...), which estimates the potential scale reduction factor, also known as Rhat, for multiple scalar chains
. The second, effective_sample_size(chain), calculates the effective sample size for scalar chains. These diagnostics are intended as building blocks for use by other libraries.

[ascl:2011.003] Kalkayotl: Inferring distances to stellar clusters from Gaia parallaxes

Kalkayotl obtains samples of the joint posterior distribution of cluster parameters and distances to the cluster stars from Gaia parallaxes using Bayesian inference. The code is designed to deal with the parallax spatial correlations of Gaia data, and can accommodate different values of parallax zero point and spatial correlation functions.

[ascl:2011.002] CAPTURE: Interferometric pipeline for image creation from GMRT data

CAPTURE (CAsa Pipeline-cum-Toolkit for Upgraded Giant Metrewave Radio Telescope data REduction) produces continuum images from radio interferometric data. Written in Python, it uses CASA (ascl:1107.013) tasks to analyze data obtained by the GMRT. It can produce self-calibrated images in a fully automatic mode or can run in steps to allow the data to be inspected throughout processing.

[ascl:2011.001] AdaMet: Adaptive Metropolis for Bayesian analysis

AdaMet (Adaptive Metropolis) performs efficient Bayesian analysis. The user-friendly Python package is an implementation of the Adaptive Metropolis algorithm. In many real-world applications, it is more efficient and robust than emcee (ascl:1303.002), which warm-up phase scales linearly with the number of walkers. For this reason, and because of its didactic value, the AdaMet code is provided as an alternative.

[ascl:2010.015] relxill: Reflection models of black hole accretion disks

relxill self-consistently connects an angle-dependent reflection model constructed with XILLVER (http://www.srl.caltech.edu/personnel/javier/xillver/index.html) with the relativistic blurring code RELLINE (ascl:1505.021). It calculates the proper emission angle of the radiation at each point on the accretion disk and then takes the corresponding reflection spectrum into account.

[ascl:2010.014] Pix2Prof: Deep learning for textraction of useful sequential information from galaxy imagery

Pix2Prof produces a surface brightness profile from an unprocessed galaxy image from the SDSS in either the g, r, or i bands. It is fast, and given suitable training data, Pix2Prof can be retrained to produce any galaxy profile from any galaxy image.

[ascl:2010.013] Legolas: Large Eigensystem Generator for One-dimensional pLASmas

Legolas (Large Eigensystem Generator for One-dimensional pLASmas) is a finite element code for MHD spectroscopy of 1D Cartesian/cylindrical equilibria with flow that balance pressure gradients, enriched with various non-adiabatic effects. The code's capabilities range from full spectrum calculations to eigenfunctions of specific modes to full-on parametric studies of various equilibrium configurations in different geometries.

[ascl:2010.012] Astronomaly: Flexible framework for anomaly detection in astronomy

Astronomaly actively detects anomalies in astronomical data. A python back-end runs anomaly detection based on machine learning; a JavaScript front-end provides data viewing and labeling. The package works on many common astronomy data types, including one-dimensional data and images, and offering extendable techniques for preprocessing, feature extraction, and machine learning.

[ascl:2010.011] ROGER: Automatic classification of galaxies using phase-space information

ROGER (Reconstructing Orbits of Galaxies in Extreme Regions) predicts the dynamical properties of galaxies using the projected phase-space information. Written in R, it offers a choice of machine learning methods to classify the dynamical properties of galaxies. An interface for online use of the software is available at https://mdelosrios.shinyapps.io/roger_shiny/.

[ascl:2010.010] lenspyx: Curved-sky python lensed CMB maps simulation package

lenspyx creates curved-sky python lensed CMB maps simulations; the software allows those familiar with healpy (ascl:2008.022) to build very easily lensed CMB simulations. Parallelization is done with openmp. The numerical cost is approximately that of an high-res harmonic transform. lenspyx provides two methods to build a simulation; one method computes a deflected spin-0 healpix map from its alm and deflection field alm, and the other computes a deflected spin-weight Healpix map from its gradient and curl modes and deflection field alm. lenspyx can be used in conjunction with the Planck 2018 CMB lensing pipeline plancklens (ascl:2010.009) to reproduce the published map and band-powers.

[ascl:2010.009] plancklens: Planck 2018 lensing pipeline

plancklens contains most of Planck 2018 CMB lensing pipeline and makes it possible to reproduce the published map and band-powers. Some numerical parts are written in Fortran, and portions of it (structure and code) have been directly adapted from pre-existing work by Duncan Hanson. The lensed CMB skies is produced by the stand-alone package lenspyx (ascl:2010.010).

[ascl:2010.008] Exo-DMC: Exoplanet Detection Map Calculator

The Exoplanet Detection Map Calculator (Exo-DMC) performs statistical analysis of exoplanet surveys results using Monte Carlo methods. Written in Python, it is the latest rendition of the MESS (Multi-purpose Exoplanet Simulation System, ascl:1111.009). Exo-DMC combines the information on the target stars with instrument detection limits to estimate the probability of detection of companions within a user defined range of masses and physical separations, ultimately generating detection probability maps. The software allows for a high level of flexibility in terms of possible assumptions on the synthetic planet population to be used for the determination of the detection probability.

[ascl:2010.007] stella: Stellar flares identifier

stella creates and trains a neural network to identify stellar flares. Within stella, users can simulate flares as a training set, run a neural network, and feed in their own data to the neural network model. The software returns a probability at each data point as to whether that data point is part of a flare; the code can also characterize the flares identified.

[ascl:2010.006] LaSSI: Large-Scale Structure Information

LaSSI produces forecasts for the LSST 3x2 point functions analysis, or the LSSTxCMB S4 and LSSTxSO 6x2 point functions analyses using a Fisher matrix. It computes the auto and cross correlations of galaxy number density, galaxy shear and CMB lensing convergence. The software includes the effect of Gaussian and outlier photo-z errors, shear multiplicative bias, linear galaxy bias, and extensions to ΛCDM.

[ascl:2010.005] GRAPUS: GRAvitational instability PopUlation Synthesis

GRAPUS (GRAvitational instability PopUlation Synthesis) executes population synthesis modeling of self-gravitating disc fragmentation and tidal downsizing in protostellar discs. It reads in pre-run 1D viscous disc models of self-gravitating discs and computes where fragmentation will occur and the initial fragment mass. GRAPUS then allows these fragment embryos to evolve under various forces, including quasistatic collapse of the embryo, growth and sedimentation of the dust inside the embryo, and the formation of solid cores. The software also evolves migration due to embryo-disc interactions and tidal disruption of the embryo, and can optionally determine gravitational interactions with neighboring embryos.

[ascl:2010.004] TACHE: TensoriAl Classification of Hydrodynamic Elements

TACHE (TensoriAl Classification of Hydrodynamic Elements) performs classification of the eigenvalues of either the tidal tensor or the velocity shear tensor at the point of a smoothed particle. This provides local information as to how matter is collapsing or flowing, respectively, in particular what stable manifold is being produced. The code reads in smoothed particle hydrodynamics (SPH) snapshot files in sphNG format and computes neighbor lists for SPH data and either the (symmetric) velocity shear tensor or tidal tensor and their eigenvalues/eigenvectors. It classifies fluid elements by number of "positive" eigenvalues and permits decomposition of snapshots into classified components; it also includes several Python plotting scripts.

[ascl:2010.003] stsynphot: synphot for HST and JWST

An extension to synphot (ascl:1811.001), stsynphot implements synthetic photometry package for HST and JWST support. The software constructs spectra from various grids of model atmosphere spectra, parameterized spectrum models, and atlases of stellar spectrophotometry. It also simulates observations specific to HST and JWST, computes photometric calibration parameters for any supported instrument mode, and plots instrument-specific sensitivity curves and calibration target spectra.

[ascl:2010.002] GSpec: Gamma-ray Burst Monitor analyzer

GSpec analyzes the Fermi mission's Gamma-ray Burst Monitor (GBM) data via a user-interactive GUI. The software provides a seamless interface to XSPEC (ascl:9910.005). It allows users to create their own Python scripts using the included libraries, and to define additional data reduction techniques, such as background fitting/estimation and data binning, as Python-based plugins. It is part of a larger effort to produce a set of GBM data tools to allow the broader community to analyze all aspects of GBM data, including the continuous data that GBM produces. GSpec is similar to RMfit (ascl:1409.011), a GUI-based spectral analysis code that specializes in the analysis of GBM trigger data, and is intended to eventually replace that IDL package.

[ascl:2010.001] MBF: MOLSCAT 2020, BOUND, and FIELD for atomic and molecular collisions

MOLSCAT, which supercedes MOLSCAT version 14 (ascl:1206.004), performs non-reactive quantum scattering calculations for atomic and molecular collisions using coupled-channel methods. Simple atom-molecule and molecule-molecule collision types are coded internally and additional ones may be handled with plug-in routines. Plug-in routines may include external magnetic, electric or photon fields (and combinations of them).

The package also includes BOUND, which performs calculations of bound-state energies in weakly bound atomic and molecular systems using coupled-channel methods, and FIELD, a development of BOUND that locates values of external fields at which a bound state exists with a specified energy. Though the three programs have different applications, they use closely related methods, share many subroutines, and are released with a single code base.

[ascl:2009.025] Binary-Speckle: Binary or triple star parameters

Binary-Speckle reduces Speckle or AO data from the raw data to deconvolved images (in Fourier space), to determine the parameters of a binary or triple, and to find limits for undetected companion stars.

[ascl:2009.024] MSL: Mining for Substructure Lenses

MSL applies simulation-based inference techniques to the problem of substructure inference in galaxy-galaxy strong lenses. It leverages additional information extracted from the simulator, then trains neural networks to estimate likelihood ratios associated with population-level parameters characterizing dark matter substructure. The package including five high-level scripts which run the simulation and create samples, combing multiple simulation runs into a single file to use for training, then train the neural networks. After training, the estimated likelihood ratio is tested, and calibrated network predictions are made based on histograms of the network output.

[ascl:2009.023] DASTCOM5: JPL small-body data browser

DASTCOM5 is a portable direct-access database containing all NASA/JPL asteroid and comet orbit solutions, and the software to access it. Available data include orbital elements, orbit diagrams, physical parameters, and discovery circumstances. A JPL implementation of the software is available at http://ssd.jpl.nasa.gov/sbdb.cgi.

[ascl:2009.022] Harmonia: Hybrid-basis inference for large-scale galaxy clustering

Harmonia combines clustering statistics decomposed in spherical and Cartesian Fourier bases for large-scale galaxy clustering likelihood analysis. Optimal weighting schemes for spherical Fourier analysis can also be readily implemented using the code.

[ascl:2009.021] Chrono: Multi-physics simulation engine

Chrono is a physics-based modelling and simulation infrastructure implemented in C++. It can handle multibody dynamics, collision detection, and granular flows, among many other physical processes. Though the applications for which Chrono has been used most often are vehicle dynamics, robotics, and machine design, it has been used to simulate asteroid aggregation and granular systems for astrophysics research. Chrono is written in C++; a Python version, PyChrono, is also available.

[ascl:2009.020] cosmoFns: Functions for observational cosmology

cosmoFns computes distances, times, luminosities, and other quantities useful in observational cosmology, including molecular line observations. Written in R and coded for a flat universe, it contains functions for rest-frame line and luminosities, cosmic lookback time given z and cosmological parameters, and differential comoving volume. cosmoFns also computes comoving, luminosity, and angular diameter distances and molecular mass, among other quantities.

[ascl:2009.019] FLEET: Finding Luminous and Exotic Extragalactic Transients

FLEET (Finding Luminous and Exotic Extragalactic Transients) is a machine-learning pipeline that predicts the probability of a transient to be a superluminous supernova. With light curve and contextual host galaxy information, it uses a random forest algorithm to rapidly identify SLSN-I without the need for redshift information.

[ascl:2009.018] CRAC: Cosmology R Analysis Code

CRAC (Cosmology R Analysis Code) provides R functions for cosmology. Its main functions are similar to the Python library CosmoloPy (ascl:2009.017); for example, it implements functions to compute spherical geometric quantities for cosmological research.

[ascl:2009.017] CosmoloPy: Cosmology package for Python

CosmoloPy is a suite of cosmology routines built on NumPy/SciPy. Its capabilities include various cosmological densities, distance measures, and galaxy luminosity functions (Schecter functions). It also offers pre-defined sets of cosmological parameters (e.g., from WMAP), conversion in and out of the AB magnitude system, and the reionization of the IGM. Functions take cosmological parameters (which can be numpy arrays) as keywords and ignore any extra keywords, making it possible to build a dictionary of cosmological parameters and pass it to any function.

[ascl:2009.016] halomod: Flexible interface for the halo model of dark matter halos

halomod calculates cosmological halo model and HOD quantities. It is built on HMF (ascl:1412.006); it retains that code's features and provides extended components for the halo model, including numerous halo bias models, including scale-dependent bias, basic concentration-mass-redshift relations, and several plug-and-play halo-exclusion models. halomod includes built-in HOD parameterizations and halo profiles, support for WDM models, and all basic quantities such as 3D correlations and power spectra, and also several derived quantities such as effective bias and satellite fraction. In addition, it offers a simple routine for populating a halo catalog with galaxies via a HOD. halomod is flexible and modular, making it easily extendable.

[ascl:2009.015] rcosmo: Cosmic Microwave Background data analysis

rcosmo provides information processing, visualization, manipulation and spatial statistical analysis of Cosmic Microwave Background (CMB) radiation and other spherical data stored in or converted to HEALPix coordinates. The package has more than 100 different functions, and can perform spherical geometry, manipulate CMB and other spherical data, and visualize HEALPix data. rcosmo can also perform statistical analysis of CMB and spherical data, and transforme spherical data in cartesian and geographic coordinates into HEALPix format.

[ascl:2009.014] pySpectrum: Power spectrum and bispectrum calculator

pySpectrum calculates the power spectrum and bispectrum for galaxies, halos, and dark matter.

[ascl:2009.013] AstroVaDEr: Unsupervised clustering and synthetic image generation

AstroVaDEr (Astronomical Variational Deep Embedder) performs unsupervised clustering and synthetic image generation using astronomical imaging catalogs to classify their morphologies. This variational autoencoder leverages improvements to the variational deep clustering (VDC) paradigm; its variational inference properties allow the network to be employed as a generative network. AstroVaDEr can be adapted to various surveys and image classification problems.

[ascl:2009.012] minot: Modeling framework for diffuse components in galaxy clusters

minot (Modeling of the ICM (Non-)thermal content and Observables prediction Tools) provides a self-consistent modeling framework for the thermal and non-thermal diffuse components in galaxy clusters and predictions multi-wavelength observables. The framework sets or modifies the cluster object according to set parameters and defines the physical and observational properties, which can include thermal gas and CR physics, tSZ, inverse Compton, and radio synchotron. minot then generates outputs, including model parameters, plots, and relationships between models.

[ascl:2009.011] PyWST: WST and RWST for astrophysics

PyWST performs statistical analyses of two-dimensional data with the Wavelet Scattering Transform (WST) and the Reduced Wavelet Scattering Transform (RWST). The WST/RWST provides convenient sets of coefficients for describing non-Gaussian data in a comprehensive way.

[ascl:2009.010] MLG: Microlensing with Gaia

MLG simulates Gaia measurements for predicted astrometric microlensing events. It fits the motion of the lens and source simultaneously and reconstructs the 11 parameters of the lensing event. For lenses passing by multiple background sources, it also fits the motion of all background sources and the lens simultaneously. A Monte-Carlo simulation is used to determine the achievable precision of the mass determination.

[ascl:2009.009] MADHAT: Gamma-ray emission analyzer

MADHAT (Model-Agnostic Dark Halo Analysis Tool) analyzes gamma-ray emission from dwarf satellite galaxies and dwarf galaxy candidates due to dark matter annihilation, dark matter decay, or other nonstandard or unknown astrophysics. The tool is data-driven and model-independent, and provides statistical upper bounds on the number of observed photons in excess of the number expected using a stacked analysis of any selected set of dwarf targets. MADHAT also calculates the resulting bounds on the properties of dark matter under any assumptions the user makes regarding dark sector particle physics or astrophysics.

[ascl:2009.008] Paramo: PArticle and RAdiation MOnitor

Paramo (PArticle and RAdiation MOnitor) numerically solves the Fokker-Planck kinetic equation, which is used to model the dynamics of a particle distribution function, using a robust implicit method, for the proper modeling of the acceleration processes, and accounts for accurate cooling coefficient (e.g., radiative cooling with Klein-Nishina corrections). The numerical solution at every time step is used to calculate radiations processes, namely synchrotron and IC, with sophisticated numerical techniques, obtaining the multi-wavelength spectral evolution of the system.

[ascl:2009.007] J plots: Tool for characterizing 2D and 3D structures in the interstellar medium

J plots classifies and quantifies a pixelated structure, based on its principal moments of inertia, thus enabling automatic detection and objective comparisons of centrally concentrated structures (cores), elongated structures (filaments) and hollow circular structures (bubbles) from the main population of slightly irregular blobs that make up most astronomical images. Examples of how to analyze 2D or 3D datasets, enabling an unbiased analysis and comparison of simulated and observed structures are provided along with the Python code.

[ascl:2009.006] SPInS: Stellar Parameters INferred Systematically

SPInS (Stellar Parameters INferred Systematically) provides the age, mass, and radius of a star, among other parameters, from a set of photometric, spectroscopic, interferometric, and/or asteroseismic observational constraints; it also generates error bars and correlations. Derived from AIMS (ascl:1611.014), it relies on a stellar model grid and uses a Bayesian approach to find the PDF of stellar parameters from a set of classical constraints. The heart of SPInS is a MCMC solver coupled with interpolation within a pre-computed stellar model grid. The code can consider priors such as the IMF or SFR and can characterize single stars or coeval stars, such as members of binary systems or of stellar clusters.

[ascl:2009.005] CASI-3D: Convolutional Approach to Structure Identification-3D

CASI-3D identifies signatures of stellar feedback in molecular line spectra, such as 12CO and 13CO, using deep learning. The code is developed from CASI-2D (ascl:1905.023) and exploits the full 3D spectral information.

[ascl:2009.004] ISPy3: Integrated-light Spectroscopy for Python3

The ISPy3 suite of Python routines models and analyzes integrated-light spectra of stars and stellar populations. The actual spectral modeling and related tasks such as setting up model atmospheres is done via external codes. Currently, the Kurucz codes (ATLAS/SYNTHE) and MARCS/TurboSpectrum are supported, though implementing other similar codes should be relatively straight forward.

[ascl:2009.003] oxkat: Semi-automated imaging of MeerKAT observations

oxkat semi-automatically performs calibration and imaging of data from the MeerKAT radio telescope. Taking as input raw visibilities in Measurement Set format, the entire processing workflow is covered, from flagging and reference calibration, to imaging and self-calibration, and (optionally) direction-dependent calibration. The oxkat scripts use Python, and draw on numerous existing radio astronomy packages, including CASA (ascl:1107.013), WSClean (ascl:1408.023), and CubiCal (ascl:1805.031), among others, that are containerized using Singularity. Submission scripts for slurm and PBS job schedulers are automatically generated where necessary, catering for HPC facilities that are commonly used for processing MeerKAT data.

[ascl:2009.002] vlt-sphere: Automatic VLT/SPHERE data reduction and analysis

The high-contrast imager SPHERE at the Very Large Telescope combines extreme adaptive optics and coronagraphy to directly image exoplanets in the near-infrared. The vlt-sphere package enables easy reduction of the data coming from IRDIS and IFS, the two near-infrared subsystems of SPHERE. The package relies on the official ESO pipeline (ascl:1402.010), which must be installed separately.

[ascl:2009.001] JetSeT: Numerical modeling and SED fitting tool for relativistic jets

JetSeT reproduces radiative and accelerative processes acting in relativistic jets and fits the numerical models to observed data. This C/Python framework re-bins observed data, can define data sets, and binds to astropy tables and quantities. It can use Synchrotron Self-Compton (SSC), external Compton (EC) and EC against the CMB when defining complex numerical radiative scenarios. JetSeT can constrain the model in the pre-fitting stage based on accurate and already published phenomenological trends starting from parameters such as spectral indices, peak fluxes and frequencies, and spectral curvatures. The package fits multiwavelength SEDs using both frequentist approach and Bayesian MCMC sampling, and also provides self-consistent temporal evolution of the plasma under the effect of radiative and accelerative processes for both first order and second order (stochastic acceleration) processes.

[ascl:2008.027] HorizonGRound: Relativistic effects in ultra-large-scale clustering

HorizonGRound forward models general relativistic effects from the tracer luminosity function. It also compares relativistic corrections with the local primordial non-Gaussianity signature in ultra-large-scale clustering statistics. The package includes several recipes along with the data required to run them.

[ascl:2008.026] TDEmass: Tidal Disruption Event interpretor

TDEmass interprets Tidal Disruption Event (TDE) observations. In TDEs, a supermassive black hole at the center of a galaxy tears apart an ordinary star; the debris is placed on highly eccentric orbits and ultimately produces a very bright flare. Using this TDEmass, one can infer the mass of the black hole (mbh) and the mass of the star (mstar) involved in a TDE.

[ascl:2008.025] TRISTAN: TRIdimensional STANford code

TRISTAN (TRIdimensional STANford) is a fully electromagnetic code with full relativistic particle dynamics. The code simulates large-scale space plasma phenomena such as the formation of systems of galaxies. TRISTAN particles which hit the boundaries are arrested there and redistributed more uniformly by having the boundaries slightly conducting, thus allowing electrons to recombine with ions and provides a realistic way of eliminating escaping particles from the code. Fresh particle fluxes can then be introduced independently across the boundaries. Written in 1993, this code has largely been superceded by TRISTAN-MP (ascl:1908.008).

[ascl:2008.024] MUSIC2-monofonIC: 3LPT initial condition generator

The original MUSIC code (ascl:1311.011) was designed to provide initial conditions for zoom initial conditions and is limited for applications to large-scale cosmological simulations. MUSIC2-monofonIC generates high order LPT/PPT cosmological initial conditions for single resolution cosmological simulations, and can be used for rapid predictions of large-scale structure. MUSIC2-monofonIC offers support for up to 3rd order Lagrangian perturbation theory, PPT (Semiclassical PT for Eulerian grids) up to 2nd order, and for mixed CDM+baryon sims. It direct interfaces with CLASS and can use file input from CAMB; it offers multiple output modules for RAMSES (ascl:1011.007), Arepo (ascl:1909.010), Gadget-2/3 (ascl:0003.001), and HACC via plugins, and new modules/plugins can be easily added.

[ascl:2008.023] DUCC: Distinctly Useful Code Collection

DUCC (Distinctly Useful Code Collection) provides basic programming tools for numerical computation, including Fast Fourier Transforms, Spherical Harmonic Transforms, non-equispaced Fourier transforms, as well as some concrete applications like 4pi convolution on the sphere and gridding/degridding of radio interferometry data. The code is written in C++17 and provides a simple and comprehensive Python
interface.

[ascl:2008.022] healpy: Python wrapper for HEALPix

healpy handles pixelated data on the sphere. It is based on the Hierarchical Equal Area isoLatitude Pixelization (HEALPix) scheme and bundles the HEALPix (ascl:1107.018) C++ library. healpy provides utilities to convert between sky coordinates and pixel indices in HEALPix nested and ring schemes and find pixels within a disk, a polygon or a strip in the sky. It can apply coordinate transformations between Galactic, Ecliptic and Equatorial reference frames, apply custom rotations either to vectors or full maps, and read and write HEALPix maps to disk in FITS format. healpy also includes utilities to upgrade and downgrade the resolution of existing HEALPix maps and transform maps to Spherical Harmonics space and back using multi-threaded C++ routines, among other utilities.

[ascl:2008.021] ramses2hsim: RAMSES output to 3D data cube for HSIM

The ramses2hsim pipeline converts a simulated galaxy in a RAMSES (ascl:1011.007) output into an 3D input data cube for HSIM (ascl:1912.006). The code incorporates gas kinematics (both bulk and turbulence), line emission and line width for Hα, and accounts for dust extinction.

[ascl:2008.020] Eclaire: CUDA-based Library for Astronomical Image REduction

Eclaire is a GPU-accelerated image-reduction pipeline; it uses CuPy, a Python package for general-purpose computing on graphics processing units (GPGPU), to perform image processing, including bias subtraction, dark subtraction, flat fielding, bad pixel masking, alignment, and co-adding. It has been used for real-time image reduction of MITSuME observational data, and can be used with data from other observatories.

[ascl:2008.019] iFIT: 1D surface photometry code

iFIT determines the Sérsic law model for galaxies with imperfect Sérsic law profiles by searching for the best match between the observationally determined and theoretically expected radial variation of the mean surface brightness and light growth curve. The technique ensures quick convergence to a unique solution for both perfect and imperfect Sérsic profiles, even shallow and resolution-degraded SBPs. iFIT allows for correction of PSF convolution effects, offering the user the option of choosing between a Moffat, Gaussian, or user-supplied PSF, and is an efficient tool for the non-supervised structural characterization of large galaxy samples, such as those expected to become available with Euclid and LSST.

[ascl:2008.018] maxsmooth: Derivative constrained function fitting

maxsmooth fits derivative constrained functions (DCF) such as Maximally Smooth Functions (MSFs) to data sets. MSFs are functions for which there are no zero crossings in derivatives of order m >= 2 within the domain of interest. They are designed to prevent the loss of signals when fitting out dominant smooth foregrounds or large magnitude signals that mask signals of interest. Here "smooth" means that the foregrounds follow power law structures and do not feature turning points in the band of interest. maxsmooth uses quadratic programming implemented with CVXOPT (ascl:2008.017) to fit data subject to a fixed linear constraint, Ga <= 0, where the product Ga is a matrix of derivatives. The code tests the <= 0 constraint multiplied by a positive or negative sign and can test every available sign combination but by default, it implements a sign navigating algorithm.

[ascl:2008.017] CVXOPT: Convex Optimization

CVXOPT makes the development of software for convex optimization applications straightforward by building on Python’s extensive standard library and on the strengths of Python as a high-level programming language. It offers efficient Python classes for dense and sparse matrices (real and complex) with Python indexing and slicing and overloaded operations for matrix arithmetic, an interface to the fast Fourier transform routines from FFTW, and an interface to most of the double-precision real and complex BLAS. It contains routines for linear, second-order cone, and semidefinite programming problems, and for nonlinear convex optimization. CVXOPT also provides an interface to LAPACK routines for solving linear equations and least-squares problems, matrix factorizations (LU, Cholesky, LDLT and QR), symmetric eigenvalue and singular value decomposition, and Schur factorization, and a modeling tool for specifying convex piecewise-linear optimization problems.

[ascl:2008.016] ParaMonte: Parallel Monte Carlo library

ParaMonte contains serial and parallel Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions. It is used for posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference and unifies the automation of Monte Carlo simulations. ParaMonte is user friendly and accessible from multiple programming environments, including C, C++, Fortran, MATLAB, and Python, and offers high performance at runtime and scalability across many parallel processors.

[ascl:2008.015] CMEchaser: Coronal Mass Ejection line-of-sight occultation detector

CMEchaser looks for the occultation of background astronomical sources by CMEs to enable measurement of effects such as variations in the ionized content and the associated Faraday rotation of polarized signals along the line of sight to the background source. The code transforms a given Galactic coordinate to its concordant point in the Helioprojective, Sun-centered plane and estimates the point at which the line of sight from the source to the Earth passes through it. It then searches a user selected database to detect if any CMEs which launched before the observation date would have crossed the line of sight at the epoch of observation, and produces a number of useful plots. CMEchaser can run as a flat script orcan be installed as a package.

[ascl:2008.014] SuperRAENN: Supernova photometric classification pipeline

SuperRAENN performs photometric classification of supernovae in the following categories: Type I superluminos supernovae, Type II, Type IIn, Type Ia and Type Ib/c. Though the code is optimized for use with complete (rather than realtime) light curves from the Pan-STARRS Medium Deep Survey, the classifier can be trained on other data. SuperRAENN can be used on a dataset containing both spectroscopically labelled and unlabelled SNe; all events will be used to train the RAENN, while labelled events will be used to train the random forest.

[ascl:2008.013] SEDBYS: Spectral Energy Distribution Builder for Young Stars

SEDBYS (Spectral Energy Distribution Builder for Young Stars) provides command-line tools and uses existing functions from standard packages such as Astropy (ascl:1304.002) to collate archival photometric and spectroscopic data. It also builds and inspects SEDS, and automatically collates the necessary software references.

[ascl:2008.012] Ujti: Geodesics in general relativity

Ujti calculates geodesics, gravitational lenses and gravitational redshift in principle, for any metric. Special attention has been given to compact objects, so the current implementation considers only metrics in spherical coordinates.

[ascl:2008.011] Magnetizer: Computing magnetic fields of evolving galaxies

Magnetizer computes time and radial dependent magnetic fields for a sample of galaxies in the output of a semi-analytic model of galaxy formation. The magnetic field is obtained by numerically solving the galactic dynamo equations throughout history of each galaxy. Stokes parameters and Faraday rotation measure can also be computed along a random line-of-sight for each galaxy.

[ascl:2008.010] zeus: Lightning Fast MCMC

Zeus is a pure-Python implementation of the Ensemble Slice Sampling method. Ensemble Slice Sampling improves upon Slice Sampling by bypassing some of that method's difficulties; it also exploits an ensemble of parallel walkers, thus making it immune to linear correlations. Zeus offers fast and robust Bayesian inference and efficient Markov Chain Monte Carlo without hand-tuning. The code provides excellent performance in terms of autocorrelation time and convergence rate, can scale to multiple CPUs without any extra effort, and includes convergence diagnostics.

[ascl:2008.009] SuperNNova: Photometric classification

SuperNNova performs photometric classification by leveraging recent advances in deep neural networks. It can train either a recurrent neural network or random forest to classify light-curves using only photometric information. It also allows additional information, such as host-galaxy redshift, to be incorporated to improve performance.

[ascl:2008.008] Barry: Modular BAO fitting code

Barry compares different BAO models. It removes as many barriers and complications to BAO model fitting as possible and allows each component of the process to remain independent, allowing for detailed comparisons of individual parts. It contains datasets, model fitting tools, and model implementations incorporating different descriptions of non-linear physics and algorithms for isolating the BAO (Baryon Acoustic Oscillation) feature.

[ascl:2008.007] sslf: A simple spectral-line finder

sslf is a simple, effective and useful spectral line finder for 1D data. It utilizes the continuous wavelet transform from SciPy, which is a productive way to find even weak spectral lines.

[ascl:2008.006] Umbrella: Asteroid detection, validation, and identification

Umbrella detects, validates, and identifies asteroids. The core of this software suite, Umbrella2, includes algorithms and interfaces for all steps of the processing pipeline, including a novel detection algorithm for faint trails. A detection pipeline accessible as a desktop program (ViaNearby) builds on the library to provide near real-time data reduction of asteroid surveys on the Wide Field Camera of the Isaac Newton Telescope. Umbrella can read and write MPC optical reports, supports SkyBoT and VizieR querying, and can be extended by user image processing functions to take advantage of the algorithms framework as a multi-threaded CPU scheduler for easy algorithm parallelization.

[ascl:2008.005] PySAP: Python Sparse data Analysis Package

PySAP (Python Sparse data Analysis Package) provides a common API for astronomical and neuroimaging datasets and access to iSAP's (ascl:1303.029) Sparse2D executables with both wrappers and bindings. It also offers a graphical user interface for exploring the provided functions and access to application specific plugins.

[ascl:2008.004] SOT: Spin-Orbit Tomography

Spin-Orbit Tomography (SOT) is a retrieval technique of a two-dimensional map of an Exo-Earth from time-series data of integrated reflection light. The software provides code for the Bayesian version of the static SOT and dynamic mapping (time-varying mapping) with full Bayesian modeling, and tutorials for L2 and Bayesian SOT are available in jupyter notebooks.

[ascl:2008.003] KLLR: Kernel Localized Linear Regression

KLLR (Kernel Localized Linear Regression) generates estimates of conditional statistics in terms of the local slope, normalization, and covariance. This method provides a more nuanced description of population statistics appropriate for very large samples with non-linear trends. The code uses a bootstrap re-sampling technique to estimate the uncertainties and also provides tools to seamlessly generate visualizations of the model parameters.

[ascl:2008.002] PhaseTracer: Cosmological phases mapping

PhaseTracer maps out cosmological phases, and potential transitions between them, for Standard Model extensions with any number of scalar fields. The code traces the minima of effective potential as the temperature changes, and then calculates the critical temperatures at which the minima are degenerate. PhaseTracer can use potentials provided by other packages and can be used to analyze cosmological phase transitions which played an important role in the early evolution of the Universe.

[ascl:2008.001] kinesis: Kinematic modeling of clusters

Kinesis fits the internal kinematics of a star cluster with astrometry and (incomplete) radial velocity data of its members. In the most general model, the stars can be a mixture of background (contamination) and the cluster, for which the (3,3) velocity dispersion matrix and velocity gradient (i.e., dv_x/dx and dv_y/dx) are included. There are also simpler versions of the most general model and utilities to generate mock clusters and mock observations.

[ascl:2007.024] CaTffs: Calcium triplet indexes

CaTffs predicts the strength of calcium triplet indices (CaT*, PaT and CaT) on the basis of empirical fitting functions and performs required interpolations between the different local functions. Together with the indices predictions, the program also computes the random errors associated to such predictions resulting from the covariance matrices of the fits (for the indices CaT* and PaT). This ensures a reliable error index estimation for any combination of input atmospheric parameters.

[ascl:2007.023] CosmoGRaPH: Cosmological General Relativity and (Perfect fluid | Particle) Hydrodynamics

CosmoGRaPH explores cosmological problems in a fully general relativistic setting. Written in C++, it implements various novel methods for numerically solving the Einstein field equations, including an N-body solver, full AMR capabilities via SAMRAI, and raytracing.

[ascl:2007.022] SPARTA: SPectroscopic vARiabiliTy Analysis

SPARTA analyzes periodically-variable spectroscopic observations. Intended for common astronomical uses, SPARTA facilitates analysis of single- and double-lined binaries, high-precision radial velocity extraction, and periodicity searches in complex, high dimensional data. It includes two modules, UNICOR and USuRPER. UNICOR analyzes spectra using 1-d CCF. It includes maximum-likelihood analysis of multi-order spectra and detection of systematic shifts. USuRPER (Unit Sphere Representation PERiodogram) is a phase-distance correlation (PDC) based periodogram and is designed for very high-dimensional data such as spectra.

[ascl:2007.021] JB2008: Empirical Thermospheric Density Model

JB2008 (Jacchia-Bowman 2008) is an empirical thermospheric density model developed as an improved revision to the Jacchia-Bowman 2006 model, based on Jacchia’s diffusion equations. Driving solar indices are computed from on-orbit sensor data, which are used for the solar irradiances in the extreme through far ultraviolet, including x-ray and Lyman-α wavelengths. Exospheric temperature equations are developed to represent the thermospheric EUV and FUV heating. Semiannual density equations based on multiple 81-day average solar indices are used to represent the variations in the semiannual density cycle that result from EUV heating, and geomagnetic storm effects are modeled using the Dst index as the driver of global density changes.

[ascl:2007.020] pygwinc: Gravitational Wave Interferometer Noise Calculator

pygwinc processes and plots noise budgets for ground-based gravitational wave detectors. Its primary feature is a collection of mostly analytic noise calculation functions for various sources of noise affecting detectors, including quantum and seismic noise, mirror coating and substrate thermal noise, suspension fiber thermal noise, and residual gas noise. It is also a generalized noise budgeting tool that allows users to create arbitrary noise budgets for any experiment, not just ground-based GW detectors, using measured or analytically calculated data.

[ascl:2007.019] TROVE: Theoretical ROVibrational Energies

TROVE (Theoretical ROVibrational Energies) performs variational calculations of rovibrational energies for general polyatomic molecules of arbitrary structure in isolated electronic states. The software numerically constructs the kinetic energy operator, which is represented as an expansion in terms of internal coordinates. The code is self-contained, requiring no analytical pre-derivation of the kinetic energy operator. TROVE is also general and can be used with any internal coordinates.

[ascl:2007.018] OSPEX: Object Spectral Executive

OSPEX (Object Spectral Executive) is an object-oriented interface for X-ray spectral analysis of solar data. The next generation of SPEX (ascl:2007.017), it reads and displays input data, selects and subtracts background, selects time intervals of interest, selects a combination of photon flux model components to describe the data, and fits those components to the spectrum in each time interval selected. During the fitting process, the response matrix is used to convert the photon model to the model counts to compare with the input count data. The resulting time-ordered fit parameters are stored and can be displayed and analyzed with OSPEX. The entire OSPEX session can be saved in the form of a script and the fit results stored in the form of a FITS file. Part of the SolarSoft (ascl:1208.013) package, OSPEX works with any type of data structured in the form of time-ordered count spectra; RHESSI, Fermi, SOXS, MESSENGER, Yohkoh, SMM, and SMART data analysis have all been implemented in OSPEX.

[ascl:2007.017] SPEX: Spectral Executive

SPEX provides a uniform interface suitable for the X-ray spectral analysis of a number of solar (or other) instruments in the X and Gamma Ray energy ranges. Part of the SolarSoft (ascl:1208.013) library, this package is suitable for any datastream which can be placed in the form of response vs interval where the response is usually a counting rate (spectrum) and the interval is normally an accumulation over time. Together with an algorithm which can be used to relate a model input spectrum to the observed response, generally a response matrix, the dataset is amenable to analysis with this package. Currently the data from a large number of instruments, including SMM (HXRBS, GRS Gamma, GRS X1, and GRS X2), Yohkoh (HXT, HXS, GRS, and SXT,) CGRO (BATSE SPEC and BATSE LAD), WIND (TGRS), HIREX, and NEAR (PIN). SPEX's next generation software is available in OSPEX (ascl:2007.018), an object-oriented package that is also part of and dependent on SolarSoft.

[ascl:2007.016] ReadPDS: Visualization tools for PDS4 data

ReadPDS reads in and visualizes data from the Planetary Data System in PDS4 format. Tools are available in Python as PDS4Viewer and in IDL as PDS4-IDL. These tools support PDS4 data, including images, spectra, and arrays and provide multiple views of the data, including summary, image, plot, and table views in addition to easy access to metadata such as structure labels and spectral characteristics.

[ascl:2007.015] MAGI: Initial-condition generator for galactic N-body simulations

MAGI (MAny-component Galaxy Initializer) generates initial conditions for numerical simulations of galaxies that resemble observed galaxies and are dynamically stable for time-scales longer than their characteristic dynamical times, taking into account galaxy bulges, discs, and haloes. MAGI adopts a distribution-function-based method and supports various kinds of density models, including custom-tabulated inputs and the presence of more than one disc, and is fast and easy to use.

[ascl:2007.014] PARS: Paint the Atmospheres of Rotating Stars

PARS (Paint the Atmospheres of Rotating Stars) quickly computes magnitudes and spectra of rotating stellar models. It uses the star's mass, equatorial radius, rotational speed, luminosity, and inclination as input; the models incorporate Roche mass distribution (where all mass is at the center of the star), solid body rotation, and collinearity of effective gravity and energy flux.

[ascl:2007.013] wdtools: Spectroscopic analysis of white dwarfs

wdtools characterizes the atmospheric parameters of white dwarfs using spectroscopic data. The flagship class is the generative fitting pipeline (GFP), which fits ab initio theoretical models to observed spectra in a Bayesian framework using high-speed neural networks to interpolate synthetic spectra.

[ascl:2007.012] Line-Stacker: Spectral lines stacking

Line-Stacker stacks both 3D cubes or already extracted spectra and is an extension of Stacker (ascl:1912.019). It is an ensemble of both CASA tasks and native python tasks. Line-Stacker supports image stacking and some additional tools, allowing further analysis of the stack product, are also included in the module.

[ascl:2007.011] FleCSPH: Parallel and distributed SPH implementation based on the FleCSI

FleCSPH is a multi-physics compact application that exercises FleCSI parallel data structures for tree-based particle methods. In particular, the software implements a smoothed-particle hydrodynamics (SPH) solver for the solution of Lagrangian problems in astrophysics and cosmology. FleCSPH includes support for gravitational forces using the fast multipole method (FMM). Particle affinity and gravitation is handled using the parallel implementation of the octree data structure provided by FleCSI.

[ascl:2007.010] DarkHistory: Modified cosmic ionization and thermal histories calculator

DarkHistory calculates the global temperature and ionization history of the universe given an exotic source of energy injection, such as dark matter annihilation or decay. The software simultaneously solves for the evolution of the free electron fraction and gas temperature, and for the cooling of annihilation/decay products and the secondary particles produced in the process. Consequently, we can self-consistently include the effects of both astrophysical and exotic sources of heating and ionization, and automatically take into account backreaction, where modifications to the ionization/temperature history in turn modify the energy-loss processes for injected particles.

[ascl:2007.009] polyMV: Multipolar coefficients converter

polyMV converts multipolar coefficients (alms in healpix order) into Multipole Vectors (MVs) and also Fréchet Vectors (FVs) given a specific multipole. The code uses MPSolve (ascl:2007.008) and is order of magnitudes faster than other existing public codes at high multipoles.

[ascl:2007.008] MPSolve: Multiprecision Polynomial SOLVEr

MPSolve (Multiprecision Polynomial SOLVEr) provides an easy-to-use universal blackbox for solving polynomials and secular equations. Its features include arbitrary precision approximation and guaranteed inclusion radii for the results. It can exploit polynomial structures, taking advantage of sparsity as well as coefficients in a particular domain (i.e., integers or rationals), and can be specialized for specific classes of polynomials.

[ascl:2007.007] PSRVoid: Statistical suite for folded pulsar data

PSRVoid performs RFI excision, flux calibration and timing of folded pulsar data. RFI excision is administered via both traditional and multi-layered deep learning neural network algorithms. The software offers full neural network control (over training set creation and manipulation and network parameters). PSRVoid also contains useful data miners for the ATNF, a multitude of plotting tools, as well as many useful pulsar processing macros such as space velocity simulators and Tempo2 (ascl:1210.015) wrappers.

[ascl:2007.006] PoPE: Population Profile Estimator

PoPE (Population Profile Estimator) analyzes spatial distribution or internal spatial structure problems of samples of astronomical systems. This population-based Bayesian inference model uses the conditional statistics of spatial profile of multiple observables assuming the individual observations are measured with errors of varying magnitude. Assuming the conditional statistics of the observables can be described with a multivariate normal distribution, the model reduces to the conditional average profile and conditional covariance between all observables. The method consists of two steps: (1) reconstructing the average profile using non-parametric regression with Gaussian Processes and (2) estimating the property profiles covariance given a set of independent variable. PoPE is computationally efficient and capable of inferring average profiles of a population from noisy measurements without stacking and binning nor parameterizing the shape of the average profile.

[ascl:2007.005] PeTar: ParticlE Tree & particle-particle & Algorithmic Regularization code for simulating massive star clusters

The N-body code PETAR (ParticlE Tree & particle-particle & Algorithmic Regularization) combines the methods of Barnes-Hut tree, Hermite integrator and slow-down algorithmic regularization (SDAR). It accurately handles an arbitrary fraction of multiple systems (e.g. binaries, triples) while keeping a high performance by using the hybrid parallelization methods with MPI, OpenMP, SIMD instructions and GPU. PETAR has very good agreement with NBODY6++GPU results on the long-term evolution of the global structure, binary orbits and escapers and is significantly faster when used on a highly configured GPU desktop computer. PETAR scales well when the number of cores increase on the Cray XC50 supercomputer, allowing a solution to the ten million-body problem which covers the region of ultra compact dwarfs and nuclear star clusters.

[ascl:2007.004] spex_to_xspec: Convert SPEX output to XSPEC input

spex_to_xspec takes the output from the collisional ionisation equilibrium model in the SPEX spectral modelling and fitting package (ascl:1308.014), and converts it into a form usable by the XSPEC spectral fitting package (ascl:9910.005). For a list of temperatures it computes the line strengths and continuum spectra using SPEX. These are collated and written into an APEC-format table model which can be loaded into Xspec. By allowing SPEX models to be loaded into XSPEC, the program allows easy comparison between the results of the SPEX and APEC codes.

[ascl:2007.003] SPARTA: Subhalo and PARticle Trajectory Analysis

SPARTA is a post-processing framework for particle-based cosmological simulations. The code is written in pure, MPI-parallelized C and is optimized for high performance. The main purpose of SPARTA is to understand the formation of structure in a dynamical sense, namely by analyzing the trajectories (or orbits) of dark matter particles around their halos. Within this framework, the user can add analysis modules that operate on individual trajectories or entire halos. The initial goal of SPARTA was to compute the splashback radius of halos, but numerous other applications have been implemented as well, including spherical overdensity calculations and tracking subhalos via their constituent particles.

[ascl:2007.002] hierArc: Hierarchical analysis of strong gravitational lenses

hierArc hierarchically infers strong lensing mass density profiles and the cosmological parameters, in particular the Hubble constant. The software supports lenses with imaging data and kinematics, and optionally time delays. The kinematics modeling is performed in conjunction with lenstronomy (ascl:1804.012).

[ascl:2007.001] GProtation: Measuring stellar rotation periods with Gaussian processes

GProtation measures stellar rotation periods with Gaussian processes.

This code is no longer being maintained. Please consider using celerite (ascl:1709.008) or exoplanet (ascl:1910.005) instead.

[submitted] SoFiAX

SoFiAX is a web-based platform to merge and interact with the results of parallel execution of SoFiA HI source finding software [ascl:1412.001] and other steps of processing ASKAP Wallaby HI survey data.

[ascl:2006.023] deepSIP: deep learning of Supernova Ia Parameters

deepSIP (deep learning of Supernova Ia Parameters) measures the phase and light-curve shape of a Type Ia Supernova (SN Ia) from an optical spectrum. The package contains a set of three trained Convolutional Neural Networks (CNNs) for the aforementioned purposes, but tools for preprocessing spectra, modifying the neural architecture, training models, and sweeping through hyperparameters are also included.

[ascl:2006.022] MCSED: Spectral energy distribution fitting package for galactic systems

MCSED models the optical, near-infrared and infrared spectral energy distribution (SED) of galactic systems. Its modularity and options make it flexible and able to address the varying physical properties of galaxies over cosmic time and environment and adjust to changes in understanding of stellar evolution, the details of mass loss, and the products of binary evolution through substitution or addition of new datasets or algorithms. MCSED is built to fit a galaxy’s full SED, from the far-UV to the far-IR. Among other physical processes, it can model continuum emission from stars, continuum and line-emission from ionized gas, attenuation from dust, and mid- and far-IR emission from dust and polycyclic aromatic hydrocarbons (PAHs). MCSED performs its calculations by creating a complex stellar population (CSP) out of a linear combination of simple-stellar populations (SSPs) using an efficient Markov Chain Monte Carlo algorithm. It is very quick, and takes advantage of parallel processing.

[ascl:2006.021] FAMED: Extraction and mode identification of oscillation frequencies for solar-like pulsators

The FAMED (Fast and AutoMated pEak bagging with Diamonds) pipeline is a multi-platform parallelized software that performs and automates extraction and mode identification of oscillation frequencies for solar-like pulsators. The pipeline can be applied to a large variety of stars, ranging from hot F-type main sequence, up to stars evolving along the red giant branch, settled into the core-Helium-burning main sequence, and even evolved beyond towards the early asymptotic giant branch. FAMED is based on DIAMONDS (ascl:1410.001), a Bayesian parameter estimation and model comparison by means of the nested sampling Monte Carlo (NSMC) algorithm.

[ascl:2006.020] GenetIC: Initial conditions generator for cosmological simulations

GenetIC generates initial conditions for cosmological simulations, especially for zoom simulations of galaxies. It provides support for "genetic modifications" of specific attributes of simulations to allow study of the impact of such modifications on the outcomes; the code can also produce constrained initial conditions.

[ascl:2006.019] TATOO: Tidal-chronology Age TOOl

TATOO (Tidal-chronology Age TOOl) estimates the age of massive close-in planetary systems, even those subject to tidal spin-up, using the systems' observed properties: the mass of the planet and the star, stellar rotational, and planetary orbital periods. It can also be used as a classical gyrochronological tool and offers first order correction of the impact of tidal interaction on gyrochronology.

[ascl:2006.018] Powderday: Dust radiative transfer package

The dust radiative transfer software Powderday interfaces with galaxy formation simulations to produce spectral energy distributions and images. The code uses fsps (ascl:1010.043) and its Python bindings python-fsps for stellar SEDs, Hyperion (ascl:1207.004) for dust radiative transfer, and works with a variety of packages, including Arepo (ascl:1909.010), Changa (ascl:1105.005), Gasoline (ascl:1710.019), and Gizmo (ascl:1410.003); threaded throughout is yt (ascl:1011.022).

[ascl:2006.017] AstroCatR: Time series reconstruction of large-scale astronomical catalogs

AstroCatR reconstructs celestial objects' time series data for astronomical catalogs. It is a command-line program running on the Linux platform and is implemented in C and Python; AstroCatR's capabilities are based on specialized sky partitioning and MPI parallel programming. The package contains three parts: ETL (extract-transform-load) pre-processing, TS-matching calculation, and time series data retrieval. Once the user obtains the original catalogs, running ETL pre-processing generates a sky zoning file. The TS-matching module marks celestial objects, and finally, running the Query program searches celestial objects from the time series datasets which matched with the target.

[ascl:2006.016] SPISEA: Stellar Population Interface for Stellar Evolution and Atmospheres

SPISEA (Stellar Population Interface for Stellar Evolution and Atmospheres) generates single-age, single-metallicity populations (i.e., star clusters). The software (formerly called PyPopStar) provides control over different parameters, including cluster characteristics (age, metallicity, mass, distance); total extinction, differential extinction, and extinction law; stellar evolution and atmosphere models; stellar multiplicity and Initial Mass Function; and photometric filters. SPISEA can be used to create a cluster isochrone in many filters using different stellar models, generate a star cluster at any age with an unusual IMF and unresolved multiplicity, and make a spectrum of a star cluster in integrated light.

[ascl:2006.015] ARCHI: Add-on pipeline module for background star analysis from CHEOPS data

The CHaracterizing ExOPlanet Satellite (CHEOPS) mission pipeline provides photometry for the central star in its field; ARCHI takes in data from the CHEOPS mission pipeline, analyzes the background stars, and determines the photometry of these stars, thus creating the possibility of producing photometric time-series of several close-by targets at once, in addition to using different stars in the image to calibrate systematic errors.

[ascl:2006.014] CARACal: Containerized Automated Radio Astronomy Calibration pipeline

CARACal (Containerized Automated Radio Astronomy Calibration, formerly MeerKATHI) reduces radio-interferometric data. Developed originally as an end-to-end continuum- and line imaging pipeline for MeerKAT, it can also be used with other radio telescopes. CARACal reduces large data sets and produces high-dynamic-range continuum images and spectroscopic data cubes. The pipeline is platform-independent and delivers imaging quality metrics to efficiently assess the data quality.

[ascl:2006.013] JoXSZ: Joint X-ray and SZ fitting for galaxy clusters in Python

JoXSZ jointly fits the thermodynamic profiles of galaxy clusters from both SZ and X-ray data using a Markov chain Monte Carlo fitting algorithm. It is an enhanced version of preprofit (ascl:1910.002), which fits only SZ data. JoXSZ parameterizes the pressure and electron density profile of a galaxy cluster with a given center and derives the temperature profile as the ratio of these quantities through the ideal gas law. The X-ray and SZ-based temperatures can be similar or different, which allows study of the cluster elongation along line of sight, gas clumping, or calibration uncertainties.

[ascl:2006.012] pxf_kin_err: Radial velocity and velocity dispersion uncertainties estimator

pxf_kin_err estimates the radial velocity and velocity dispersion uncertainties based solely on the shape of a template spectrum used in the fitting procedure and signal-to-noise information. This method can be used for exposure time calculators, in the design of observational programs and estimates on expected uncertainties for spectral surveys of galaxies and star clusters, and as an accurate substitute for Monte-Carlo simulations when running them for large samples of thousands of spectra is unfeasible.

[ascl:2006.011] SERVAL: SpEctrum Radial Velocity AnaLyser

SERVAL calculates radial velocities (RVs) from stellar spectra. The code uses least-squares fitting algorithms to derive the RVs and additional spectral diagnostics. Forward modeling in pixel space is used to properly weight pixel errors, and the stellar templates are reconstructed from the observations themselves to make optimal use of the RV information inherent in the stellar spectra.

[ascl:2006.010] PRISim: Precision Radio Interferometer Simulator

PRISim is a modular radio interferometer array simulator, including the radio sky and instrumental effects, and generates a transit dataset in HD5 format.

[ascl:2006.009] AxionNS: Ray-tracing in neutron stars

AxionNS computes radio light curves resulting from the resonant conversion of Axion dark matter into photons within the magnetosphere of a neutron star. Photon trajectories are traced from the observer to the magnetosphere where a root finding algorithm identifies the regions of resonant conversion. Given the modeling of the axion dark matter distribution and conversion probability, one can compute the photon flux emitted from these regions. The individual contributions from all the trajectories is then summed to obtain the radiated photon power per unit solid angle.

[ascl:2006.008] DeepSphere: Graph-based spherical convolutional neural network for cosmology

DeepSphere implements a generalization of Convolutional Neural Networks (CNNs) to the sphere. It models the discretized sphere as a graph of connected pixels. The resulting convolution is more efficient (especially when data doesn't span the whole sphere) and mostly equivariant to rotation (small distortions are due to the non-existence of a regular sampling of the sphere). The pooling strategy exploits a hierarchical pixelization of the sphere (HEALPix) to analyze the data at multiple scales. The graph neural network model is based on ChebNet and its TensorFlow implementation.

[ascl:2006.007] TATTER: Two-sAmple TesT EstimatoR

TATTER (Two-sAmple TesT EstimatoR) performs two-sample hypothesis test. The two-sample hypothesis test is concerned with whether distributions p(x) and q(x) are different on the basis of finite samples drawn from each of them. This ubiquitous problem appears in a legion of applications, ranging from data mining to data analysis and inference. This implementation can perform the Kolmogorov-Smirnov test (for one-dimensional data only), Kullback-Leibler divergence, and Maximum Mean Discrepancy (MMD) test. The module performs a bootstrap algorithm to estimate the null distribution and compute p-value.

[ascl:2006.006] CosmoLike: Cosmological Likelihood analyses

CosmoLike analyzes cosmological data sets and forecasts future missions. It has been used in the analysis of the Dark Energy Survey and to optimize the Large Synoptic Survey Telescope and the Wide-Field Infrared Survey Telescope, and is useful for innovative theory projects that test new concepts and methods to enhance the constraining power of cosmological analyses.

[ascl:2006.005] CosmoCov: Configuration space covariances for projected galaxy 2-point statistics

CosmoCov computes configuration space covariances for projected galaxy 2-point statistics based on the CosmoLike (ascl:2006.006) framework. The package provides a flat sky covariance module, computed with the 2D-FFTLog (ascl:2006.004) algorithm, and a curved sky covariance module.

[ascl:2006.004] 2D-FFTLog: Generalized FFTLog algorithm for non-Gaussian covariance matrices

2D-FFTLog takes the FFTLog algorithm for 1D Hankel transforms and generalizes it for 2D Hankel transforms. The algorithm is useful for efficiently computing non-Gaussian covariance matrices of cosmological 2-point statistics in configuration space from Fourier space covariances. Fast bin-averaging method is also developed for both the logarithmic binning and general binning choices. C and Python versions of the code are available.

[ascl:2006.003] KinMS: Three-dimensional kinematic modeling of arbitrary gas distributions

The KinMS (KINematic Molecular Simulation) package simulates observations of arbitrary molecular/atomic cold gas distributions from interferometers and line observations from integral field units. This modeling tool is optimized for situations where one has analytic forms for e.g. the rotation curve and/or surface brightness profiles (and may want to fit the parameters of these parametric models). It can, however, also be used as a tilted-ring modelling code. The routines are flexible and have been used in various different applications, including investigating the kinematics of molecular gas in early-type galaxies and determining supermassive black-hole masses from CO interferometric observations. They are also useful for creating mock observations from hydrodynamic simulations, and input data-cubes for further simulation in, for example, CASA's (ascl:1107.013) sim_observe tool. Interactive Data Language (IDL) and Python versions of the code are available.

[ascl:2006.002] PRIISM: Python module for Radio Interferometry Imaging with Sparse Modeling

PRIISM images radio interferometry data using the sparse modeling technique. In addition to generating an image, PRIISM can choose the best image from a range of processing parameters using cross validation. User can obtain statistically optimal images by providing the visibility data with some configuration parameters. The software is implemented as a Python module.

[ascl:2006.001] HEARSAY: Simulations for the probability of alien contact

HEARSAY computes simulations of the causal contacts between emitters in the Galaxy. It implements the Stochastic Constrained Causal Contact Network (SC3Net) model and explores the parameter space of the model for the emergence of communicating nodes through Monte Carlo simulations and analyzes their causal connections. This model for the abundance and duration of civilizations is based on minimal assumptions and three free parameters, with focus on the statistical properties of empirical models instead of an interpretable model with variables to be determined by observation.

[ascl:2005.020] HIPSTER: HIgh-k Power Spectrum EstimatoR

HIPSTER (HIgh-k Power Spectrum EstimatoR) computes small-scale power spectra and isotropic bispectra for cosmological simulations and galaxy surveys of arbitrary shape. The code computes the Legendre multipoles of the power spectrum, P(k), or bispectrum B(k1,k2), by computing weighted pair counts over the simulation box or survey, truncated at some maximum radius. The code can be run either in 'aperiodic' or 'periodic' mode for galaxy surveys or cosmological simulations respectively. HIPSTER also supports weighted spectra, for example when tracer particles are weighted by their mass in a multi-species simulation. Generalization to anisotropic bispectra is straightforward (and requires no additional computing time) and can be added on request.

[ascl:2005.019] MCRaT: Monte Carlo Radiation Transfer

MCRaT (Monte Carlo Radiation Transfer) analyzes the radiation signature expected from astrophysical outflows. MCRaT injects photons in a FLASH (ascl:1010.082) simulation and individually propagates and compton scatters the photons through the fluid until the end of the simulation. This process of injection and propagating occurs for a user specified number of times until there are no more photons to be injected. Users can then construct light curves and spectra with the MCRaT calculated results. The hydrodynamic simulations used with this version of MCRaT must be in 2D; however, the photon propagation and scattering is done in 3D by assuming cylindrical symmetry. Additionally, MCRaT uses the full Klein–Nishina cross section including the effects of polarization, which can be fully simulated in the code. MCRaT works with FLASH hydrodynamic simulations and PLUTO (ascl:1010.045) AMR simulations, with both 2D spherical (r, equation) and 2D cartesian ((x,y) and (r,z)).

[ascl:2005.018] RFCDE: Random Forests for Conditional Density Estimation

RFCDE provides an implementation of random forests designed for conditional density estimation. It computes a kernel density estimate of y with nearest neighbor weightings defined by the location of the evaluation point x relative to the leaves in the random forest.

[ascl:2005.017] cdetools: Tools for Conditional Density Estimates

cdetools provides tools for evaluating conditional density estimates and has applications to photometric redshift estimation and likelihood-free cosmological inference. Available in R and Python, it provides functions for computing a so-called CDE loss function for tuning and assessing the quality of individual probability density functions (PDFs) and diagnostic functions that probe the population-level performance of the PDFs.

[ascl:2005.016] RAPP: Robust Automated Photometry Pipeline

RAPP is a robust automated photometry pipeline for blurred images. RAPP requires that the observed images contain at least three stars and applies bias, dark, and flat field correction on blurred observational raw data; it also uses the median of adjacent pixels to eliminate outliers. It also uses star enhancement and robust image matching, extracts stars, and performs aperture photometry to extract information from blurred images.

[ascl:2005.015] AMPEL: Alert Management, Photometry, and Evaluation of Light curves

AMPEL provides an analysis framework for high-throughput surveys and is suited for streamed data. The package combines the functionality of an alert broker with a generic framework capable of hosting user-contributed code; it encourages provenance and keeps track of the varying information states that a transient displays. The latter concept includes information gathered over time and data policies such as access or calibration levels.

[ascl:2005.014] FETCH: Fast Extragalactic Transient Candidate Hunter

FETCH (Fast Extragalactic Transient Candidate Hunter) provides real-time classification of candidates from single pulse search pipelines. The package takes in a candidate file of frequency-time and DM-time data and, for each candidate and choice of model, provides the probability that the candidate is an FRB. FETCH also provides a framework for fine-tuning the models to further improve its performance for particular backends.

[ascl:2005.013] qubefit: MCMC kinematic modeling

qubefit fits an observed data cube to generate a model cube from a user-defined emission model. The model cube is convolved with the observed beam, after which residuals between the convolved model and the observed data cube are minimized using a Markov chain Monte Carlo approach. qubefit also determines estimates of the uncertainty for each parameter of the model.

[ascl:2005.012] 2DBAT: 2D Bayesian Automated Tilted-ring fitter

2DBAT implements Bayesian fits of 2D tilted-ring models to derive rotation curves of galaxies. It performs 2D tilted-ring analysis based on a Bayesian Markov Chain Monte Carlo (MCMC) technique, thus quantifying the kinematic geometry of galaxy discs, and deriving high-quality rotation curves that can be used for mass modeling of baryons and dark matter halos.

[ascl:2005.011] gotetra: Cosmic velocity fields tracking through the use of tetrahedra

gotetra uses phase-space tesselation techniques to extract information about cosmological N-body simulations. The key applications of this Go-based code are the measurement of splashback shells around halos and the generation of high resolution images of density fields. The package includes routines to generates 3D and 2D (projected) density fields from a particle snapshot generated by a cosmological N-body simulation, measure density along lines of sight from the center of halos, and compresse the position space data from cosmological N-body simulations. Included are two helper libraries with functions for calculating cosmological quantities and computing a number of useful mathematical functions.

[ascl:2005.010] NNKCDE: Nearest Neighbor Kernel Conditional Density Estimation

NNKCDE is a simple and easily interpretable Conditional Density Estimation (CDE) method. It computes a kernel density estimate of y using the k nearest neighbors of the evaluation point x. The model has only two tuning parameters: the number of nearest neighbors k and the bandwidth h of the smoothing kernel in y-space. Both tuning parameters are chosen in a principled way by minimizing the CDE loss on validation data.

[ascl:2005.009] s3PCF: Compute the 3-point correlation function in the squeezed limit

s3PCF computes the 3-point correlation function (3PCF) in the squeezed limit given galaxy positions and pair positions. The code is currently written specifically for the Abacus simulations, but the main functionalities can be also easily adapted for other galaxy catalogs with the appropriate properties.

[ascl:2005.008] HiFLEx: Echelle data reduction pipeline

HiFLEx reduces echelle data taken with a single or bifurcated fiber input. It takes a FITS image file (i.e., a CCD image) and runs data reduction steps, extracts out orders from an Echelle spectrograph (regardless of separation and curvature, as long as orders are distinguishable from one-another), applies the wavelength correction, measures the radial velocity, and performs further calibration steps.

[ascl:2005.007] Carpyncho: VVV Catalog browser toolkit

Carpyncho browses catalogs to search for and characterize time variable data of the Vista Variables in the Via Lactea (VVV) Survey. The stacked pawprint data from the Cambridge Astronomical Science Unit's (CASU) Vista Data Flow System (VDFS) v>= 1.3 catalogs have been crossed matched with the VDFS CASU v1.3 tile catalogs into Parquet files, allowing detection and classification of periodic variables within this dataset.

[ascl:2005.006] FFANCY: Fast Folding Algorithm for pulsar searching

FFANCY uses the Fast Folding Algorithm (FFA) on a distributed-computing framework to search for pulsars in time-domain series data. This enables the algorithm to be applied to all-sky blind pulsar surveys. The package runs an implementation of the FFA on real or simulated pulsar time series data in either SIGPROC (ascl:1107.016) or PRETSO (ascl:1107.017) format with a choice of additional algorithms to be used in the evaluation of each folded profile and outputs a periodogram along with other output threads used for testing. It also contains routines that convert the periodogram output into a list of pulsar candidates with options for candidate grouping and harmonic matching, generate simulated pulsar profiles for use in testing profile evaluation algorithms independent of the FFA, provide basic statistics for the folded profiles produced by progeny, test individual profiles using profiles produced by progeny, and other complementary functions.

[ascl:2005.005] RoLo: Calculate radius and potential of the Roche Lobe

RoLo (Roche Lobe) calculates the radius and potential of the Roche Lobe for any specified direction, and also gives some other commonly used quantities (such as the Lagrange points). The calculator is valid for any mass ratio q between 0.01 and 100. The coordinates are spherical-polar (R, theta, phi) centered on one star (M1), with the x-axis (theta=pi/2, phi=0) pointing towards the other star (M2). The mass ratio is defined as q=M2/M1. Distances are given in units of the binary separation, a. A circular orbit is assumed.

[ascl:2005.004] REDFIT: Red-noise spectra directly from unevenly spaced time series

Time series are commonly unevenly spaced in time make it difficult to obtain an accurate estimate of their typical red-noise spectrum. REDFIT overcomes this problem by fitting a first-order autoregressive (AR1) process directly to unevenly spaced time series. Hence, interpolation in the time domain and its inevitable bias can be avoided. The program can be used to test if peaks in the spectrum of a time series are significant against the red-noise background from an AR1 process.

[ascl:2005.003] RM-Tools: Rotation measure (RM) synthesis and Stokes QU-fitting

RM-Tools analyzes radio polarization data, specifically the use of Faraday rotation measure synthesis and Stokes QU model fitting. It contains routines for both single-pixel 1D polarized spectra as well as 3D polarization cubes. RM-Tools is intended to serve as a toolkit for studies of polarized radio sources and measurements of their Faraday rotation. RM-Tools is the core package for the pipelines used for the POlarized Sky Survey of the Universe's Magnetism (POSSUM) and the polarization component of the Very Large Array Sky Survey (VLASS). The package is maintained by the Canadian Initiative for Radio Astronomy Data Analysis (CIRADA; cirada.org).

[ascl:2005.002] michi2: SED and SLED fitting tool

michi2 fits combinations of arbitrary numbers of libraries/components to a given observational data. Written in C++ and Python, this chi-square fitting tool can fit a galaxy's spectral energy distribution (SED) with stellar, active galactic nuclear, dust and radio SED templates, and fit a galaxy's spectral line energy distribution (SLED) with one or more gas components using radiative transfer LVG model grid libraries.

michi2 first samples the high-dimensional parameter space (N1*N2*N3*..., where N is the number of independent templates in each library, and 1/2/3 is the ID of components) in an optimized way for a few thousand or tens of thousand times to compute the chi-square to the input observational data, then uses Python scripts to analyze the chi-square distribution and derive the best-fit, median, lower and higher 1-sigma values for each parameter in each library/component. This tool is useful for fitting larger number of templates and arbitrary combinations of libraries/components, including some constraining of one library/component onto another.

[ascl:2005.001] RID: Relativistic Image Doubling in water Cherenkov detectors

RID (Relativistic Image Doubling in water Cherenkov detectors) uses Monte Carlo simulations to find the relative fraction of charged, relativistic particles entering a HAWC-like Water Cherenkov Detector that can cause a Relativistic Image Doubling (RID) effect visible to at least one of the internal detectors. The technique is available in C++ and Fortran; RID also includes python code for the horizontal incidence of the muon inside the tank.

[ascl:2004.016] PRECISION: Astronomical infrared observations data reduction

PRECISION reduces astronomical IR imaging data. Written with SPHERE data in mind, it provides a fast and easy reduction of bright sources suitable for science. While it may not extract the absolute maximum amount of science, the objective is to provide a means to get science-ready data with minimal computing time or human interaction.

[ascl:2004.015] IRDAP: SPHERE-IRDIS polarimetric data reduction pipeline

IRDAP (IRDIS Data reduction for Accurate Polarimetry) accurately reduces SPHERE-IRDIS polarimetric data. It is a highly-automated end-to-end pipeline; its core feature is model-based correction of the instrumental polarization effects. IRDAP handles data taken both in field- and pupil-tracking mode and using the broadband filters Y, J, H and Ks. Data taken with the narrowband filters can be reduced as well, although with a somewhat worse accuracy. For pupil-tracking observations IRDAP can additionally apply angular differential imaging.

[ascl:2004.014] PyKat: Python interface and tools for Finesse

The Python wrapper PyKat extends the optical interferometer modeling software Finesse (ascl:2004.013). It provides an efficient GUI for conducting complex numerical simulations and manipulating and viewing simulation setups, and enables the use of Python's extensive scientific software ecosystem.

[ascl:2004.013] Finesse: Frequency domain INterfErometer Simulation SoftwarE

Finesse is a numeric simulation for laser interferometers and models parametric instabilities, easily providing the required mechanical-to-optical transfer functions in imperfect and arbitrary interferometer configurations using Hermite-Gaussian beams. The code has been used to apply limits to the number and type of higher order modes used in simulation and investigate the potential use of higher order Laguerre-Gauss modes to reduce thermal noise in future gravitational wave detector designs. The PyKat wrapper (ascl:2004.014) helps automate complex Finesse tasks.

[ascl:2004.012] ArviZ: Exploratory analysis of Bayesian models

ArviZ provides backend-agnostic tools for diagnostics and visualizations of Bayesian inference by first converting inference data into xarray objects. It includes functions for posterior analysis, model checking, comparison and diagnostics. ArviZ’s functions work with NumPy arrays, dictionaries of arrays, xarray datasets, and have built-in support for PyMC3 (ascl:1610.016), PyStan, CmdStanPy, Pyro (ascl:1507.018), NumPyro, emcee (ascl:1303.002), and TensorFlow Probability objects. A Julia wrapper is also available.

[ascl:2004.011] FUNDPAR: Deriving FUNDamental PARameters from equivalent widths

FUNDPAR determines fundamental parameters of solar-type stars, by using as input the Equivalent Widths of Fe I,II lines. The code uses solar-scaled ATLAS9 model atmospheres with NEWODF opacities, together with the 2009 version of the MOOG (ascl:1202.009) program. Parameter files control different details, such as the mixing-length parameter, the overshooting, and the damping of the lines. FUNDPAR also derives the uncertainties of the parameters.

[ascl:2004.010] kombine: Kernel-density-based parallel ensemble sampler

kombine is an ensemble sampler built for efficiently exploring multimodal distributions. By using estimates of ensemble’s instantaneous distribution as a proposal, it achieves very fast burnin, followed by sampling with very short autocorrelation times.

[ascl:2004.009] stardate: Measure precise stellar ages

stardate measures precise stellar ages by combining isochrone fitting with gyrochronology (rotation-based ages) to increase the precision of stellar ages on the main sequence. The best possible ages provided by stardate will be for stars with rotation periods, though ages can also be predicted for stars without rotation periods. stardate is an extension to isochrones that incorporates gyrochronology and the code reverts back to isochrones when no rotation period is provided.

[ascl:2004.008] PPMAP: Column density mapping with extra dimensions

PPMAP provides column density mapping with extra dimensions (temperature and dust opacity index); it generate image cubes of differential column density as a function of (x,y) sky position and temperature for diffuse dusty structures. The code incorporates parallel processing using OpenMP for some of the more CPU-intensive steps. It is currently configured for the "Raven" cluster at Cardiff University and runs in a mode in which the computations are split between 16 separate nodes, each of which uses 16 cores with OpenMP.

[ascl:2004.007] PyCosmo: Multi-purpose cosmology calculation tool

PyCosmo provides accurate predictions for cosmological observables including background quantities, power spectra and Limber and beyond-Limber angular power spectra. The software is designed to be interactive and user-friendly. It is available for download and is also offered on an interactive platform (PyCosmo Hub), which allows users to perform their own computations using Jupyter Notebooks without installing any software.

[ascl:2004.006] ASTRAEUS: Semi-analytical semi-numerical galaxy evolution and reionization code

ASTRAEUS (semi-numerical rAdiative tranSfer coupling of galaxy formaTion and Reionization in n-body dArk mattEr simUlationS) self-consistently derives the evolution of galaxies and the reionization of the IGM based on the merger trees and density fields of a DM-only N-body simulation. It models gas accretion, star formation, SN feedback, the time and spatial evolution of the ionized regions, accounting for recombinations, HI fractions and photoionization rates within ionized regions, and radiative feedback. ASTRAEUS is for studying the galaxy-reionization interplay in the first billion years. The underlying code is written in C and is MPI-parallelized; its modular design allows new physical processes and galaxy properties to be added easily. ASTRAEUS can be run on a tree-branch-by-tree-branch basis (i.e., fully vertical) or on a redshift-by-redshift basis (i.e., fully horizontal) when evolving the galaxies by using local horizontal merger trees.

[ascl:2004.005] PyWD2015: Wilson-Devinney code GUI

PyWD2015 provides a modern graphical user interface (GUI) for the 2015 version of the Wilson-Devinney (WD) code (ascl:2004.004). The GUI is written in Python 2.7 and uses the Qt4 interface framework. At its core, PyWD2015 generates lcin and dcin files from user inputs and sends them to WD, then reads and visualizes the output in a user-friendly way. It also includes tools that make the technical aspects of the modeling process significantly easier.

[ascl:2004.004] WD: Wilson-Devinney binary star modeling

Wilson-Devinney binary star modeling code (WD) is a complete package for modeling binary stars and their eclipes and consists of two main modules. The LC module generates light and radial velocity curves, spectral line profiles, images, conjunction times, and timing residuals; the DC module handles differential corrections, performing parameter adjustment of light curves, velocity curves, and eclipse timings by the Least Squares criterion. WD handles eccentric orbits and asynchronous rotation, and can compute velocity curves (with proximity and eclipse effects). It offers options for detailed reflection and nonlinear (logarithmic law) limb darkening, adjustment of spot parameters, an optional provision for spots to drift over the surface, and can follow light curve development over large numbers of orbits. Absolute flux solution allow Direct Distance Estimation (DDE) and there are improved solutions for ellipsoidal variables and for eclipsing binaries (EBs) with very shallow eclipses. Absolute flux solutions also can estimate temperatures of both EB components under suitable circumstances.

[ascl:2004.003] IllinoisGRMHD: GRMHD code for dynamical spacetimes

IllinoisGRMHD is an open-source, highly-extensible rewrite of the original closed-source general relativistic (ideal) magnetohydrodynamics (GRMHD) code of the Illinois Numerical Relativity (ILNR) Group. Reducing the learning curve was the primary focus of this rewrite, with the goal of facilitating community involvement in the code's use and development, as well as reducing the human effort necessary to generate new science. IllinoisGRMHD also saves computer time, generating roundoff-precision identical output to the original code on adaptive-mesh grids while being nearly twice as fast at scales of hundreds to thousands of cores.

[ascl:2004.002] Tangra: Software for video photometry and astrometry

Tangra performs scientific grade data reduction of GPS time-tagged video observations, including reduction of stellar occultation light curves and astrometry of close flybys of Near Earth Objects. It offers Dark and Flat frame image correction, PSF and aperture photometry, multiple methods for deriving a background as well as extensibility via add-ins. Tangra is actively developed for Windows and the current version of the software supports UCAC2, UCAC3, UCAC4, NOMAD, PPMXL and Gaia DR2 star catalogues for astrometry. The software can perform motion-fitting for fast objects and derive a mini-normal astrometric positions. The supported video file formats are AVI, SER, ADV and AAV. Tangra can be also used with observations recorded as a sequence of FITS files. There are also versions for Linux and OS-X with more limited functionality.

[ascl:2004.001] Locus: Optimized differential photometry

Locus implements the Locus Algorithm, which maximizes the performance of differential photometry systems by optimizing the number and quality of reference stars in the Field of View with the target.

[ascl:2003.014] Torch: Coupled gas and N-body dynamics simulator

Torch simulates coupled gas and N-body dynamics in astrophysical systems such as newly forming star clusters. It combines the FLASH (ascl:1010.082) code for gas dynamics and the ph4 code for direct N-body evolution via the AMUSE framework.

[ascl:2003.013] AstroHOG: Analysis correlations using the Histograms of Oriented Gradients

AstroHOG compares extended spectral-line observations (PPV cubes); the histogram of oriented gradients (HOG) technique takes as input two PPV cubes and provides an estimate of their spatial correlation across velocity channels to study spatial correlation between different tracers of the ISM.

[ascl:2003.012] PYSOLATOR: Remove orbital modulation from a binary pulsar and/or its companion

PYSOLATOR removes the orbital modulation from a binary pulsar and/or its companion. In essence, it subtracts the predicted Roemer delay for the given orbit and then resamples the time series so as to make the signal appear as if it were emitted from the barycenter of the binary system, making the search for pulses easier and faster.

[ascl:2003.011] HOMER: A Bayesian inverse modeling code

HOMER (Helper Of My Eternal Retrievals) is a machine-learning-accelerated Bayesian inverse modeling code. Given some data and uncertainties, the code determines the posterior distribution of a model. HOMER uses MC3 (ascl:1610.013) for its MCMC; its forward model is a neural network surrogate model trained by MARGE (ascl:2003.010). The code produces plots of the 1D marginalized posteriors, 2D pairwise posteriors, and parameter history traces, and can also overplot the 1D and 2D posteriors for comparison with another posterior. HOMER computes the Bhattacharyya coefficient to compare the similarity of two 1D marginalized posteriors.

[ascl:2003.010] MARGE: Machine learning Algorithm for Radiative transfer of Generated Exoplanets

MARGE (Machine learning Algorithm for Radiative transfer of Generated Exoplanets) generates exoplanet spectra across a defined parameter space, processes the output, and trains, validates, and tests machine learning models as a fast approximation to radiative transfer. It uses BART (ascl:1608.004) for spectra generation and modifies BART’s Bayesian sampler (MC3, ascl:1610.013) with a random uniform sampler to propose models within a defined parameter space. More generally, MARGE provides a framework for training neural network models to approximate a forward, deterministic process.

[ascl:2003.009] TOASTER: Times-Of-Arrival Tracker

TOASTER is a pulse times-of-arrival (TOA) tracker. It stores reduced/folded observations, meta data, templates, parfiles, TOAs, and timefiles in an organized manner using an SQL database. TOASTER also provides a full-featured python toolkit for reliably interacting with the data and database, and provides scripts that, for example, list and summarize the TOAs in the data base, and generate TOA files in multiple formats. The framework can also be used to generate TOAs from observations using flexible and reproducible plugins referred to as "manipulators".

[ascl:2003.008] CoastGuard: Automated timing data reduction pipeline

CoastGuard reduces Effelsberg data; it is written in python and based on PSRCHIVE (ascl:1105.014). Though primarily designed for Effelsberg PSRIX data, it contains components sufficiently general for use with psrchive-compatible data files from other observing systems. In particular, the radio frequency interference (RFI) removal algorithm has been applied to data from the Parkes Telescope and has also been adopted by the LOFAR pulsar timing data reduction pipeline.

[ascl:2003.007] RAPID: Real-time Automated Photometric IDentification

RAPID (Real-time Automated Photometric IDentification) classifies multiband photometric light curves into several different transient classes. It uses a deep recurrent neural network to produce time-varying classifications, and because it does not rely on deriving computationally expensive features from the data, it is well suited for processing alerts that wide-field surveys such as the Zwicky Transient Facility (ZTF) and the Large Synoptic Survey Telescope (LSST) will produce.

[ascl:2003.006] PORTAL: POlarized Radiative Transfer Adapted to Lines

PORTAL (POlarized Radiative Transfer Adapted to Lines), a 3D polarized radiative transfer code, simulates the emergence of polarization in the emission of atomic or molecular (sub-)millimeter lines. Written in Fortran90, PORTAL can be used in standalone mode or can process the output of other 3D radiative transfer codes

[ascl:2003.005] RHT: Rolling Hough Transform

The RHT (Rolling Hough Transform) measures linear intensity as a function of orientation in images. This machine vision algorithm works on any image-space (2D) data, and quantifies the presence of linear structure as a function of orientation. The RHT can be used to identify linear features in images, to quantify the orientation of structure in images, and to map image intensity from 2D x-y space to 3D x-y-orientation space. An option in the code allows the user to quantify intensity as a function of direction (modulo 2pi) rather than orientation (modulo pi). The RHT was first used to discover that filamentary structures in neutral hydrogen emission are aligned with the ambient magnetic field.

[ascl:2003.004] scousepy: Semi-automated multi-COmponent Universal Spectral-line fitting Engine

scousepy is a Python implementation of spectral line-fitting IDL code SCOUSE (ascl:1601.003). It fits a large amount of complex astronomical spectral line data in a systematic way.

[ascl:2003.003] acorns: Agglomerative Clustering for ORganising Nested Structures

acorns generates a hierarchical system of clusters within discrete data by using an n-dimensional unsupervised machine-learning algorithm that clusters spectroscopic position-position-velocity data. The algorithm is based on a technique known as hierarchical agglomerative clustering. Although acorns was designed with the analysis of discrete spectroscopic position-position-velocity (PPV) data in mind (rather than uniformly spaced data cubes), clustering can be performed in n-dimensions and the algorithm can be readily applied to other data sets in addition to PPV measurements.

[ascl:2003.002] MAGNETAR: Histogram of relative orientation calculator for MHD observations

MAGNETAR is a set of tools for the study of the magnetic field in simulations of MHD turbulence and polarization observations. It calculates the histogram of relative orientation between density structure in the magnetic field in data cubes from simulations of MHD turbulence and observations of polarization using the method of histogram of relative orientations (HRO).

[ascl:2003.001] TESS-Point: High precision TESS pointing tool

TESS-Point converts astronomical target coordinates given in right ascension and declination to detector pixel coordinates for the MIT-led NASA Transiting Exoplanet Survey Satellite (TESS) spacecraft. The program can also provide detector pixel coordinates for a star by TESS input catalog identifier number and common astronomical name. Tess-Point outputs the observing sector number, camera number, detector number, and pixel column and row.

[ascl:2002.022] DISKMODs: Accretion Disk Radial Structure Models

DISKMODs provides radial structure models of accretion disk solutions. The following models are included: Novikov-Thorne thin disk model and Sadowski polytropic slim disk model. Each model implements a common interface that gives the radial dependence of selected geometrical, physical and thermodynamic quantities of the accretion flow. The model interpolates through a set of tabulated numerical solutions. These solutions are computed for a reference mass M=10 Msun. The model can rescale the disk structure to any mass, with masses in the range of 5-20 Msun giving reasonably good results.

[ascl:2002.021] CR-SISTEM: Symplectic integrator for lunar core-mantle and orbital dynamics

CR-SISTEM models lunar orbital and rotational dynamics, taking into account the effects of a liquid core. Orbits of the Moon and Earth are fully integrated, and other planets (or additional point-mass satellites) may be included in the integration. Lunar and solar tides on Earth, eccentricity and obliquity tides on the Moon, and lunar core-mantle friction are included. The integrator is one file (crsistem5.for) written in FORTRAN 90, uses seven input files (settings.in, planets.in, moons.in, tidal.in, lunar.in, precess.in and core.in), and has at least eight output files (planet101.out, moon101.out, pole.out, spin_orb.out, spin_ecl.out, cspin_ecl.out, long.out and clong.out); additional moons and planets would add more output. The input files provided with the code set up a 1 Myr simulation of a slow-spinning Moon on an orbit of 40 Earth radii, which will then dynamically relax to the lowest-energy state (in this case it is a synchronous rotation with a core spinning separately from the mantle).

[ascl:2002.020] ExoCAM: Exoplanet Community Atmospheric Model

ExoCAM adapts the NCAR Community Earth System Model (CESM) for planetary and exoplanetary applications. The system files, source code, initial conditions files, and namelists provided do not run standalone. ExoCAM is a patch to be used with standard distributions of CESM version 1.2.1 (http://www.cesm.ucar.edu/models/current.html), and is also intended to be run with ExoRT (ascl:2002.019), a correlated-k radiative transfer package.

[ascl:2002.019] ExoRT: Two-stream radiative transfer code

ExoRT is a flexible, two-stream radiative transfer code that interfaces with CAM/CESM (http://www.cesm.ucar.edu/models/current.html) or 1D offline; it is also used with ExoCAM (ascl:2002.020). Quadrature is used for shortwave and hemispheric mean is used for longwave. The gas phase optical depths are calculate using a correlated K-distribution method, with overlapping bands treated using an amount weighted scheme. Cloud optics are treated using mie scattering for both liquid and ice clouds, and cloud overlap is treated using Monte Carlo Independent Column Approximation.

[ascl:2002.018] Bayesfit: Command-line program for combining Tempo2 and MultiNest components

Bayesfit pulls together Tempo2 (ascl:1210.015) and MultiNest (ascl:1109.006) components to provide additional functionality such as the specification of priors; Nelder–Mead optimization of the maximum-posterior point; and the capability of computing the partially marginalized likelihood for a given subset of timing-model parameters. Bayesfit is a single python command-line application.

[ascl:2002.017] libstempo: Python wrapper for Tempo2

libstempo uses the Tempo2 library (ascl:1210.015) to load a pulsar's tim/par files, providing Python access to the TOAs, the residuals, the timing-model parameters, the fit procedure, and more.

[ascl:2002.016] Cobra: Bayesian pulsar searching

Cobra uses single pulse time series data to search for and time pulsars, performing a fully phase coherent timing analysis. The GPU-accelerated Bayesian analysis package, written in Python, incorporates models for both isolated and accelerated systems, as well as both Keplerian and relativistic binaries. Cobra builds a model pulse train that incorporates effects such as aliasing, scattering and binary motion and a simple Gaussian profile and compares this directly to the data; the software can thus combine data over multiple frequencies, epochs, or even across telescopes.

[ascl:2002.015] GizmoAnalysis: Read and analyze Gizmo simulations

GizmoAnalysis reads and analyzes N-body simulations run with the Gizmo code (ascl:1410.003). Written in Python, it was developed primarily to analyze FIRE simulations, though it is usable with any Gizmo snapshot files. It offers the following functionality: reads snapshot files and converts particle data to physical units; provides a flexible dictionary class to store particle data and compute derived quantities on the fly; plots images and properties of particles; and generates region files for input to MUSIC (ascl:1311.011) to generate cosmological zoom-in initial conditions. GizmoAnalysis also computes rates of supernovae and stellar winds, including their nucleosynthetic yields, as used in FIRE simulations. The software package includes a tutorial in a Jupyter notebook.

[ascl:2002.014] HaloAnalysis: Read and analyze halo catalogs and merger trees

HaloAnalysis reads and analyzes halo/galaxy catalogs, generated from Rockstar (ascl:1210.008) or AHF (ascl:1102.009), and merger trees generated from Consistent Trees (ascl:1210.011). Written in Python, it offers the following functionalities: reads halo/galaxy/tree catalogs from multiple file formats; assigns baryonic particles and galaxy properties to dark-matter halos; combines and re-generates halo/galaxy/tree files in hdf5 format; analyzes properties of halos/galaxies; and selects halos to generate zoom-in initial conditions. The code includes a tutorial in the form of a Jupyter notebook.

[ascl:2002.013] GWecc: Calculator for pulsar timing array signals due to eccentric supermassive binaries

GWecc computes the pulsar timing array (PTA) signals induced by eccentric supermassive binaries. Written in C++, it computes the plus/cross polarizations as well as Earth and pulsar terms of the PTA signal given the binary parameters and the sky locations of the binary and the pulsar. A python wrapper is included through which GWecc can be used to simulate, search for and constrain gravitational wave-emitting eccentric supermassive binaries using packages such as ENTERPRISE (ascl:1912.015) and libstempo (ascl:2002.017).

[ascl:2002.012] DMRadon: Radon Transform calculation tools

DMRadon calculates the Radon Transform for use in the analysis of Directional Dark Matter Direct Detection. The code can calculate speed distributions, velocity distribution, velocity integral (eta) and Radon Transforms or a standard Maxwell-Boltzmann distribution. DMRadon also calculates the velocity distribution averaged over different angular bins.

[ascl:2002.011] PyHammer: Python spectral typing suite

PyHammer performs rapid and automatic spectral classification of stars according to the Morgan-Keenan classification system; it is a Python revision of the IDL code The Hammer (ascl:1405.003) and offers additional capabilities. Working in the range of 3,650-10,200 Angstroms, the automatic spectral typing algorithm compares important spectral lines to template spectra and determines the best matching spectral type, ranging from O to L type stars. The code can also determine a star's metallicity ([Fe/H]) and radial velocity shifts. Once the automatic classification algorithm has run, PyHammer provides the user an interface for determining spectral types visually by comparing their spectra to provided templates.

[ascl:2002.010] Apercal: Pipeline for the Westerbork Synthesis Radio Telescope Apertif upgrade

Apercal is a dedicated, automated data reduction and analysis pipeline written for the Apertif (APERture Tile In Focus) upgrade to the Westerbork Synthesis Radio Telescope. This upgrade dramatically increases the field of view and survey speed of the telescope and is being used for survey observations that can produce 5 terabytes of data for each observation. Apercal uses existing and new tools and parallelization to provide the performance needed for the large volume of data produced Apertif surveys. The software is written entirely in Python and uses third–party astronomical software, such as AOFlagger (ascl:1010.017), CASA (ascl:1107.013), and Miriad (ascl:1106.007), for certain tasks. Apercal is modular, making it possible to run specific modules manually instead of the full pipeline, and information can be exchanged between modules because status parameters are written and read from a python pickled dictionary file. The pipeline can also run fully automatically.

[ascl:2002.009] DASH: Deep Automated Supernova and Host classifier

DASH classifies the type, age, redshift and host for any supernova spectra based on the learned features, through use of a deep convolutional neural network to train a matching algorithm, of each supernova’s type and age. The Python library allows a user to classify spectra; the software is fast and can classify thousands of spectra in seconds. A graphical interface that enables a user to view and classify a spectrum is also available.

[ascl:2002.008] ExoSim: Simulator for predicting signal and noise in transit spectroscopy observations

ExoSim models host star and planet transit events, simulating the temporal change in stellar flux due to the light curve. It is wavelength-dependent, using an input planet spectrum to determine the light curve depth for any given wavelength and can capture temporal effects, such as correlated noise. ExoSim's star spot simulator produces simulated observations that include spot and facula contamination. The code is flexible and can be generically applied to different instruments that simulate specific time-dependent processes.

[ascl:2002.007] ProSpect: Spectral generation package

ProSpect generates good quality SEDs that can be used to estimate the broad band photometric properties of galaxies that have known star formation and gas metallicity histories. It allows for complex star formation and metallicity histories to be specified, and can be used in a generative or fitting (Bayesian) mode. ProSpect provides a high level interface to the BC03 (low and high resolution) and EMILES libraries, as well as the Dale 2014 dust emission templates. Its source code is available for download, and it is also available as an interactive web tool.

[ascl:2002.006] ScamPy: Sub-halo Clustering and Abundance Matching Python interface

ScamPy "paints" an observed population of cosmological objects on top of the DM-halo/subhalo hierarchy obtained from DM-only simulations. The method combines the Halo Occupation Distribution (HOD) method with sub-halo abundance matching (SHAM); the two processes together are dubbed Sub-halo clustering and abundance matching (SCAM). The procedure requires applying the two methods in sequence; by applying the HOD scheme, the host sub-haloes are selected, and the SHAM algorithm associates an observable property of choice to each sub-halo. The provided python interface allows users to load and populate DM halos and sub-halos obtained by FoF and SUBFIND algorithms applied to DM snapshots at any redshift. The software is highly-optimized and flexible.

[ascl:2002.005] ODUSSEAS: Observing Dwarfs Using Stellar Spectroscopic Energy-Absorption Shapes

ODUSSEAS (Observing Dwarfs Using Stellar Spectroscopic Energy-Absorption Shapes) uses machine learning to derive the Teff and [Fe/H] of M dwarf stars by using their optical spectra obtained by different spectrographs with different resolutions. The software uses the measurement of the pseudo equivalent widths for more than 4000 stellar absorption lines and the machine learning Python package scikit-learn (https://scikit-learn.org/stable/) to predict the stellar parameters.

[ascl:2002.004] triceratops: Candidate exoplanet rating tool

triceratops (Tool for Rating Interesting Candidate Exoplanets and Reliability Analysis of Transits Originating from Proximate Stars) validates planet candidates from the Transiting Exoplanet Survey Satellite (TESS). The code calculates the probabilities of a wide range of transit-producing scenarios using the primary transit of the planet candidate and preexisting knowledge of its host and nearby stars. It then uses the known properties of these stars to calculate star-specific priors for each scenario with estimates of stellar multiplicity and planet occurrence rates.

[ascl:2002.003] ORIGIN: detectiOn and extRactIon of Galaxy emIssion liNes

ORIGIN performs blind detection of faint emitters in MUSE datacubes. The algorithm is tuned to detect faint spatial-spectral emission signatures while allowing for a stable false detection rate over the data cube, and providing in the same time an automated and reliable estimation of the purity. ORIGIN implements a nuisance removal part based on a continuum subtraction combining a Discrete Cosine Transform and an iterative Principal Component Analysis and a detection part based on the local maxima of Generalized Likelihood Ratio test statistics obtained for a set of spatial-spectral profiles of emission line emitters. In addition, it performs a purity estimation in which the proportion of true emission lines is estimated from the data itself: the distribution of the local maxima in the noise only configuration is estimated from that of the local minima.

[ascl:2002.002] RASCAS: Resonant line transfer in AMR simulations

The massively parallel code RASCAS (RAdiative SCattering in Astrophysical Simulations) performs radiative transfer on an adaptive mesh with an octree structure using the Monte Carlo technique. The code features full MPI parallelization, domain decomposition, adaptive load-balancing, and a standard peeling algorithm to construct mock observations. The radiative transport of resonant line photons through different mixes of species (e.g. HI, SiII, MgII, FeII), including their interaction with dust, is implemented in a modular fashion to allow new transitions to be easily added to the code. RASCAS may also be used to propagate photons at any wavelength (e.g. stellar continuum or fluorescent lines), and has been designed to be easily customizable and to process simulations of arbitrarily large sizes on large supercomputers.

[ascl:2002.001] SDAR: Slow-Down Algorithmic Regularization code for solving few-body problems

SDAR (Slow-Down Algorithmic Regularization) simulates the long-term evolution of few-body systems such as binaries and triples. The algorithm used provides a few orders of magnitude faster performance than the classical N-body method. The secular evolution of hierarchical systems, e.g. Kozai-Lidov oscillation, can be well reproduced. The code is written in the C++ language and can be used either as a stand-alone tool or a library to be plugged in other N-body codes. The high precision of the floating point to 62 digits is also supported.

[submitted] Determination of Length of (Earth) Day [LOD] in the past geologic epochs

The protocol describes the algorithm of arriving at LOD in a given past geological Epoch. First the lunar orbital radius of the given geologic epoch has to be determined. For this the velocity of recession of Moon for the accelerated phase has to be determined. The spatial integral of the reciprocal of Velocity of recession gives the the transit time of Moon from desired orbit to the present orbit.Through several iterations the transit time is made to converge on the geologic epoch. Once we determine the desired orbital radius it has to be substituted in the LOD expression to determine the LOD in the given geologic epoch.

[submitted] MERA: Analysis Tool for Astrophysical Simulation Data in the Julia Language

MERA works with large 3D AMR/uniform-grid and N-body particle data sets from astrophysical simulations such as those produced by the hydrodynamic code RAMSES (ascl:1011.007) and is written entirely in the Julia language. The package provides essential functions for efficient and memory lightweight data loading and analysis. The core of MERA is a database framework.

[submitted] pycf3 - Cosmicflows-3 Distance-Velocity Calculator client for Python

The project is a simple Python client for Cosmicflows-3 Distance-Velocity Calculator at distances less than 400 Mpc (http://edd.ifa.hawaii.edu/CF3calculator/)

Compute expectation distances or velocities based on smoothed velocity field from the Wiener filter model of https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.5438G/abstract.

[submitted] StarburstPy: Python Wrapper for Starburst99

StarburstPy is a python wrapper for Starburst99 (ascl:1104.003). The code contains methods for setting all inputs, running Starburst99, and reading output data into python dictionaries.

[ascl:2001.015] gnm: The MCMC Jagger

gnm is an implementation of the affine-invariant sampler for Markov chain Monte Carlo (MCMC) that uses the Gauss-Newton-Metropolis (GNM) Algorithm. The GNM algorithm is specialized in sampling highly non-linear posterior probability distribution functions of the form exp(-||f(x)||^2/2). The code includes dynamic hyper-parameter optimization to increase performance of the sampling; other features include the Jacobian tester and an error bars creator.

[ascl:2001.014] Peasoup: C++/CUDA GPU pulsar searching library

The NVIDIA GPU-based pipeline code peasoup provides a one-step pulsar search, including searching for pulsars with up to moderate accelerations, with only one command. Its features include dedispersion, dereddening in the Fourier domain, resampling, peak detection, and optional time series folding. peasoup's output is the candidate list.

[ascl:2001.013] RPPPS: Re-analyzing Pipeline for Parkes Pulsar Survey

RPPPS (Re-analysing Pipeline for Parkes Pulsar Survey) uses Linux shell scripts, C language, and python code and two parallel strategies to reorganize the PRESTO (ascl:1107.017) pulsar search pipeline to run multiple processes in parallel, thus accelerating the search for pulsars. Though originally designed for reprocessing PMPS data, the code has also been successfully used with FAST (Five-hundred-meter Aperture Spherical radio Telescope) drift scan data. The pipeline is only CPU-based and can be easily and quickly deployed in computing nodes for testing purposes or data processes.

[ascl:2001.012] MCMCI: Markov Chain Monte Carlo + Isochrones method for characterizing exoplanetary systems

MCMCI (Markov chain Monte Carlo + isochrones) characterizes a whole exoplanetary system directly by modeling the star and its planets simultaneously. The code, written in Fortran, uses light curves and basic stellar parameters with a transit analysis algorithm that interacts with stellar evolutionary models, thus using both model-dependent and empirical age indicators to characterize the system.

[ascl:2001.011] ExoTETHyS: Exoplanetary transits and eclipsing binaries modeler

ExoTETHyS models exoplanetary transits, eclipsing binaries, and related phenomena. The package calculates stellar limb-darkening coefficients down to <10 parts per million (ppm) and generates an exact transit light-curve based on the entire stellar intensity profile rather than limb-darkening coefficients.

[ascl:2001.010] CosMOPED: Compressed Planck likelihood

CosMOPED (Cosmological MOPED) uses the MOPED (Multiple/Massively Optimised Parameter Estimation and Data compression) compression scheme to compress the Planck power spectrum. This convenient and lightweight compressed likelihood code is implemented in Python. To compute the likelihood for the LambdaCDM model using CosMOPED, one needs only six compression vectors, one for each parameter, and six numbers from compressing the Planck data using the six compression vectors. Using these, the likelihood of a theory power spectrum given the Planck data is the product of six one-dimensional Gaussians. Extended cosmological models require computing extra compression vectors.

[ascl:2001.009] ORCS: Analysis engine for SITELLE spectral cubes

ORCS (Outils de Réduction de Cubes Spectraux) is an analysis engine for SITELLE spectral cubes. The software extracts integrated spectra, fits the sinc emission lines, and recalibrates data in wavelength, astrometry and flux. ORCS offers a choice between a Bayesian or a classical fitting algorithm
, and also provides automatic source detection and radial velocity correction.

[ascl:2001.008] DebrisDiskFM: Debris Disk Forward Modeling

DebrisDiskFM provides forward modeling for circumstellar debris disks in scattered light using the MCFOST disk modeling software to generate disk model images using given input parameters and emcee (ascl:1303.002) to obtain the posterior distributions for these parameters.

[ascl:2001.007] BTS: Behind The Spectrum

Behind The Spectrum (BTS) is a fully-automated multiple-component fitter for optically-thin spectra. Written as a python module, the routine uses the first, second and third derivatives to determine thenumber of components in the spectrum. A least-squared fitting routine then determines the best fit with that number of components, checking for over-fitting and over-lapping velocity centroids.

[ascl:2001.006] Protostellar Evolution: Stellar evolution simulator

Protostellar Evolution simulates the evolution of stellar stellar radius and luminosity from the bound core stage through to the core hydrogen ignition as a zero-age main-sequence (ZAMS) star and beyond. Written in Fortran 90, the code is implemented as a module of the FLASH astrophysical fluid dynamics code (ascl:1010.082).

[ascl:2001.005] FAKEOBS: Model visibilities generator

The CASA (1107.013) task FAKEOBS generates model visibilities from already-existing measurement sets. This task can be used to substitute all the visibilities of the target with simulations computed from any model image. The measurement can either be with real or simulated data, the target can have been observed in mosaic mode, and there can be several sources (e.g., bandpass calibrator, flux/phase calibrator, and target).

[ascl:2001.004] FragMent: Fragmentation techniques for studying filaments

FragMent studies fragmentation in filaments by collating a number of different techniques, including nearest neighbour separations, minimum spanning tree, two-point correlation function, and Fourier power spectrum. It also performs model selection using a frequentist and Bayesian approach to find the best descriptor of a filament's fragmentation. While the code was designed to investigate filament fragmentation, the functions are general and may be used for any set of 2D points to study more general cases of fragmentation.

[ascl:2001.003] sf3dmodels: Star-forming regions 3D modelling package

sf3dmodels models star-forming regions; it brings together analytical models in order to compute their physical properties in a 3-dimensional grid. The package can couple different models in a single grid to recreate complex star forming systems such as those being revealed by current instruments. The output data can be read with LIME (ascl:1107.012) or RADMC-3D (ascl:1108.016) to carry out radiative transfer calculations of the modeled region.

[ascl:2001.002] TRANSPHERE: 1-D spherical continuum radiative transfer

TRANSPHERE is a simple dust continuum radiative transfer code for spherically symmetric circumstellar envelopes. It handles absorption and re-emission and computes the dust temperature self-consistently; it does not, however, deal with scattering. TRANSPHERE uses a variable eddington factor method for the radiative transfer. The RADMD code (ascl:1108.016) is more versatile, but for a spherically symmetric problem for which scattering is of much concern, it may be easier to use a simple code such as TRANSPHERE.

Please note that this code has not been updated since 2006.

[ascl:2001.001] Min-CaLM: Mineral compositional analysis on debris disk spectra

Min-CaLM performs automated mineral compositional analysis on debris disk spectra. The user inputs the debris disk spectrum, and using Min-CaLM's built-in mineralogical library, Min-CaLM calculates the relative mineral abundances within the disk. To do this calculation, Min-CaLM converts the debris disk spectrum and the mineralogical library spectra into a system of linear equations, which it then solves using non-negative least square minimization. This code comes with a GitHub tutorial on how to use the Min-CaLM package.

[submitted] amber_meta

amber_meta integrates a few routines to launch AMBER (ascl:2209.007) in a systematic manner. To avoid typing a string in the command line manually with all parameters required to launch AMBER, amber_meta generates the command from configuration files, and can directly launch AMBER instances.

[submitted] Time-domain astronomy sandbox

Time-domain astronomy sandbox consists in a series of classes to simulate and process time-domain astronomy data products in Python. The code was originally developed to model Fast Radio Burst (FRB) and Radio Frequency Interference (RFI), and evaluate different RFI mitigation methods and their effect on FRB search.

[submitted] SDSS Dual Active Nuclei Galaxy Detection Pipeline

Dual Active Nuclei Galaxies (DAGNs) are rare occurrences in the sky. Until now, most AGNs have been described to be found serendipitously, or by manual observation. In recent years, there has been an increasing interest in such dual AGNs and their astrophysical properties. Their study is important to the understanding of galaxy formation, star formation and these objects are the precursors to Gravitational Wave Sources.

Hence, we have devised a pipeline, that along with systematic data collection, can detect such dual AGN candidates. A novel algorithm 'Graph-Boosted Gradient Ascent' has been devised to detect whether an R-band image of a galaxy is a potential candidate for a DAGN or not. The pipeline can be cloned to a user's machine, and by joining the AstrIRG_DAGN group on SciServer, astronomers can collectively contribute to the mining of DAGNs.

[submitted] K2CE: Kepler-K2 Cadence Events

Since early 2018, the Kepler/K2 project has been performing a uniform global reprocessing of data from K2 Campaigns 0 through 14. Subsequent K2 campaigns (C15-C19) are being processed using the same processing pipeline. One of the major benefits of the reprocessing effort is that, for the first time, short-cadence (1-min) light curves are produced in addition to the standard long-cadence (30-min) light curves. Users have been cautioned that the Kepler pipeline detrending module (PDC), developed for use on original Kepler data, has not been tailored for use on short-cadence K2 observations. Systematics due to events on fast timescales, such as thruster firings, are sometimes poorly corrected for many short-cadence targets. A Python data visualization and manipulation tool, called Kepler-K2 Cadence Events, has been developed that identifies and removes cadences associated with problematic thruster events, thus producing better light curves. Kepler-K2 Cadence Events can be used to visualize and manipulate light curve files and target pixel files from the Kepler, K2, and TESS missions. This software is available at the following NASA GitHub repository https://github.com/nasa/K2CE .

[ascl:1912.020] MRExo: Non-parametric mass-radius relationship for exoplanets

MRExo performs non-parametric fitting and analysis of the mass-radius (M-R) relationship for exoplanets. Written in Python, it offers tools for fitting the M-R relationship to a given data set and also includes predicting (M->R, and R->M) and plotting functions.

[ascl:1912.019] STACKER: Stack sources in interferometric data

STACKER stacks sources in interferometric data, i.e., averaging emission from different sources. The library allows stacking to be done directly on visibility data as well as in the image domain. The code is in format of a CASA (ascl:1107.013) task and implements uv- and image-stacking algorithms; it also provides several useful tasks for stacking related data processing. It allows introduction and stacking of random sources to estimate bias and noise, and also allows removal of a model of bright sources from the data.

[ascl:1912.018] Tangos: Framework and web interface for database-driven analysis of numerical structure formation simulations

Tangos builds databases (along the lines of Eagle or MultiDark) for cosmological and zoom simulations. Its modular system generates and queries databases. It is designed to store and manage results from a user's own analysis code, provides web and python interfaces, and allows users to construct science-focused queries, including across entire merger trees, without requiring knowledge of SQL. Tangos manages the process of populating the database with science data, including auto-parallelizing the analysis. It can be customized to work with multiple python modules such as pynbody (ascl:1305.002) or yt (ascl:1011.022) to process raw simulation data; it defaults to using SQLite, but allows use of other databases as the underlying store through the use of SQLAlchemy.

[ascl:1912.017] PTMCMCSampler: Parallel tempering MCMC sampler package written in Python

PTMCMCSampler performs MCMC sampling using advanced techniques. The code implements a variety of proposal schemes, including adaptive Metropolis, differential evolution, and parallel tempering, which can be used together in the same run.

[ascl:1912.016] GWpy: Python package for studying data from gravitational-wave detectors

The Python package GWpy analyzes and characterizes gravitational wave data. It provides a user-friendly, intuitive interface to the common time-domain and frequency-domain data produced by the LIGO and Virgo observatories and their analyses. The core Python infrastructure is influenced by, and extends the functionality of, the Astropy (ascl:1304.002) package, and its methodology has been derived from, and augmented by, the LIGO Algorithm Library Suite (LALSuite), a large collection of primarily C99 routines for analysis and manipulation of data from gravitational-wave detectors. These packages use the SWIG program to produce Python wrappings for all C modules, allowing the GWpy package to leverage both the completeness, and the speed, of these libraries.

[ascl:1912.015] ENTERPRISE: Enhanced Numerical Toolbox Enabling a Robust PulsaR Inference SuitE

ENTERPRISE (Enhanced Numerical Toolbox Enabling a Robust PulsaR Inference SuitE) is a pulsar-timing analysis code which performs noise analysis, gravitational-wave searches, and timing model analysis. It uses Tempo2 (ascl:1210.015) to find the maximum-likelihood fit for the timing parameters and the basis of the fit for the red noise parameters if they are significant.

[ascl:1912.014] HARMPI: 3D massively parallel general relativictic MHD code

HARMPI is a parallel, 3D version of HARM (ascl:1209.005), which solves hyperbolic partial differential equations in conservative form using high-resolution shock-capturing techniques. The code is parallelized using MPI and is fully operational in 3D. HARMPI, like HARM, is capable of using non-uniform grids and solves the relativistic magnetohydrodynamic equations of motion on a stationary black hole spacetime in Kerr-Schild coordinates to evolve an accretion disk model.

[ascl:1912.013] GriSPy: Fixed-radius nearest neighbors grid search in Python

GriSPy (Grid Search in Python) uses a regular grid search algorithm for quick fixed-radius nearest-neighbor lookup. It indexes a set of k-dimensional points in a regular grid providing a fast approach for nearest neighbors queries. Optional periodic boundary conditions can be provided for each axis individually. GriSPy implements three types of queries: bubble, shell and the nth-nearest, and offers three different metrics of interest in astronomy: the Euclidean and two distance functions in spherical coordinates of varying precision, haversine and Vincenty. It also provides a custom distance function. GriSPy is particularly useful for large datasets where a brute-force search is not practical.

[ascl:1912.012] GAME: GAlaxy Machine learning for Emission lines

GAME infers different ISM physical properties by analyzing the emission line intensities in a galaxy spectrum. The code is trained with a large library of synthetic spectra spanning many different ISM phases, including HII (ionized) regions, PDRs, and neutral regions. GAME is based on a Supervised Machine Learning algorithm called AdaBoost with Decision Trees as base learner. Given a set of input lines in a spectrum, the code performs a training on the library and then evaluates the line intensities to give a determination of the physical properties. The errors on the input emission line intensities and the uncertainties on the physical properties determinations are also taken into account. GAME infers gas density, column density, far-ultraviolet (FUV, 6–13.6 eV) flux, ionization parameter, metallicity, escape fraction, and visual extinction. A web interface for using the code is available.

[ascl:1912.011] QSOSIM: Simulated Quasar Spectrum Generator

QSOSIM realistically simulates high-resolution quasar spectra using a set of basic parameters (magnitude, redshift, and spectral index). The simulated spectra include physical effects seen in the real data: the power-law quasar continuum, the narrow and broad emission lines, absorption by neutral hydrogen (HI) in the Lyman alpha forest, and heavy element transitions along the line of sight. The code uses empirical HI column density, redshift, and b-parameter distributions to simulate absorption in the Lyman alpha forest. All absorbers with column densities larger than log [N(HI)/cm2]>17 have heavy element absorption, for which the column densities are calculated using the plasma simulation code CLOUDY (ascl:9910.001) and the radiative transfer code CUBA. The code also simulates the clustering of the intergalactic medium along the line of sight, the proximity effect of the quasar, and the effect of the cosmic ultraviolet background. Each simulated spectrum is saved in a single FITS file in as a noiseless R=100000 spectrum, as well as a spectrum convolved with Sloan Digital Sky Survey resolution (R=10000) and realistic noise.

[ascl:1912.010] AstroAccelerate: Accelerated software package for processing time-domain radio astronomy data

AstroAccelerate processes time-domain radio astronomy data. It offers a standalone code that can be used to process filterbank data and a library that performs GPU-accelerated single pulse processing (SPS), Fourier Domain Acceleration Searching (FDAS) and dedispersion in real-time on very large data-sets comparable to those that will be produced by next-generation radio telescopes such as the SKA. AstroAccelerate uses NVIDIAR GPUs, and is configurable, stable, and easily maintained.

[ascl:1912.009] FORSTAND: Flexible ORbit Superposition Toolbox for ANalyzing Dynamical models

FORSTAND constructs dynamical models of galaxies using the Schwarzschild orbit-superposition method; the method is available as part of the AGAMA (ascl:1805.008) framework. The models created are constrained by line-of-sight kinematic observations and are applicable to galaxies of all morphological types, including disks and triaxial rotating bars.

[submitted] Exo-MerCat: a merged exoplanet catalog with Virtual Observatory connection

The heterogeneity of papers dealing with the discovery and characterization of exoplanets makes every attempt to maintain a uniform exoplanet catalog almost impossible. Four sources currently available online (NASA Exoplanet Archive, Exoplanet Orbit Database, Exoplanet Encyclopaedia, and Open Exoplanet Catalogue) are commonly used by the community, but they can hardly be compared, due to discrepancies in notations and selection criteria.
Exo-MerCat is a Python code that collects and selects the most precise measurement for all interesting planetary and orbital parameters contained in the four databases, accounting for the presence of multiple aliases for the same target. It can download information about the host star as well by the use of Virtual Observatory ConeSearch connections to the major archives such as SIMBAD and those available in VizieR. A Graphical User Interface is provided to filter data based on the user's constraints and generate automatic plots that are commonly used in the exoplanetary community.
With Exo-MerCat, we retrieved a unique catalog that merges information from the four main databases, standardizing the output and handling notation differences issues. Exo-MerCat can correct as many issues that prevent a direct correspondence between multiple items in the four databases as possible, with the available data. The catalog is available as a VO resource for everyone to use and it is periodically updated, according to the update rates of the source catalogs.

[submitted] PyFOSC: a pipeline toolbox for BFOSC/YFOSC long-slit spectroscopy data reduction

PyFOSC is a pipeline toolbox for long-slit spectroscopy data reduction written in Python. It can be used for FOSC (Faint Object Spectrograph and Camera) data from Xinglong/Lijiang 2-meter telescopes in China. This pipeline privodes a neat way for data pre-processing, including updating missing header fileds for BFOSC data, reducing fits file extension for YFOSC data, etc. And it makes the data reduction procedure efficient by using previously identified lamp spectra as re-identification references during wavelength calibration, and applying multiprocessing in some modules. PyFOSC also enables customization for any other long-slit spectroscopy data.

[ascl:1912.008] PopSyCLE: Population Synthesis for Compact object Lensing Events

PopSyCLE performs compact object population synthesis while taking photometric and astrometric microlensing effects into consideration. It uses Galaxia (ascl:1101.007) to produces a synthetic survey, injects compact objects into the resulting survey, and then produces a list of microlensing events, enabling the discovery of black holes with microlensing. It can be used to examine historical microlensing events from photometric surveys to statistically constrain the abundance of black holes in our galaxy, and to forward model microlensing survey results to constrain, for example, the properties of compact objects, Galactic structure, and the initial-final mass relation.

[ascl:1912.007] anesthetic: Nested sampling visualization

anesthetic brings together tools for processing nested sampling chains, leveraging standard scientific python libraries. The code provides computation of Bayesian evidences, Kullback-Liebler divergences and Bayesian model dimensionalities, marginalized 1d and 2d plots, and dynamic replaying of nested sampling. anesthetic was designed primarily for use with nested sampling outputs, although it can be used for normal MCMC chains.

[ascl:1912.006] HSIM: HARMONI simulation pipeline

HSIM simulates observations with HARMONI on the Extremely Large Telescope. HSIM takes high spectral and spatial resolution input data cubes, encoding physical descriptions of astrophysical sources, and generates mock observed data cubes. The simulations incorporate detailed models of the sky, telescope, instrument, and detectors to produce realistic mock data. HSIM performs in-depth simulations for several key science cases as part of the design and development of the HARMONI integral field spectrograph, including the ELT AO performance, atmospheric effects and realistic detector statistics.

[ascl:1912.005] Athena++: Radiation GR magnetohydrodynamics code

Athena++ is a complete re-write of the Athena astrophysical magnetohydrodynamics (MHD) code (ascl:1010.014) in C++. Compared to earlier versions, the Athena++ code has much more flexible coordinate and grid options and supports new physics. It also offers significantly improved performance and scalability, and improved source code clarity and modularity. Athena++ supports compressible hydrodynamics and MHD in 1D, 2D, and 3D, and special and general relativistic hydrodynamics and MHD. In addition, it supports Cartesian, cylindrical, or spherical polar coordinates; static or adaptive mesh refinement in any coordinate system; mixed parallelization with both OpenMP and MPI; and a task-based execution model for improved load balancing, scalability and modularity.

[ascl:1912.004] DALiuGE: Data Activated Liu Graph Engine

DALiuGE provides a distributed data management platform and a scalable pipeline execution environment to support continuous, soft real-time, data-intensive processing for producing radio astronomy data products; it originated from a prototyping activity as part of the SKA SDP Consortium called Data Flow Management System (DFMS). Though the development of DALiuGE is largely based on radio astronomy processing requirements, it has adopted a generic, data-driven framework architecture potentially applicable to many other data-intensive applications.

[ascl:1912.003] ASKAPsoft: ASKAP science data processor software

ASKAPsoft provides data processing functionality for Australian Square Kilometre Array Pathfinder, including calibration, spectral line imaging, continuum imaging, source detection and generation of source catalogs, and transient detection. The MPI-based package is the primary software for storing and processing raw data, and initiating the archiving of resulting science data products into the data archive (CASDA). The processing pipelines within ASKAPsoft are largely written in C++ built on top of casacore (ascl:1912.002) and other third party libraries.

[ascl:1912.002] casacore: Suite of C++ libraries for radio astronomy data processing

The casacore package contains the core libraries of the old AIPS++/CASA (ascl:1107.013) package. This split was made to get a better separation of core libraries and applications. CASA is now built on top of Casacore. The system consists of a set of layered libraries (packages) and includes a library (using Boost-Python) that converts the basic Casacore types (e.g., Array, Record) to and from Python. Casacore includes the casa package for core functionality and data types like Array and Record; a scimath package for N-dim functions with auto-differentiation and linear or non-linear fitting; and a tables package for the table data system supporting N-dim arrays with advanced querying. It also includes the measures package to manage values in astronomical reference frames using physical units (Quanta) and the MeasurementSets for storing data in the UV-domain, and also the images package for N-dim images in world coordinates with various analysis operations.

[ascl:1912.001] Polyspectrum: Computing polyspectra using an FFT estimator

Polyspectrum computes the polyspectrum from 3D grids using a fast Fourier transformation (FFT) estimator. The code, written in C and MPI-parallelized, support the computation of power- and bispectra; it also supports higher-order polyspectra, but streamlining the input data is required.

[ascl:1911.024] comb: Spectral line data reduction and analysis package

comb is a single-dish radio astronomy spectral line data reduction and analysis package developed at AT&T Bell labs and was used for data reduction for many single-dish telescopes, including Bell Labs 7-m, NRAO 12-m, DSN network, FCRAO 14-m, Arecibo, AST/RO, SEST, BIMA, and in 2011-2012, the Stratospheric Terahertz Observatory. A cookbook for the code is available.

[ascl:1911.023] miluphcuda: Smooth particle hydrodynamics code

miluphcuda is the CUDA port of the original miluph code; it runs on single Nvidia GPUs with compute capability 5.0 and higher and provides fast and efficient computation. The code can be used for hydrodynamical simulations and collision and impact physics, and features self-gravity via Barnes-Hut trees and porosity models such as P-alpha and epsilon-alpha. It can model solid bodies, including ductile and brittle materials, as well as non-viscous fluids, granular media, and porous continua.

[ascl:1911.022] FFTLog-and-beyond: Generalized FFTLog algorithm

FFTLog-and-beyond takes the FFTLog algorithm for single-Bessel integrals and generalizes it for integrals containing a derivative of the Bessel function to solve the non-Limber integrals. The full non-Limber angular power spectrum integral is simplified by noting the small contribution from unequal-time nonlinear terms; this significantly reduces the computation and avoids the double-Bessel integral. The original FFTLog algorithm is also extended to compute integrals containing derivatives of Bessel functions, which can be used to efficiently compute angular power spectra including redshift-space distortions (RSD) and Doppler effects. C and Python versions of the code are available.

[ascl:1911.021] TreeFrog: Construct halo merger trees and compare halo catalogs

TreeFrog reads in particle IDs information between various structure catalogs and cross matches catalogs, assuming that particle IDs are unique and constant across snapshots. Though it is built as a cross correlator (in that it can match particles across several different catalogs), its principle use is as halo merger tree builder. TreeFrog produces links between objects found at different snapshots (or catalogs) and uses several possible functions to evaluate the merit of a link between one object at a given snapshot (or in a given catalog) to another object in a previous snapshot (or different catalog). It can also produce a full graph. The code utilizes MPI and OpenMP. It is optimzed for reading VELOCIraptor (ascl:1911.020) output but can also read output from other structure finders such as AHF (ascl:1102.009).

[ascl:1911.020] VELOCIraptor-STF: Six-dimensional Friends-of-Friends phase space halo finder

VELOCIraptor-STF, formerly STructure Finder (ascl:1306.009), is a 6-Dimensional Friends-of-Friends (6D-FoF) phase space halo finder and constructs halo catalogs. The code uses using MPI and OpenMP APIs and can be compiled as a library for on-the-fly halo finding within an N-body/hydrodynamnical code. There is an associated halo merger tree code TreeFrog (ascl:1911.021).

[ascl:1911.019] OrbWeaver: Galaxy/(sub)halo orbital processing tool

OrbWeaver extracts orbits from halo catalogs, enabling large statistical studies of their orbital parameters. The code is run in two stages. For the first run, a configuration file is used to modify orbit host selection and the region around orbit host used for the superset of orbiting halos. Each orbit host has a orbit forest (containing halos that passed within the region of interest); the code generates a pre-processed catalog which contains a superset of orbiting halo for each identified orbit host. The second run uses the file list generated in the first stage for the creation of the orbit catalog, which is the final output.

[ascl:1911.018] WhereWolf: Galaxy/(sub)Halo ghosting tool for N-body simulations

WhereWolf tracks (sub)haloes even if they have been lost by a halo finder in cosmological simulations and supplements halo catalogs such as VELOCIraptor (ascl:1911.020) with these recovered (sub)haloes. The code can improve measurements of the subhalo/halo mass function and present estimates of the distribution of radii at which subhaloes merge.

[ascl:1911.017] HLattice: Scalar fields and gravity simulator for the early universe

HLattice simulates scalar fields and gravity in the early universe. The code allows the user to select between symplectic integrators, descretization schemes, and metrics such as Minkowski or FRW backgrounds and adaptice schemes in an "all-in-one" configuration file.

[ascl:1911.016] CLUSTEREASY: Lattice simulator for evolving interacting scalar fields in an expanding universe on parallel computing clusters

CLUSTEREASY is a parallel programming extension of the simulation program LATTICEEASY (ascl:1911.015); running the program in parallel greatly extends the range of scales and times that can be simulated. The program is particularly useful for the study of reheating and thermalization after inflation.

[ascl:1911.015] LATTICEEASY: Lattice simulator for evolving interacting scalar fields in an expanding universe

LATTICEEASY creates lattice simulations of the evolution of interacting scalar fields in an expanding universe. The program can do runs with different parameters and new models can be easily introduced for evaluation. Simulations can be done in one, two, or three dimensions by resetting a single variable. Mathematica notebooks for plotting the output and a range of models are also available for download; a parallel processing version of LATTICEEASY called CLUSTEREASY (ascl:1911.016) is also available.

[ascl:1911.014] MORDI: Massively-Overlapped Ring-Diagram Inversion

MORDI (Massively-Overlapped Ring-Diagram Inversion) performs three-dimensional ring-diagram inversions. The code reads in frequency shift measurements and their associated sensitivity kernels and outputs two-dimensional slices of the subsurface flow field at a constant depth and (optionally) the associated averaging kernels. It relies on both distributed-memory (MPI) and shared-memory (OpenMP) parallelism to scale efficiently up to a few thousand processors, but can also run reasonably well on small machines (1-4 cpus). The actions of the code are modified by command-line parameters, which enable a significant amount of flexibility when setting up an inversion.

[ascl:1911.013] ATLAS: Turning Dopplergram images into frequency shift measurements

ATLAS performs the tracking, projecting, power-spectrum-making, and ring-fitting needed to turn a set of Dopplergram images into a set of frequency shift measurements. This code is essentially a combination of three codes, FRACK (FORTRAN Tracking), PSPEC (Power SPECtrum), and MRF (Multi-Ridge Fitting), included in the ATLAS package. ATLAS reads in a list of longitude/latitude coordinates corresponding to the desired tile centers and a set of full-disk Dopplergram images and outputs frequency shift measurements from each wave mode of each tile. The code relies on both distributed-memory (MPI) and shared-memory (OpenMP) parallelism to scale up to around 1000 processes. Due to the immense volume of data produced by the tracking and projecting steps, the intermediate data products (tiles, power spectra) are never written out.

[ascl:1911.012] Zeltron: Explicit 3D relativistic electromagnetic Particle-In-Cell code

Zeltron is an explicit 3D relativistic electromagnetic Particle-In-Cell code suited for modeling particle acceleration in astrophysical plasmas. The code is efficiently parallelized with the Message Passing Interface, and can be run on a laptop computer or on multiple cores on current supercomputers. Zeltron takes into account the effect of the radiation reaction force on the motion of the particles; it assigns variable weights to the macro-particles to model particle density gradients, and does not strictly conserve the total energy. The code uses linear interpolation to deposit the charges and currents generated by each particle at the nodes of the computational grid, and computes the charge and current densities for Maxwell's equations. Zeltron contains a large set of analysis tools, including plasma density, particle spectrum, optically thin synchrotron and inverse Compton spectra, angular distributions, and stress-energy tensor.

[ascl:1911.011] IDG: Image Domain Gridding

IDG (Image Domain Gridding) is an imager that makes w-term corrections and a-term corrections computationally very cheap. It works with WSClean (ascl:1408.023) and supports the same cleaning and data selections options that WSClean offers in normal mode (such as cotton-schwab, multi-frequency multi-scale cleaning, and auto-masking). IDG also allows gridding with a time-variable beam including the LOFAR, AARTFAAC and MWA beam and can perform full beam or differential correction. The code requires measurement sets with four polarizations (e.g. XX/XY/YX/YY), can apply a spatially varying time-variable TEC term that can additionally be different for different antennas and output channels, and performs extremely well on GPUs.

[ascl:1911.010] Fruitbat: Fast radio burst redshift estimation

Fruitbat estimates the redshift of Fast Radio Bursts (FRB) from their dispersion measure. The code combines various dispersion measure (DM) and redshift relations with the YMW16 galactic dispersion measure model into a single easy to use API.

[ascl:1911.009] frbpoppy: Fast radio burst population synthesis in Python

frbpoppy conducts fast radio burst population synthesis and continues the work of PSRPOP (ascl:1107.019) and PsrPopPy (ascl:1501.006) in the realm of FRBs. The code replicates observed FRB detection rates and FRB distributions in three steps. It first simulates a cosmic population of one-off FRBs and allows the user to select options such as models for source number density, cosmology, DM host/IGM/Milky Way, luminosity functions, and emission bands as well as maximum redshift and size of the FRB population. The code then generates a survey by adopting a beam pattern using various survey parameters, among them telescope gain, sampling time, receiver temperature, central frequency, channel bandwidth, number of polarizations, and survey region limits. Finally, frbpoppy convolves the generated intrinsic population with the generated survey to simulate an observed FRB population.

[ascl:1911.008] HeatingRate: Radioactive heating rate and macronova (kilonova) light curve

HeatingRate calculates the nuclear heating rates [erg/s/g] of beta-decay, alpha-decay, and spontaneous fission of r-process nuclei, taking into account for thermalization of gamma-rays and charged decay products in r-process ejecta. It uses the half-lives and injection energy spectra from an evaluated nuclear data library (ENDF/B-VII.1). Each heating rate is computed for given abundances, ejecta mass, velocity, and density profile. HeatingRate also computes the bolometric light curve and the evolution of the effective temperature for given abundances, ejecta mass, velocity, and density profile assuming opacities independent of the wavelength.

[ascl:1911.007] planetplanet: General photodynamical code for exoplanet light curves

planetplanet models exoplanet transits, secondary eclipses, phase curves, and exomoons, as well as eclipsing binaries, circumbinary planets, and more. The code was originally developed to model planet-planet occultation (PPO) light curves for the TRAPPIST-1 system, but it is generally applicable to any exoplanet system. During a PPO, a planet occults (transits) the disk of another planet in the same planetary system, blocking its thermal (and reflected) light, which can be measured photometrically by a distant observer. planetplanet is coded in C and wrapped in a user-friendly Python interface.

[ascl:1911.006] ATHOS: A Tool for HOmogenizing Stellar parameters

ATHOS provides on-the-fly stellar parameter determination of FGK stars based on flux ratios from optical spectra. Once configured properly, it will measure flux ratios in the input spectra and deduce the stellar parameters effective temperature, iron abundance (a.k.a [Fe/H]), and surface gravity by employing pre-defined analytical relations. ATHOS can be configured to run in parallel in an arbitrary number of threads, thus enabling the fast and efficient analysis of huge datasets.

[ascl:1911.005] MARTINI: Mock spatially resolved spectral line observations of simulated galaxies

MARTINI (Mock APERTIF-like Radio Telescope Interferometry of the Neutal ISM) creates synthetic resolved HI line observations (data cubes) of smoothed-particle hydrodynamics simulations of galaxies. The various aspects of the mock-observing process are divided logically into sub-modules handling the data cube, source, beam, noise, spectral model and SPH kernel. MARTINI is object-oriented: each sub-module provides a class (or classes) which can be configured as desired. For most sub-modules, base classes are provided to allow for straightforward customization. Instances of each sub-module class are then given as parameters to the Martini class. A mock observation is then constructed by calling a handful of functions to execute the desired steps in the mock-observing process.

[ascl:1911.004] PypeIt: Python spectroscopic data reduction pipeline

PypeIt reduces data from echelle and low-resolution spectrometers; the code can be run in several modes of reduction that demark the level of sophistication (e.g. quick and dirty vs. MonteCarlo) and also the amount of output written to disk. It also generates numerous data products, including 1D and 2D spectra; calibration images, fits, and meta files; and quality assurance figures.

[ascl:1911.003] OpenSPH: Astrophysical SPH and N-body simulations and interactive visualization tools

OpenSPH runs hydrodynamical and N-body simulations and was written for asteroid collisions and subsequent gravitational evolution. The code offers SPH and N-body solvers with several different equations of state and material rheologies. It is written in C++14 with a modular object-oriented design, focused on extensibility and maintainability, and it can be used either as a library or as a standalone graphical program that allows to set up the problem in a convenient graphical node editor. The graphical program further allows real-time visualization of the simulation, diagnostics and tools for analysis of the results.

[ascl:1911.002] uvplot: Interferometric visibilities plotter

uvplot makes nice plots of deprojected interferometric visibilities (often called uvplots). It implements plotting functionality, handles MS tables with spectral windows with different number of channels, and can import visibilities from ASCII to MS Table. It also allows export of specific channels. uvplot can be installed inside the NRAO CASA package (ascl:1107.013).

[ascl:1911.001] PLAN: A Clump-finder for Planetesimal Formation Simulations

PLAN (PLanetesimal ANalyzer) identifies and characterizes planetesimals produced in numerical simulations of the Streaming Instability that includes particle self-gravity with code Athena (ascl:1010.014). PLAN works with the 3D particle output of Athena and finds gravitationally bound clumps robustly and efficiently. PLAN — written in C++ with OpenMP/MPI — is massively parallelized, memory-efficient, and scalable to analyze billions of particles and multiple snapshots simultaneously. The approach of PLAN is based on the dark matter halo finder HOP (ascl:1102.019), but with many customizations for planetesimal formation. PLAN can be easily adapted to analyze other object formation simulations that use Lagrangian particles (e.g., Athena++ simulations). PLAN is also equipped with a toolkit to analyze the grid-based hydro data (VTK dumps of primitive variables) from Athena, which requires the Boost MultiDimensional Array Library.

[submitted] Network Flux Transport Demonstration

We have developed a method to efficiently simulate the dynamics of the magnetic flux in the solar network. We call this method Network Flux Transport (NFT). Implemented using a Spherical Centroidal Voronoi Tessellation (SCVT) based network model, magnetic flux is advected by photospheric plasma velocity fields according to the geometry of the SCVT model. We test NFT by simulating the magnetism of the Solar poles. The poles of the sun above 55 deg latitude are free from flux emergence from active regions or ephemeral regions. As such, they are ideal targets for a simplified simulation that relies on the strengths of the NFT model. This simulation method reproduces the magnetic and spatial distributions for the solar poles over two full solar cycles.

[ascl:1910.022] qnm: Kerr quasinormal modes, separation constants, and spherical-spheroidal mixing coefficients calculator

qnm computes the Kerr quasinormal mode frequencies, angular separation constants, and spherical-spheroidal mixing coefficients. The qnm package includes a Leaver solver with the Cook-Zalutskiy spectral approach to the angular sector, and a caching mechanism to avoid repeating calculations. A large cache of low ℓ, m, n modes is available for download and can be installed with a single function call and interpolated to provide good initial guess for root-polishing at new values of spin.

[ascl:1910.021] AOtools: Adaptive optics modeling and analysis toolkit

The AOtools package offers generic adaptive optics processing tools in addition to astronomy-specific methods; among these are analyzing data in the pupil plane, images and point spread functions in the focal plane, wavefront sensors, modeling of atmospheric turbulence, physical optical propagation of wavefronts, and conversion functions to convert stellar brightness into photon flux for a given waveband. The software also calculates integrated atmospheric parameters, such as coherence time and isoplanatic angle from atmospheric turbulence and wind speed profile.

[ascl:1910.020] OCD: O'Connell Effect Detector using push-pull learning

OCD (O'Connell Effect Detector) detects eclipsing binaries that demonstrate the O'Connell Effect. This time-domain signature extraction methodology uses a supporting supervised pattern detection algorithm. The methodology maps stellar variable observations (time-domain data) to a new representation known as Distribution Fields (DF), the properties of which enable efficient handling of issues such as irregular sampling and multiple values per time instance. Using this representation, the code applies a metric learning technique directly on the DF space capable of specifically identifying the stars of interest; the metric is tuned on a set of labeled eclipsing binary data from the Kepler survey, targeting particular systems exhibiting the O’Connell Effect. This code is useful for large-scale data volumes such as that expected from next generation telescopes such as LSST.

[ascl:1910.019] Cobaya: Bayesian analysis in cosmology

Cobaya (Code for BAYesian Analysis) provides a framework for sampling and statistical modeling and enables exploration of an arbitrary prior or posterior using a range of Monte Carlo samplers, including the advanced MCMC sampler from CosmoMC (ascl:1106.025) and the advanced nested sampler PolyChord (ascl:1502.011). The results of the sampling can be analyzed with GetDist (ascl:1910.018). It supports MPI parallelization and is highly extensible, allowing the user to define priors and likelihoods and create new parameters as functions of other parameters.

It includes interfaces to the cosmological theory codes CAMB (ascl:1102.026) and CLASS (ascl:1106.020) and likelihoods of cosmological experiments, such as Planck, Bicep-Keck, and SDSS. Automatic installers are included for those external modules; Cobaya can also be used as a wrapper for cosmological models and likelihoods, and integrated it in other samplers and pipelines. The interfaces to most cosmological likelihoods are agnostic as to which theory code is used to compute the observables, which facilitates comparison between those codes. Those interfaces are also parameter-agnostic, allowing use of modified versions of theory codes and likelihoods without additional editing of Cobaya’s source.

[ascl:1910.018] GetDist: Monte Carlo sample analyzer

GetDist analyzes Monte Carlo samples, including correlated samples from Markov Chain Monte Carlo (MCMC). It offers a point and click GUI for selecting chain files, viewing plots, marginalized constraints, and LaTeX tables, and includes a plotting library for making custom publication-ready 1D, 2D, 3D-scatter, triangle and other plots. Its convergence diagnostics include correlation length and diagonalized Gelman-Rubin statistics, and the optimized kernel density estimation provides an automated optimal bandwidth choice for 1D and 2D densities with boundary and bias correction. It is available as a standalong package and with CosmoMC (ascl:1106.025).

[ascl:1910.017] ChainConsumer: Corner plots, LaTeX tables and plotting walks

ChainConsumer consumes the chains output from Monte Carlo processes such as MCMC to produce plots of the posterior surface inferred from the chain distributions, to plot the chains as walks to check for mixing and convergence, and to output parameter summaries in the form of LaTeX tables. It handles multiple models (chains), allowing for model comparison using AIC, BIC or DIC metrics.

[ascl:1910.016] MiSTree: Construct and analyze Minimum Spanning Tree graphs

MiSTree quickly constructs minimum spanning tree graphs for various coordinate systems, including Celestial coordinates, by using a k-nearest neighbor graph (k NN, rather than a matrix of pairwise distances) which is then fed to Kruskal's algorithm to create the graph. MiSTree bins the MST statistics into histograms and plots the distributions; enabling the inclusion of high-order statistics information from the cosmic web to provide additional information that improves cosmological parameter constraints. Though MiSTree was designed for use in cosmology, it can be used in any field requiring extracting non-Gaussian information from point distributions.

[ascl:1910.015] MarsLux: Illumination Mars maps generator

MarsLux generates illumination maps of Mars from Digital Terrain Model (DTM), permitting users to investigate in detail the illumination conditions on Mars based on its topography and the relative position of the Sun. MarsLux consists of two Python codes, SolaPar and MarsLux. SolaPar calculates the matrix with solar parameters for one date or a range between the two. The Marslux code generates the illumination maps using the same DTM and the files generated by SolaPar. The resulting illumination maps show areas that are fully illuminated, areas in total shadow, and areas with partial shade, and can be used for geomorphological studies to examine gullies, thermal weathering, or mass wasting processes as well as for producing energy budget maps for future exploration missions.

[ascl:1910.014] ANNz2: Estimating photometric redshift and probability density functions using machine learning methods

ANNz2, a newer implementation of ANNz (ascl:1209.009), utilizes multiple machine learning methods such as artificial neural networks, boosted decision/regression trees and k-nearest neighbors to measure photo-zs based on limited spectral data. The code dynamically optimizes the performance of the photo-z estimation and properly derives the associated uncertainties. In addition to single-value solutions, ANNz2 also generates full probability density functions (PDFs) in two different ways. In addition, estimators are incorporated to mitigate possible problems of spectroscopic training samples which are not representative or are incomplete. ANNz2 is also adapted to provide optimized solutions to general classification problems, such as star/galaxy separation.

[ascl:1910.013] E0102-VR: Virtual Reality application to visualize the optical ejecta in SNR 1E 0102.2-7219

E0102-VR facilitates the characterization of the 3D structure of the oxygen-rich optical ejecta in the young supernova remnant 1E 0102.2-7219 in the Small Magellanic Cloud. This room-scale Virtual Reality application written for the HTC Vive contributes to the exploration of the scientific potential of this technology for the field of observational astrophysics.

[ascl:1910.012] AOTOOLS: Reduce IR images from Adaptive Optics

AOTOOLS reduces IR images from adaptive optics. It uses effective dithering, either sky subtraction or dark-subtration, and flat-fielding techniques to determine the effect of the instrument on an image of an object. It also performs bad pixel masking, degrades an AO on-axis PSF due to effects of anisoplanicity, and corrects an AO on-axis PSF due to effects of seeing.

[ascl:1910.011] LEO-Py: Likelihood Estimation of Observational data with Python

LEO-Py uses a novel technique to compute the likelihood function for data sets with uncertain, missing, censored, and correlated values. It uses Gaussian copulas to decouple the correlation structure of variables and their marginal distributions to compute likelihood functions, thus mitigating inconsistent parameter estimates and accounting for non-normal distributions in variables of interest or their errors.

[ascl:1910.010] PEXO: Precise EXOplanetology

PEXO provides a global modeling framework for ns timing, μas astrometry, and μm/s radial velocities. It can account for binary motion and stellar reflex motions induced by planetary companions and also treat various relativistic effects both in the Solar System and in the target system (Roemer, Shapiro, and Einstein delays). PEXO is able to model timing to a precision of 1 ns, astrometry to a precision of 1 μas, and radial velocity to a precision of 1 μm/s.

[ascl:1910.009] orbitize: Orbit-fitting for directly imaged objects

orbitize fits the orbits of directly-imaged objects by packaging the Orbits for the Impatient (OFTI) algorithm and a parallel-tempered Markov Chain Monte Carlo (MCMC) algorithm into a consistent API. It accepts observations in three measurement formats, which can be mixed in the same input file, generates orbits, and plots the computed orbital parameters. orbitize offers numerous ways to visualize the data, including histograms, corner plots, and orbit plots. Generated orbits can be saved in HDF5 format for future use and analysis.

[ascl:1910.008] ECLIPS3D: Linear wave and circulation calculations

ECLIPS3D (Eigenvectors, Circulation, and Linear Instabilities for Planetary Science in 3 Dimensions) calculates a posteriori energy equations for the study of linear processes in planetary atmospheres with an arbitrary steady state, and provides both increased robustness and physical meaning to the obtained eigenmodes. It was developed originally for planetary atmospheres and includes python scripts for data analysis. ECLIPS3D can be used to study the initial spin up of superrotation of GCM simulations of hot Jupiters in addition to being applied to other problems.

[ascl:1910.007] TLS: Transit Least Squares

TLS is an optimized transit-fitting algorithm to search for periodic transits of small planets. In contrast to BLS: Box Least Squares (ascl:1607.008), which searches for rectangular signals in stellar light curves, TLS searches for transit-like features with stellar limb-darkening and including the effects of planetary ingress and egress. TLS also analyses the entire, unbinned data of the phase-folded light curve. TLS yields a ~10% higher detection efficiency (and similar false alarm rates) compared to BLS though has a higher computational load. This load is partly compensated for by applying an optimized period sampling and transit duration sampling constrained to the physically plausible range.

[ascl:1910.006] EMERGE: Empirical ModEl for the foRmation of GalaxiEs

Emerge (Empirical ModEl for the foRmation of GalaxiEs) populates dark matter halo merger trees with galaxies using simple empirical relations between galaxy and halo properties. For each model represented by a set of parameters, it computes a mock universe, which it then compares to observed statistical data to obtain a likelihood. Parameter space can be explored with several advanced stochastic algorithms such as MCMC to find the models that are in agreement with the observations.

[ascl:1910.005] exoplanet: Probabilistic modeling of transit or radial velocity observations of exoplanets

exoplanet is a toolkit for probabilistic modeling of transit and/or radial velocity observations of exoplanets and other astronomical time series using PyMC3 (ascl:1610.016), a flexible and high-performance model building language and inference engine. exoplanet extends PyMC3's language to support many of the custom functions and distributions required when fitting exoplanet datasets. These features include a fast and robust solver for Kepler's equation; scalable Gaussian processes using celerite (ascl:1709.008); and fast and accurate limb darkened light curves using the code starry (ascl:1810.005). It also offers common reparameterizations for limb darkening parameters, and planet radius and impact parameters.

[ascl:1910.004] DM_phase: Algorithm for correcting dispersion of radio signals

DM_phase maximizes the coherent power of a radio signal instead of its intensity to calculate the best dispersion measure (DM) for a burst such as those emitted by pulsars and fast radio bursts (FRBs). It is robust to complex burst structures and interference, thus mitigating the limitations of traditional methods that search for the best DM value of a source by maximizing the signal-to-noise ratio (S/N) of the detected signal.

[ascl:1910.003] a3cosmos-gas-evolution: Galaxy cold molecular gas evolution functions

a3cosmos-gas-evolution calculates galaxies' cold molecular gas properties using gas scaling functions derived from the A3COSMOS project. By known galaxies' redshifts or cosmic age, stellar masses, and star formation enhancement to galaxies' star-forming main sequence (Delta MS), the gas scaling functions predict their stellar mass ratio (gas fraction) and gas depletion time.

[ascl:1910.002] PreProFit: Pressure Profile Fitter for galaxy clusters in Python

PreProFit fits the pressure profile of galaxy clusters using Markov chain Monte Carlo (MCMC). The software can analyze data from different sources and offers flexible parametrization for the pressure profile. PreProFit accounts for Abel integral, beam smearing, and transfer function filtering when fitting data and returns χ2, model parameters and uncertainties in addition to marginal and joint probability contours, diagnostic plots, and surface brightness radial profiles. The code can be used for analytic approximations for the beam and transfer functions for feasibility studies.

[ascl:1910.001] PINK: Parallelized rotation and flipping INvariant Kohonen maps

Morphological classification is one of the most demanding challenges in astronomy. With the advent of all-sky surveys, an enormous amount of imaging data is publicly available, and are typically analyzed by experts or encouraged amateur volunteers. For upcoming surveys with billions of objects, however, such an approach is not feasible anymore. PINK (Parallelized rotation and flipping INvariant Kohonen maps) is a simple yet effective variant of a rotation-invariant self-organizing map that is suitable for many analysis tasks in astronomy. The code reduces the computational complexity via modern GPUs and applies the resulting framework to galaxy data for morphological analysis.

[ascl:1909.014] fgivenx: Functional posterior plotter

fgivenx plots a predictive posterior of a function, dependent on sampled parameters, for a Bayesian posterior Post(theta|D,M) described by a set of posterior samples {theta_i}~Post. If there is a function parameterized by theta y=f(x;theta), this script produces a contour plot of the conditional posterior P(y|x,D,M) in the (x,y) plane.

[ascl:1909.013] EPOS: Exoplanet Population Observation Simulator

EPOS (Exoplanet Population Observation Simulator) simulates observations of exoplanet populations. It provides an interface between planet formation simulations and exoplanet surveys such as Kepler. EPOS can also be used to estimate planet occurrence rates and the orbital architectures of planetary systems.

[ascl:1909.012] HISS: HI spectra stacker

HISS stacks HI (emission and absorption) spectra in a consistent and reliable manner to enable statistical analysis of average HI properties. It provides plots of the stacked spectrum and reference spectrum with any fitted function, of the stacked noise response, and of the distribution of the integrated fluxes when calculating the uncertainties. It also produces a table containing the integrated flux calculated from the fitted functions and the stacked spectrum, among other output files.

[ascl:1909.011] WVTICs: SPH initial conditions using Weighted Voronoi Tesselations

WVTICs generates glass-like initial conditions for Smoothed Particle Hydrodynamics. Relaxation of the particle distribution is done using an algorithm based on Weighted Voronoi Tesselations; additional particle reshuffling can be enabled to improve over- and undersampled maxima/minima. The WBTICs package includes a full suite of analytical test problems.

[ascl:1909.010] AREPO: Cosmological magnetohydrodynamical moving-mesh simulation code

AREPO is a massively parallel gravity and magnetohydrodynamics code for astrophysics, designed for problems of large dynamic range. It employs a finite-volume approach to discretize the equations of hydrodynamics on a moving Voronoi mesh, and a tree-particle-mesh method for gravitational interactions. AREPO is originally optimized for cosmological simulations of structure formation, but has also been used in many other applications in astrophysics.

[ascl:1909.009] CLOVER: Convolutional neural network spectra identifier and kinematics predictor

CLOVER (Convnet Line-fitting Of Velocities in Emission-line Regions) is a convolutional neural network (ConvNet) trained to identify spectra with two velocity components along the line of sight and predict their kinematics. It works with Gaussian emission lines (e.g., CO) and lines with hyperfine structure (e.g., NH3). CLOVER has two prediction steps, classification and parameter prediction. For the first step, CLOVER segments the pixels in an input data cube into one of three classes: noise (i.e., no emission), one-component (emission line with single velocity component), and two-component (emission line with two velocity components). For the pixels identified as two-components in the first step, a second regression ConvNet is used to predict centroid velocity, velocity dispersion, and peak intensity for each velocity component.

[ascl:1909.008] RascalC: Fast code for galaxy covariance matrix estimation

RascalC quickly estimates covariance matrices from two- or three-point galaxy correlation functions. Given an input set of random particle locations and a two-point correlation function (or input set of galaxy positions), RascalC produces an estimate of the associated covariance for a given binning strategy, with non-Gaussianities approximated by a ‘shot-noise-rescaling’ parameter. For the 2PCF, the rescaling parameter can be calibrated by dividing the particles into jackknife regions and comparing sample to theoretical jackknife covariance. RascalC can also be used to compute Legendre-binned covariances and cross-covariances between different two-point correlation functions.

[ascl:1909.007] EBHLIGHT: General relativistic radiation magnetohydrodynamics with Monte Carlo transport

EBHLIGHT (also referred to as BHLIGHT) solves the equations of general relativistic radiation magnetohydrodynamics in stationary spacetimes. Fluid integration is performed with the second order shock-capturing scheme HARM (ascl:1209.005) and frequency-dependent radiation transport is performed with the second order Monte Carlo code grmonty (ascl:1306.002). Fluid and radiation exchange four-momentum in an explicit first-order operator-split fashion.

[ascl:1909.006] ChempyMulti: Multi-star Bayesian inference with Chempy

ChempyMulti is an update to Chempy (ascl:1702.011) and provides yield table scoring and multi-star Bayesian inference. This replaces the ChempyScoring package in Chempy. Chempy is a flexible one-zone open-box chemical evolution model, incorporating abundance fitting and stellar feedback calculations. It includes routines for parameter optimization for simulations and observational data and yield table scoring.

[ascl:1909.005] HADES: Hexadecapolar Analysis for Dust Estimation in Simulations (of CMB B-mode thermal dust emission)

HADES analyzse dust levels in simulated CMB galactic dust maps with realistic experimental noise and lensing configurations. It allows detection of dust via its anisotropy properties in CMB B-modes. It also includes techniques for computing null-tests and a rudimentary technique for dedusting.

[ascl:1909.004] TPI: Test Particle Integrator

TPI computes the gravitational dynamics of particles orbiting a supermassive black hole (SBH). A distinction is made to two types of particles: test particles and field particles. Field particles are assumed to move in quasi-static Keplerian orbits around the SBH that precess due to the enclosed mass (Newtonian 'mass precession') and relativistic effects. Otherwise, field-particle-field-particle interactions are neglected. Test particles are integrated in the time-dependent potential of the field particles and the SBH. Relativistic effects are included in the equations of motion (including the effects of SBH spin), and test-particle-test-particle interactions are neglected.

[ascl:1909.003] SecularMultiple: Hierarchical multiple system secular evolution model

SecularMultiple computes the secular (orbit-averaged) gravitational dynamics of hierarchical multiple systems composed of nested binary orbits (simplex-type systems) with any configuration and any number of bodies. A particle can represent a binary or a body. The structure of the system is determined by linking to other particles with the attributes child1 and child2, and tidal interactions and relativistic corrections are included in an ad hoc fashion. SecularMultiple also includes routines for external perturbations such as flybys and supernovae.

[ascl:1909.002] MultiColorFits: Colorize and combine multiple fits images for visually aesthetic scientific plots

MultiColorFits is a tool to colorize and combine multiple fits images for making visually aesthetic scientific plots. The standard method to make color composites by combining fits images programmatically in python is to assign three images as separate red, green, and blue channels. This can produce unsatisfactory results for a variety of reasons, such as when less than three images are available, or additional images are desired to be shown. MultiColorFits breaks these limitations by allowing users to apply any color to a given image, not just red, green, or blue. Composites can then be created from an arbitrary number of images. Controls are included for stretching brightness scales with common functions.

[ascl:1909.001] Auto-multithresh: Automated masking for clean

Auto-multithresh implements an automated masking algorithm for clean. It operates on the residual image within the minor cycle of clean to identify and mask regions of significant emission. It then cascades these significant regions down to lower signal to noise. It includes features to pad the mask to avoid sharp edges and to remove small regions that are unlikely to be significant emission. The algorithm described by this code was incorporated into the tclean task within CASA as auto-multithresh.

[ascl:1908.025] FastCSWT: Fast directional Continuous Spherical Wavelet Transform

FastCSWT performs a directional continuous wavelet transform on the sphere. The transform is based on the construction of the continuous spherical wavelet transform (CSWT) developed by Antoine and Vandergheynst (1999). A fast implementation of the CSWT (based on the fast spherical convolution developed by Wandelt and Gorski 2001) is also provided.

[ascl:1908.024] PYSAT: Python Satellite Data Analysis Toolkit

The Python Satellite Data Analysis Toolkit (pysat) provides a simple and flexible interface for downloading, loading, cleaning, managing, processing, and analyzing space science data. The toolkit supports in situ satellite observations and many different types of ground- and space-based measurements. Its analysis routines are independent of instrument and data source.

[ascl:1908.023] FIRST Classifier: Automated compact and extended radio sources classifier

FIRST Classifier is an on-line system for automated classification of compact and extended radio sources. It is developed based on a trained Deep Convolutional Neural Network Model to automate the morphological classification of compact and extended radio sources observed in the FIRST radio survey. FIRST Classifier is able to predict the morphological class for a single source or for a list of sources as Compact or Extended (FRI, FRII and BENT).

[ascl:1908.022] YMW16: Electron-density model

YMW16 models the distribution of free electrons in the Galaxy, the Magellanic Clouds and the inter-galactic medium and can be used to estimate distances for real or simulated pulsars and fast radio bursts (FRBs) based on their position and dispersion measure. The Galactic model is based on 189 pulsars that have independently determined distances as well as dispersion measures, whereas simpler models are used for the electron density in the MC and the IGM.

[ascl:1908.021] bias_emulator: Halo bias emulator

bias_emulator models the clustering of halos on large scales. It incorporates the cosmological dependence of the bias beyond the mapping of halo mass to peak height. Precise measurements of the halo bias in the simulations are interpolated across cosmological parameter space to obtain the halo bias at any point in parameter space within the simulation cloud. A tool to produce realizations of correlated noise for propagating the modeling uncertainty into error budgets that use the emulator is also provided.

[ascl:1908.020] QLF: Luminosity function analysis code

QLF derives full posterior distributions for and analyzes luminosity functions models; it also models hydrogen and helium reionization. Used with the included homogenized data, the derived luminosity functions can be easily compared with theoretical models or future data sets.

[ascl:1908.019] MAESTROeX: Low Mach number stellar hydrodynamics code

MAESTROeX solves the equations of low Mach number hydrodynamics for stratified atmospheres or stars with a general equation of state. It includes reactions and thermal diffusion and can be used on anything from a single core to 100,000s of processor cores with MPI + OpenMP. MAESTROeX maintains the accuracy of its predecessor MAESTRO (ascl:1010.044) while taking advantage of a simplified temporal integration scheme and leveraging the AMReX software framework for block-structured adaptive mesh refinement (AMR) applications.

[ascl:1908.018] EBAI: Eclipsing Binaries with Artificial Intelligence

Eclipsing Binaries via Artificial Intelligence (EBAI) automates the process of solving light curves of eclipsing binary stars. EBAI is based on the back-propagating neural network paradigm and is highly flexible in construction of neural networks. EBAI comes in two flavors, serial (ebai) and multi-processor (ebai.mpi), and can be run in training, continued training, and recognition mode.

[ascl:1908.017] JPLephem: Jet Propulsion Lab ephemerides package

JPLephem loads and uses standard Jet Propulsion Laboratory (JPL) ephemerides for predicting the position and velocity of a planet or other Solar System body. It is one of the foundations of the Skyfield (ascl:1907.024) astronomy library for Python, and can also be used as a standalone package to generate raw vectors.

[ascl:1908.016] DustCharge: Charge distribution for a dust grain

DustCharge calculates the equilibrium charge distribution for a dust grain of a given size and composition, depending on the local interstellar medium conditions, such as density, temperature, ionization fraction, local radiation field strength, and cosmic ray ionization fraction.

[ascl:1908.015] Analysator: Quantitative analysis of Vlasiator files

Analysator analyzes vlsv files produced by Vlasiator (ascl:1908.014). The code facilitates studies of particle paths, pitch angle distributions, velocity distributions, and more. It can read and write VLSV files and do calculations with the data, plot the real space from VLSV files with Mayavi (ascl:1205.008), and plot the velocity space (both blocks and iso surface) from VLSV files. It can also take cut-throughs, pitch angle distributions, gyrophase angle, and 3d slices, plot variables with sub plots in a clean format, and fit 1D polynomials to data.

[ascl:1908.014] Vlasiator: Hybrid-Vlasov simulation code

Vlasiator is a 6-dimensional Vlasov theory-based simulation. It simulates the entire near-Earth space at a global scale using the kinetic hybrid-Vlasov approach, to study fundamental plasma processes (reconnection, particle acceleration, shocks), and to gain a deeper understanding of space weather.

[ascl:1908.013] BEAST: Bayesian Extinction And Stellar Tool

BEAST (Bayesian Extinction and Stellar Tool) fits the ultraviolet to near-infrared photometric SEDs of stars to extract stellar and dust extinction parameters. The stellar parameters are age (t), mass (M), metallicity (M), and distance (d). The dust extinction parameters are dust column (Av), average grain size (Rv), and mixing between type A and B extinction curves (fA).

[ascl:1908.012] oscode: Oscillatory ordinary differential equation solver

oscode solves oscillatory ordinary differential equations efficiently. It is designed to deal with equations of the form x¨(t)+2γ(t)x˙(t)+ω2(t)x(t)=0, where γ(t) and ω(t) can be given as explicit functions or sequence containers (Eigen::Vectors, arrays, std::vectors, lists) in C++ or as numpy.arrays in Python. oscode makes use of an analytic approximation of x(t) embedded in a stepping procedure to skip over long regions of oscillations, giving a reduction in computing time. The approximation is valid when the frequency changes slowly relative to the timescales of integration, it is therefore worth applying when this condition holds for at least some part of the integration range.

[ascl:1908.011] NuRadioMC: Monte Carlo simulation package for radio neutrino detectors

NuRadioMC simulates ultra-high energy neutrino detectors that rely on the radio detection method, which exploits the radio emission generated in the electromagnetic component of a particle shower following a neutrino interaction. The code simulates the neutrino interaction in a medium, subsequent Askaryan radio emission, propagation of the radio signal to the detector and the detector response. NuRadioMC is a Monte Carlo framework that combines flexibility in detector design with user-friendliness. It includes an event generator, improved modeling of the radio emission, a revisited approach to signal propagation, and increased flexibility and precision in the detector simulation.

[ascl:1908.010] SNAPDRAGONS: Stellar Numbers And Parameters Determined Routinely And Generated Observing N-body Systems

SNAPDRAGONS (Stellar Numbers And Parameters Determined Routinely And Generated Observing N-body Systems) is a simplified version of the population synthesis code Galaxia (ascl:1101.007), using a different process to generate the stellar catalog. It splits each N-body particle from the galaxy simulation into an appropriate number of stellar particles to create a mock catalog of observable stars from the N-body model. SNAPDRAGON uses the same isochrones and extinction map as Galaxia.

[ascl:1908.009] PyRADS: Python RADiation model for planetary atmosphereS

The 1D radiation code PyRADS provides line-by-line spectral resolution. For Earth-like atmospheres, PyRADS currently uses HITRAN 2016 line lists and the MTCKD continuum model. A version for shortwave radiation (scattering) is also available.

[ascl:1908.008] TRISTAN-MP: TRIdimensional STANford - Massively Parallel code

TRISTAN-MP is a fully relativistic Particle-In-Cell (PIC) code for plasma physics computations and self-consistently solves the full set of Maxwell’s equations, along with the relativistic equations of motion for the charged particles. Fields are discretized on a finite 3D or 2D mesh, the computational grid; the code then uses time-centered and space-centered finite difference schemes to advance the equations in time via the Lorentz force equation, and to calculate spatial derivatives, so that the algorithm is second order accurate in space and time. The charges and currents derived from the particles' velocities and positions are then used as source terms to re-calculate the electromagnetic fields. TRISTAN-MP is based on the original TRISTAN code (ascl:2008.025) by O. Buneman (1993).

[ascl:1908.007] MosfireDRP: MOSFIRE Data Reduction Pipeline

MosfireDRP reduces data from the MOSFIRE spectrograph of the Keck Observatory; it produces flat-fielded, wavelength calibrated, rectified, and stacked 2D spectrograms for each slit on a given mask in nearly real time. Background subtraction is performed in two states: a simple pairwise subtraction of interleaved stacks, and then fitting a 2D b-spline model to the background residuals.

[ascl:1908.006] GBKFIT: Galaxy kinematic modeling

GBKFIT performs galaxy kinematic modeling. It can be used to extract morphological and kinematical properties of galaxies by fitting models to spatially resolved kinematic data. The software can also take beam smearing into account by using the knowledge of the line and point spread functions. GBKFIT can take advantage of many-core and massively parallel architectures such as multi-core CPUs and Graphics Processing Units (GPUs), making it suitable for modeling large-scale surveys of thousands of galaxies within a very seasonable time frame. GBKFIT features an extensible object-oriented architecture that supports arbitrary models and optimization techniques in the form of modules; users can write custom modules without modifying GBKFIT’s source code. The software is written in C++ and conforms to the latest ISO standards.

[ascl:1908.005] dips: Detrending periodic signals in timeseries

dips detrends timeseries of strictly periodic signals. It does not assume any functional form for the signal or the background or the noise; it disentangles the strictly periodic component from everything else. It has been used for detrending Kepler, K2 and TESS timeseries of periodic variable stars, eclipsing binary stars, and exoplanets.

[ascl:1908.004] Gramsci: GRAph Made Statistics for Cosmological Information

Gramsci (GRAph Made Statistics for Cosmological Information) computes the general N-point spatial correlation functions of any discrete point set embedded within an Euclidean space of ℝ^n. It uses kd-trees and graph databases to count all possible N-tuples in binned configurations within a given length scale, e.g. all pairs of points or all triplets of points with side lengths. Gramsci can run in serial, OpenMP, MPI and hybrid parallel schemes. It is useful for performing domain decomposition of input catalogs, especially if the catalogs are large or the Rmax value is too large.

[ascl:1908.003] ActSNClass: Active learning for supernova photometric classification

ActSNClass uses a parametric feature extraction method, Random Forest classifier and two learning strategies (uncertainty sampling and random sampling) to performs active learning for supernova photometric classification.

[ascl:1908.002] Molsoft: Molonglo Telescope Observing Software

Molsoft operates, monitors and schedules observations, both through predetermined schedule files and fully dynamically, at the refurbished Molonglo Observatory Synthesis Radio Telescope (MOST). It was developed as part of the UTMOST upgrade of the facility. The software runs a large-scale pulsar timing program; the autonomous observing system and the dynamic scheduler have increased the observing efficiency by a factor of 2-3 in comparison with static scheduling.

[ascl:1908.001] QAC: Quick Array Combinations front end to CASA

QAC (Quick Array Combinations) is a front end to CASA (ascl:1107.013) and calls tools and tasks to help in combining data from a single dish and interferometer. QAC hides some of the complexity of writing CASA scripts and provides a simple interface to array combination tools and tasks in CASA. This project was conceived alongside the TP2VIS (ascl:1904.021) project, where it was used to provide an easier way to call CASA and perform regression tests.

[ascl:1907.032] Astro-SCRAPPY: Speedy Cosmic Ray Annihilation Package in Python

Astro-SCRAPPY detects cosmic rays in images (numpy arrays), based on Pieter van Dokkum's L.A.Cosmic algorithm and originally adapted from cosmics.py written by Malte Tewes. This implementation is optimized for speed, resulting in slight difference from the original code, such as automatic recognition of saturated stars (rather than treating such stars as large cosmic rays, and use of a separable median filter instead of the true median filter. Astro-SCRAPPY is an AstroPy (ascl:1304.002) affiliated package.

[ascl:1907.031] MGB: Interactive spectral classification code

MGB (Marxist Ghost Buster) attacks spectral classification by using an interactive comparison with spectral libraries. It allows the user to move along the two traditional dimensions of spectral classification (spectral subtype and luminosity classification) plus the two additional ones of rotation index and spectral peculiarities. Double-lined spectroscopic binaries can also be fitted using a combination of two standards. The code includes OB2500 v2.0, a standard grid of blue-violet R ~ 2500 spectra of O stars from the Galactic O-Star Spectroscopic Survey, but other grids can be added to MGB.

[ascl:1907.030] Wōtan: Stellar detrending methods

Wōtan provides free and open source algorithms to remove trends from time-series data automatically as an aid to search efficiently for transits in stellar light curves from surveys. The toolkit helps determine empirically the best tool for a given job, serving as a one-stop solution for various smoothing tasks.

[ascl:1907.029] XDF-GAN: Mock astronomical survey generator

XDF-GAN generates mock galaxy surveys with a Spatial Generative Adversarial Network (SGAN)-like architecture. Mock galaxy surveys are generated from data that is preprocessed as little as possible (preprocessing is only a 99.99th percentile clipping). The outputs can also be tessellated together to create a very large survey, limited in size only by the RAM of the generation machine.

[ascl:1907.028] ROHSA: Separation of diffuse sources in hyper-spectral data

ROHSA (Regularized Optimization for Hyper-Spectral Analysis) reveals the statistical properties of interstellar gas through atomic and molecular lines. It uses a Gaussian decomposition algorithm based on a multi-resolution process from coarse to fine grid to decompose any kind of hyper-spectral observations into a sum of coherent Gaussian. Optimization is performed on the whole data cube at once to obtain a solution with spatially smooth parameters.

[ascl:1907.027] intensitypower: Spectrum multipoles modeler

intensitypower measures and models the auto- and cross-power spectrum multipoles of galaxy catalogs and radio intensity maps presented in spherical coordinates. It can also convert the multipoles to power spectrum wedges P(k,mu) and 2D power spectra P(k_perp,k_par). The code assumes the galaxy catalog is a set of discrete points and the radio intensity map is a pixelized continuous field which includes angular pixelization using healpix, binning in redshift channels, smoothing by a Gaussian telescope beam, and the addition of a Gaussian noise in each cell. The galaxy catalog and radio intensity map are transferred onto an FFT grid, and power spectrum multipoles are measured including curved-sky effects. Both maps include redshift-space distortions.

[ascl:1907.026] MCRGNet: Morphological Classification of Radio Galaxy Network

MCRGNet (Morphological Classification of Radio Galaxy Network) classifies radio galaxies of different morphologies. It is based on the Convolutional Neural Network (CNN), which is trained and applied under a three-step framework: 1.) pretraining the network unsupervisedly with unlabeled samples, 2.) fine-tuning the pretrained network parameters supervisedly with labeled samples, and 3.) classifying a new radio galaxy by the trained network. The code uses a dichotomous tree classifier composed of cascaded CNN based subclassifiers.

[ascl:1907.025] GIST: Galaxy IFU Spectroscopy Tool

GIST (Galaxy IFU Spectroscopy Tool) provides a convenient all-in-one framework for the scientific analysis of fully reduced, (integral-field) spectroscopic data, conducting all the steps from the preparation of input data to the scientific analysis and to the production of publication-quality plots. In its basic set-up, the GIST pipeline extracts stellar kinematics, performs an emission-line analysis, and derives stellar population properties from full spectral fitting and via the measurement of absorption line-strength indices by exploiting pPXF (ascl:1210.002)and GandALF routines. The pipeline is not specific to any instrument or analysis technique, and includes a dedicated visualization routine with a sophisticated graphical user interface for fully interactive plotting of all measurements, spectra, fits, and residuals, as well as star formation histories and the weight distribution of the models.

[ascl:1907.024] Skyfield: High precision research-grade positions for planets and Earth satellites generator

Skyfield computes positions for the stars, planets, and satellites in orbit around the Earth. Its results should agree with the positions generated by the United States Naval Observatory and their Astronomical Almanac to within 0.0005 arcseconds (which equals half a “mas” or milliarcsecond). It computes geocentric coordinates or topocentric coordinates specific to your location on the Earth’s surface. Skyfield accepts AstroPy (ascl:1304.002) time objects as input and can return results in native AstroPy units but is not dependend on AstroPy nor its compiled libraries.

[ascl:1907.023] REVOLVER: REal-space VOid Locations from suVEy Reconstruction

REVOLVER reconstructs real space positions from redshift-space tracer data by subtracting RSD through FFT-based reconstruction (optional) and applies void-finding algorithms to create a catalogue of voids in these tracers. The tracers are normally galaxies from a redshift survey but could also be halos or dark matter particles from a simulation box. Two void-finding routines are provided. The first is based on ZOBOV (ascl:1304.005) and uses Voronoi tessellation of the tracer field to estimate the local density, followed by a watershed void-finding step. The second is a voxel-based method, which uses a particle-mesh interpolation to estimate the tracer density, and then uses a similar watershed algorithm. Input data files can be in FITS format, or ASCII- or NPY-formatted data arrays.

[ascl:1907.022] CMDPT: Color Magnitude Diagrams Plot Tool

CMD Plot Tool calculates and plots Color Magnitude Diagrams (CMDs) from astronomical photometric data, e.g. of a star cluster observed in two filter bandpasses. It handles multiple file formats (plain text, DAOPHOT .mag files, ACS Survey of Galactic Globular Clusters .zpt files) to generate professional and customized plots without a steep learning curve. It works “out of the box” and does not require any installation of development environments, additional libraries, or resetting of system paths. The tool is available as a single application/executable file with the source code. Sample data is also bundled for demonstration. CMD Plot Tool can also convert DAOPHOT magnitude files to CSV format.

[ascl:1907.021] PRISM: Probabilistic Regression Instrument for Simulating Models

PRISM analyzes scientific models using the Bayes linear approach, the emulation technique, and history matching to construct an approximation ('emulator') of any given model. The software facilitates and enhances existing MCMC methods by restricting plausible regions and exploring parameter space efficiently and can be used as a standalone alternative to MCMC for model analysis, providing insight into the behavior of complex scientific models. PRISM stores results in HDF5-files and can be executed in serial or MPI on any number of processes. It accepts any type of model and comparison data and can reduce relevant parameter space by factors over 100,000 using only a few thousand model evaluations.

[ascl:1907.020] GaussPy+: Gaussian decomposition package for emission line spectra

GaussPy+ is a fully automated Gaussian decomposition package for emission line spectra. It is based on GaussPy (ascl:1907.019) and offers several improvements, including automating preparatory steps and providing an accurate noise estimation, improving the fitting routine, and providing a routine to refit spectra based on neighboring fit solutions. GaussPy+ handles complex emission and low to moderate signal-to-noise values.

[ascl:1907.019] GaussPy: Python implementation of the Autonomous Gaussian Decomposition algorithm

GaussPy implements the Autonomous Gaussian Decomposition (AGD) algorithm, which uses computer vision and machine learning techniques to provide optimized initial guesses for the parameters of a multi-component Gaussian model automatically and efficiently. The speed and adaptability of AGD allow it to interpret large volumes of spectral data efficiently. Although it was initially designed for applications in radio astrophysics, AGD can be used to search for one-dimensional Gaussian (or any other single-peaked spectral profile)-shaped components in any data set. To determine how many Gaussian functions to include in a model and what their parameters are, AGD uses a technique called derivative spectroscopy. The derivatives of a spectrum can efficiently identify shapes within that spectrum corresponding to the underlying model, including gradients, curvature and edges.

[ascl:1907.018] StePar: Inferring stellar atmospheric parameters using the EW method

StePar computes the stellar atmospheric parameters Teff, log g, [Fe/H], and ξ of FGK-type stars using the Equivalent Width (EW) method. The code implements a grid of MARCS model atmospheres and uses the MOOG radiative transfer code (ascl:1202.009) and TAME (ascl:1503.003). StePar uses a Downhill Simplex minimization algorithm, running it twice for any given star, to compute the stellar atmospheric parameters.

[ascl:1907.017] ZChecker: Zwicky Transient Facility moving target checker for short object lists

ZChecker finds, measures, and visualizes known comets in the Zwicky Transient Facility time-domain survey. Images of targets are identified using on-line ephemeris generation and survey metadata. The photometry of the targets are measured and the images are processed with temporal filtering to highlight morphological variations in time.

[ascl:1907.016] astrodendro: Astronomical data dendrogram creator

Astrodendro, written in Python, creates dendrograms for exploring and displaying hierarchical structures in observed or simulated astronomical data. It handles noisy data by allowing specification of the minimum height of a structure and the minimum number of pixels needed for an independent structure. Astrodendro allows interactive viewing of computed dendrograms and can also produce publication-quality plots with the non-interactive plotting interface.

[ascl:1907.015] TurbuStat: Turbulence statistics in spectral-line data cubes

TurbuStat implements a variety of turbulence-based statistics described in the astronomical literature and defines distance metrics for each statistic to quantitatively compare spectral-line data cubes, as well as column density, integrated intensity, or other moment maps. The software can simulate observations of fractional Brownian Motion fields, including 2-D images and optically thin H I data cubes. TurbuStat also offers multicore fast-Fourier-transform support and provides a segmented linear model for fitting lines with a break point.

[ascl:1907.014] sbpy: Small-body planetary astronomy

sbpy, an Astropy affiliated package, supplements functionality provided by Astropy (ascl:1304.002) with functions and methods that are frequently used for planetary astronomy with a clear focus on asteroids and comets. It offers access tools for various databases for orbital and physical data, spectroscopy analysis tools and models, photometry models for resolved and unresolved observations, ephemerides services, and other tools useful for small-body planetary astronomy.

[ascl:1907.013] RVSpecFit: Radial velocity and stellar atmospheric parameter fitting

RVSpecFit determines radial velocities and stellar atmospheric parameters from spectra by direct pixel fitting by interpolated stellar templates. The code doesn't require spectrum normalization and can deal with non-flux calibrated spectra. RVSpecFit is able to fit multiple spectra simultaneously.

[ascl:1907.012] molly: 1D astronomical spectra analyzer

molly analyzes 1D astronomical spectra. Its prime purpose is for handling large numbers of similar spectra (e.g., time series spectroscopy), but it contains many of the standard operations used for normal spectrum analysis as well. It overlaps with the various similar programs such as dipso (ascl:1405.016) and has strengths (particularly for time series spectra) and weaknesses compared to them.

[ascl:1907.011] beamconv: Cosmic microwave background detector data simulator

beamconv simulates the scanning of the CMB sky while incorporating realistic beams and scan strategies. It uses (spin-)spherical harmonic representations of the (polarized) beam response and sky to generate simulated CMB detector signal timelines. Beams can be arbitrarily shaped. Pointing timelines can be read in or calculated on the fly; optionally, the results can be binned on the sphere.

[ascl:1907.010] OMNICAL: Redundant calibration code for low frequency radio interferometers

OMNICAL calibrates antennas in the redundant subset of the array. The code consists of two algorithms, a logarithmic method (logcal) and a linearized method (lincal). OMNICAL makes visibilities from physically redundant baselines agree with each other and also explicitly minimizes the variance within redundant visibilities.

[ascl:1907.009] Plonk: Smoothed particle hydrodynamics data analysis and visualization

Plonk analyzes and visualizes smoothed particle hydrodynamics simulation data, focusing on astrophysical applications. It calculates extra quantities on the particles, calculates and plots radial profiles, accesses subsets of particles, and provides visualization of any quantity defined on the particles via kernel density estimation. Plock's visualization module uses Splash (ascl:1103.004) to produce images using smoothed particle hydrodynamics interpolation. The code is modular and extendible, and can be scripted or used interactively.

[ascl:1907.008] Dewarp: Distortion removal and on-sky orientation solution for LBTI detectors

Dewarp constructs pipelines to remove distortion from a detector and find the orientation with true North. It was originally written for the LBTI LMIRcam detector, but is generalizable to any project with reference sources and/or an astrometric field paired with a machine-readable file of astrometric target locations.

[ascl:1907.007] SPAM: Hu-Sawicki f(R) gravity imprints search

SPAM searches for imprints of Hu-Sawicki f(R) gravity on the rotation curves of the SPARC (Spitzer Photometry and Accurate Rotation Curves) sample using the MCMC sampler emcee (ascl:1303.002). The code provides attributes for inspecting the MCMC chains and translating names of parameters to indices. The SPAM package also contains plotting scripts.

[ascl:1907.006] POCS: PANOPTES Observatory Control System

PANOPTES (Panoptic Astronomical Networked Observatories for a Public Transiting Exoplanets Survey) is a citizen science project for low cost, robotic detection of transiting exoplanets. POCS (PANOPTES Observatory Control System) is the main software driver for the PANOPTES telescope system, responsible for high-level control of the unit. POCS defines an Observatory class that automatically controls a commercially available equatorial mount, including image analysis and corresponding mount adjustment to obtain a percent-level photometric precision.

[ascl:1907.005] SARA-PPD: Preconditioned primal-dual algorithm for radio-interferometric imaging

SARA-PPD is a proof of concept MATLAB implementation of an acceleration strategy for a recently proposed primal-dual distributed algorithm. The algorithm optimizes resolution by accounting for the correct noise statistics, leverages natural weighting in the definition of the minimization problem for image reconstruction, and optimizes sensitivity by enabling accelerated convergence through a preconditioning strategy incorporating sampling density information. This algorithm offers efficient processing of large-scale data sets that will be acquired by next generation radio-interferometers such as the Square Kilometer Array.

[ascl:1907.004] pyGTC: Parameter covariance plots

pyGTC creates giant triangle confusogram (GTC) plots. Triangle plots display the results of a Monte-Carlo Markov Chain (MCMC) sampling or similar analysis. The recovered parameter constraints are displayed on a grid in which the diagonal shows the one-dimensional posteriors (and, optionally, priors) and the lower-left triangle shows the pairwise projections. Such plots are useful for seeing the parameter covariances along with the priors when fitting a model to data.

[ascl:1907.003] pyuvdata: Pythonic interface to interferometric data sets

pyuvdata defines a pythonic interface to interferometric data sets; it supports the development of and interchange of data between calibration and foreground subtraction pipelines. It can read and write MIRIAD (ascl:1106.007), uvfits, and uvh5 files and reads CASA (ascl:1107.013) measurement sets and FHD (ascl:2205.014) visibility save files. Particular focus has been paid to supporting drift and phased array modes.

[ascl:1907.002] healvis: Radio interferometric visibility simulator based on HEALpix maps

Healvis simulates radio interferometric visibility off of HEALPix shells. It generates a flat-spectrum and a GSM model and computes visibilities, and can simulates visibilities given an Observation Parameter YAML file. Healvis can perform partial frequency simulations in serial to minimize instantaneous memory loads.

[ascl:1907.001] schwimmbad: Parallel processing pools interface

schwimmbad provides a uniform interface to parallel processing pools and enables switching easily between local development (e.g., serial processing or with multiprocessing) and deployment on a cluster or supercomputer (via, e.g., MPI or JobLib). The utilities provided by schwimmbad require that tasks or data be “chunked” and that code can be “mapped” onto the chunked tasks.

[ascl:1906.022] pyLIMA: Microlensing modeling package

pyLIMA (python Lightcurve Identification and Microlensing Analysis) fits microlensing lightcurves and derives the physical quantities of lens systems. The package provides microlensing modeling, and the magnification estimation for high cadence lightcurves has been optimized. pyLIMA is designed to make microlensing modeling and event simulation widely available to the community.

[ascl:1906.021] centerRadon: Center determination code in stellar images

centerRadon finds the center of stars based on Radon Transform to sub-pixel precision. For a coronagraphic image of a star, it starts from a given location, then for each sub-pixel position, it interpolates the image and sums the pixels along different angles, creating a cost function. The center of the star is expected to correspond with where the cost function maximizes. The default values are set for the STIS coronagraphic images of the Hubble Space Telescope by summing over the diagonals (i.e., 45° and 135°), but it can be generally applied to other high-contrast imaging instruments with or without Adaptive Optics systems such as HST-NICMOS, P1640, or GPI.

[ascl:1906.020] LIZARD: Particle initial conditions for cosmological simulations

LIZARD (Lagrangian Initialization of Zeldovich Amplitudes for Resimulations of Displacements) creates particle initial conditions for cosmological simulations using the Zel'dovich approximation for the matter and velocity power spectrum.

[ascl:1906.019] PlasmaPy: Core Python package for plasma physics

PlasmaPy provides core functionality and a common framework for data visualization and analysis for plasma physics. It has modules for basic plasma physics calculations, running desktop-scale simulations to test preliminary ideas such as one-dimensional MHD/PIC or test particles, or comparing data from two different sources, such as simulations and spacecraft.

[ascl:1906.018] MEGAlib: Medium Energy Gamma-ray Astronomy library

The Medium Energy Gamma-ray Astronomy library (MEGAlib) simulates, calibrates, and analyzes data of hard X-ray and gamma-ray detectors, with a specialization on Compton telescopes. The library comprises all necessary data analysis steps for these telescopes, from simulation/measurements via calibration, event reconstruction to image reconstruction.

MEGAlib contains a geometry and detector description tool for the detailed modeling of different detector types and characteristics, and provides an easy to use simulation program based on Geant4 (ascl:1010.079). For different Compton telescope detector types (electron tracking, multiple Compton or time of flight based), specialized Compton event reconstruction algorithms are implemented in different approaches (Chi-square and Bayesian). The high level data analysis tools calculate response matrices, perform image deconvolution (specialized in list-mode-likelihood-based Compton image reconstruction), determine detector resolutions and sensitivities, retrieve spectra, and determine polarization modulations.

[ascl:1906.017] mcfit: Multiplicatively Convolutional Fast Integral Transforms

mcfit computes integral transforms, inverse transforms without analytic inversion, and integral kernels as derivatives. It can also transform input array along any axis, output the matrix form, an is easily extensible for other kernels.

[ascl:1906.016] PandExo: Instrument simulations for exoplanet observation planning

PandExo generates instrument simulations of JWST’s NIRSpec, NIRCam, NIRISS and NIRCam and HST WFC3 for planning exoplanet observations. It uses throughput calculations from STScI’s Exposure Time Calculator, Pandeia, and offers both an online tool and a python package.

[ascl:1906.015] OIT: Nonconvex optimization approach to optical-interferometric imaging

In the context of optical interferometry, only undersampled power spectrum and bispectrum data are accessible, creating an ill-posed inverse problem for image recovery. Recently, a tri-linear model was proposed for monochromatic imaging, leading to an alternated minimization problem; in that work, only a positivity constraint was considered, and the problem was solved by an approximated Gauss–Seidel method.

The Optical-Interferometry-Trilinear code improves the approach on three fundamental aspects. First, the estimated image is defined as a solution of a regularized minimization problem, promoting sparsity in a fixed dictionary using either an l1 or a (re)weighted-l1 regularization term. Second, the resultant non-convex minimization problem is solved using a block-coordinate forward–backward algorithm. This algorithm is able to deal both with smooth and non-smooth functions, and benefits from convergence guarantees even in a non-convex context. Finally, the model and algorithm are generalized to the hyperspectral case, promoting a joint sparsity prior through an l2,1 regularization term.

[ascl:1906.014] GPUVMEM: Maximum Entropy Method (MEM) GPU algorithm for radio astronomical image synthesis

The maximum entropy method (MEM) is a well known deconvolution technique in radio-interferometry. This method solves a non-linear optimization problem with an entropy regularization term. Other heuristics such as CLEAN are faster but highly user dependent. Nevertheless, MEM has the following advantages: it is unsupervised, it has a statistical basis, it has a better resolution and better image quality under certain conditions. GPUVMEM presents a high performance GPU version of non-gridding MEM.

[ascl:1906.013] MORPHEUS: A 3D Eulerian Godunov MPI-OpenMP hydrodynamics code with multiple grid geometries

MORPHEUS (Manchester Omni-geometRical Program for Hydrodynamical EUlerian Simulations) is a 3D hydrodynamical code used to simulate astrophysical fluid flows. It has three different grid geometries (cartesian, spherical, and cylindrical) and uses a second-order Godunov method to solve the equations of hydrodynamics. Physical modules also include radiative cooling and gravity, and a hybrid MPI-OpenMP parallelization allows computations to be run on large-scale architectures. MORPHEUS is written in Fortran90 and does not require any libraries (apart from MPI) to run.

[ascl:1906.012] Morpheus: Library to generate morphological semantic segmentation maps of astronomical images

Morpheus generates pixel level morphological classifications of astronomical sources by leveraging advances in deep learning to perform source detection, source segmentation, and morphological classification pixel-by-pixel via a semantic segmentation algorithm adopted from the field of computer vision. By utilizing morphological information about the flux of real astronomical sources during object detection, Morpheus shows resiliency to false positive identifications of sources.

[ascl:1906.011] Lizard: An extensible Cyclomatic Complexity Analyzer

Lizard is an extensible Cyclomatic Complexity Analyzer for imperative programming languages including C/C++/C#, Python, Java, and Javascript. It counts the nloc (lines of code without comments) and CCN (cyclomatic complexity number), and takes a token count of functions and a parameter count of functions. It also does copy-paste detection (code clone detection/code duplicate detection) and many other forms of static code analysis. Lizard is often used in software-related research and calculates how complex the code looks rather than how complex the code really is; thought it's often very hard to get all the included folders and files right when they are complicated, that accuracy is not needed to determine cyclomatic complexity, which can be useful for measuring the maintainability of a software package.

[ascl:1906.010] PyA: Python astronomy-related packages

The PyA (PyAstronomy) suite of astronomy-related packages includes a convenient fitting package that provides support for minimization and MCMC sampling, a set of astrophysical models (e.g., transit light-curve modeling), and algorithms for timing analysis such as the Lomb-Scargle and the Generalized Lomb-Scargle periodograms.

[ascl:1906.009] PyMORESANE: Python MOdel REconstruction by Synthesis-ANalysis Estimators

PyMORESANE is a Python and pyCUDA-accelerated implementation of the MORESANE deconvolution algorithm, a sparse deconvolution algorithm for radio interferometric imaging. It can restore diffuse astronomical sources which are faint in brightness, complex in morphology and possibly buried in the dirty beam’s side lobes of bright radio sources in the field.

[ascl:1906.008] T-RECS: Tiered Radio Extragalactic Continuum Simulation

T-RECS produces radio sources catalogs with user-defined frequencies, area and depth. It models two main populations of radio galaxies, Active Galactic Nuclei (AGNs) and Star-Forming Galaxies (SFGs), and corresponding sub-populations. T-RECS is not computationally demanding and can be run multiple times, using the same catalog inputs, to project the simulated sky onto different fields.

[ascl:1906.007] limb-darkening: Limb-darkening coefficients generator

Limb-darkening generates limb-darkening coefficients from ATLAS and PHOENIX model atmospheres using arbitrary response functions. The code uses PyFITS (ascl:1207.009) and has several other dependencies, and produces a folder of results with descriptions of the columns contained in each file.

[ascl:1906.006] turboSETI: Python-based SETI search algorithm

TurboSETI analyzes filterbank data (frequency vs. time) for narrow band drifting signals; its main purpose is to search for signals of extraterrestrial origin. TurboSETI can search the data for hundreds of drift rates (in Hz/sec) and handles either .fil or .h5 file formats. It has several dependencies, including Blimpy (ascl:1906.002) and Astropy (ascl:1304.002).

[ascl:1906.005] Kalman: Forecasts and interpolations for ALMA calibrator variability

Kalman models an inhomogeneous time series of measurements at different frequencies as noisy sampling from a finite mixture of Gaussian Ornstein-Uhlenbeck processes to try to reproduce the variability of the fluxes and of the spectral indices of the quasars used as calibrators in the Atacama Large Millimeter/Sub-millimeter Array (ALMA), assuming sensible parameters are provided to the model (obtained, for example, from maximum likelihood estimation). One routine in the Kalman Perl module calculates best forecast estimations based on a state space representation of the stochastic model using Kalman recursions, and another routine calculates the smoothed estimation (or interpolations) of the measurements and of the state space also using Kalman recursions. The code does not include optimization routines to calculate best fit parameters for the stochastic processes.

[ascl:1906.004] The Exo-Striker: Transit and radial velocity interactive fitting tool for orbital analysis and N-body simulations

The Exo-Striker analyzes exoplanet orbitals, performs N-body simulations, and models the RV stellar reflex motion caused by dynamically interacting planets in multi-planetary systems. It offers a broad range of tools for detailed analysis of transit and Doppler data, including power spectrum analysis for Doppler and transit data; Keplerian and dynamical modeling of multi-planet systems; MCMC and nested sampling; Gaussian Processes modeling; and a long-term stability check of multi-planet systems. The Exo-Striker can also analyze Mean Motion Resonance (MMR) analysis, create fast fully interactive plots, and export ready-to-use LaTeX tables with best-fit parameters, errors, and statistics. It combines Fortran efficiency and Python flexibility and is cross-platform compatible (MAC OS, Linux, Windows). The tool relies on a number of open-source packages, including RVmod engine, emcee (ascl:1303.002), batman (ascl:1510.002), celerite (ascl:1709.008), and dynesty (ascl:1809.013).

[ascl:1906.003] FREDDA: A fast, real-time engine for de-dispersing amplitudes

FREDDA detects Fast Radio Bursts (FRBs) in power data. It is optimized for use at ASKAP, namely GHz frequencies with 10s of beams, 100s of channels and millisecond integration times. The code is written in CUDA for NVIDIA Graphics Processing Units.

[ascl:1906.002] Blimpy: Breakthrough Listen I/O Methods for Python

Blimpy (Breakthrough Listen I/O Methods for Python) provides utilities for viewing and interacting with the data formats used within the Breakthrough Listen program, including Sigproc filterbank (.fil) and HDF5 (.h5) files that contain dynamic spectra (aka 'waterfalls'), and guppi raw (.raw) files that contain voltage-level data. Blimpy can also extract, calibrate, and visualize data and a suite of command-line utilities are also available.

[ascl:1906.001] Astroalign: Asterism-matching alignment of astronomical images

Astroalign tries to register (align) two stellar astronomical images, especially when there is no WCS information available. It does so by finding similar 3-point asterisms (triangles) in both images and deducing the affine transformation between them. Generic registration routines try to match feature points, using corner detection routines to make the point correspondence. These generally fail for stellar astronomical images since stars have very little stable structure so are, in general, indistinguishable from each other. Asterism matching is more robust and closer to the human way of matching stellar images. Astroalign can match images of very different field of view, point-spread function, seeing and atmospheric conditions. It may require special care or may not work on images of extended objects with few point-like sources or in crowded fields.

[submitted] Sacc: Save All Correlations and Covariances

SACC (Save All Correlations and Covariances) is a format and reference library for general storage
of summary statistic measurements for the Dark Energy Science Collaboration (DESC) within and from the Large Synoptic Survey Telescope (LSST) project's Dark Energy Science Collaboration.

[ascl:1905.027] PyPDR: Python Photo Dissociation Regions

PyPDR calculates the chemistry, thermal balance and molecular excitation of a slab of gas under FUV irradiation in a self-consistent way. The effect of FUV irradiation on the chemistry is that molecules get photodissociated and the gas is heated up to several 1000 K, mostly by the photoelectric effect on small dust grains or UV pumping of H2 followed by collision de-excitation. The gas is cooled by molecular and atomic lines, thus indirectly the chemical composition also affects the thermal structure through the abundance of molecules and atoms. To find a self-consistent solution between heating and cooling, the code iteratively calculates the chemistry, thermal-balance and molecular/atomic excitation.

[ascl:1905.026] SEDPY: Modules for storing and operating on astronomical source spectral energy distribution

SEDPY performs a variety of tasks for astronomical spectral energy distributions. It can generate synthetic photometry through any filter, provides detailed modeling of extinction curves, and offers basic aperture photometry algorithms. SEDPY can also store and interpolate model SEDs, convolve absolute or apparent fluxes, and calculate rest-frame magnitudes.

[ascl:1905.025] Prospector: Stellar population inference from spectra and SEDs

Prospector conducts principled inference of stellar population properties from photometric and/or spectroscopic data. The code combine photometric and spectroscopic data rigorously using a flexible spectroscopic calibration model and infer high-dimensional stellar population properties using parameteric SFHs (with ensemble MCMC sampling). Prospector also constrains the linear combination of stellar population components that are present in a galaxy (e.g. non-parametric SFHs) using spectra and/or photometry, and fits individual stellar spectra using large interpolated grids.

[ascl:1905.024] SICON: Stokes Inversion based on COnvolutional Neural networks

SICON (Stokes Inversion based on COnvolutional Neural networks) provides a three-dimensional cube of thermodynamical and magnetic properties from the interpretation of two-dimensional maps of Stokes profiles by use of a convolutional neural network. In addition to being much faster than parallelized inversion codes, SICON, when trained on synthetic Stokes profiles from two numerical simulations of different structures of the solar atmosphere, also provided a three-dimensional view of the physical properties of the region of interest in geometrical height, and pressure and Wilson depression properties that are decontaminated from the blurring effect of instrumental point spread functions.

[ascl:1905.023] CASI-2D: Convolutional Approach to Shell Identification - 2D

CASI-2D (Convolutional Approach to Shell Identification) identifies stellar feedback signatures using data from magneto-hydrodynamic simulations of turbulent molecular clouds with embedded stellar sources and deep learning techniques. Specifically, a deep neural network is applied to dense regression and segmentation on simulated density and synthetic 12 CO observations to identify shells, sometimes referred to as "bubbles," and other structures of interest in molecular cloud data.

[ascl:1905.022] ClusterPyXT: Galaxy cluster pipeline for X-ray temperature maps

ClusterPyXT (Cluster Pypeline for X-ray Temperature maps) creates X-ray temperature maps, pressure maps, surface brightness maps, and density maps from X-ray observations of galaxy clusters to show turbulence, shock fronts, nonthermal phenomena, and the overall dynamics of cluster mergers. It requires CIAO (ascl:1311.006) and CALDB. The code analyzes archival data and provides capability for integrating additional observations into the analysis. The ClusterPyXT code is general enough to analyze data from other sources, such as galaxies, active galactic nuclei, and supernovae, though minor modifications may be necessary.

[ascl:1905.021] ODEPACK: Ordinary differential equation solver library

ODEPACK solves for the initial value problem for ordinary differential equation systems. It consists of nine solvers, a basic solver called LSODE and eight variants of it: LSODES, LSODA, LSODAR, LSODPK, LSODKR, LSODI, LSOIBT, and LSODIS. The collection is suitable for both stiff and nonstiff systems. It includes solvers for systems given in explicit form, dy/dt = f(t,y), and also solvers for systems given in linearly implicit form, A(t,y) dy/dt = g(t,y). The ODEPACK solvers are written in standard Fortran and there are separate double and single precision versions. Each solver consists of a main driver subroutine having the same name as the solver and some number of subordinate routines. For each solver, there is also a demonstration program, which solves one or two simple problems in a somewhat self-checking manner.

[ascl:1905.020] NAPLES: Numerical Analysis of PLanetary EncounterS

NAPLES (Numerical Analysis of PLanetary EncounterS) performs batch propagations of close encounters in the three-body problem and computes the numerical error with respect to reference trajectories computed in quadruple precision. It uses the LSODAR integrator from ODEPACK (ascl:1905.021) and the equations of motion correspond to several regularized formulations.

[ascl:1905.019] PICASO: Planetary Intensity Code for Atmospheric Scattering Observations

PICASO (Planetary Intensity Code for Atmospheric Scattering Observations), written in Python, computes the reflected light of exoplanets at any phase geometry using direct and diffuse scattering phase functions and Raman scattering spectral features.

[ascl:1905.018] THALASSA: Orbit propagator for near-Earth and cislunar space

THALASSA (Tool for High-Accuracy, Long-term Analyses for SSA) propagates orbits for bodies in the Earth-Moon-Sun system. Written in Fortran, it integrates either Newtonian equations in Cartesian coordinates or regularized equations of motion with the LSODAR (Livermore Solver for Ordinary Differential equations with Automatic Root-finding). THALASSA is a command-line tool; the repository also includes some Python3 scripts to perform batch propagations.

[ascl:1905.017] LensQuEst: CMB Lensing QUadratic Estimator

LensQuEst forecasts the signal-to-noise of CMB lensing estimators (standard, shear-only, magnification-only), generates mock maps, lenses them, and applies various lensing estimators to them. It can manipulate flat sky maps in various ways, including FFT, filtering, power spectrum, generating Gaussian random field, and applying lensing to a map, and evaluate these estimators on flat sky maps.

[ascl:1905.016] LensCNN: Gravitational lens detector

The LensCNN (Convolutional Neural Network) identifies images containing gravitational lensing systems after being trained and tested on simulated images, recovering most systems that are identifiable by eye.

[ascl:1905.015] rPICARD: Radboud PIpeline for the Calibration of high Angular Resolution Data

rPICARD (Radboud PIpeline for the Calibration of high Angular Resolution Data) reduces data from different VLBI arrays, including high-frequency and low-sensitivity arrays, and supports continuum, polarization, and phase-referencing observations. Built on the CASA (ascl:1107.013) framework, it uses CASA for CLEAN imaging and self-calibration, and can be run non-interactively after only a few non-default input parameters are set. rPICARD delivers high-quality calibrated data and large bandwidth data can be processed within reasonable computing times.

[ascl:1905.014] Bandmerge: Merge data from different wavebands

Bandmerge takes in ASCII tables of positions and fluxes of detected astronomical sources in 2-7 different wavebands, and write out a single table of the merged data. The tool was designed to work with source lists generated by the Spitzer Science Center's MOPEX (ascl:1111.006) software, although it can be "fooled" into running on other data as well.

[ascl:1905.013] SPARK: K-band Multi Object Spectrograph data reduction

SPARK (Software Package for Astronomical Reduction with KMOS), also called kmos-kit, reduces data from the K-band Multi Object Spectrograph (KMOS) for the VLT. In many cases, science data can be processed using a single recipe; alternately, all functions this recipe provides can be performed using other recipes provided as tools. Among the functions the recipes provide are sky subtraction, cube reconstruction with the application of flexure corrections, dividing out the telluric spectrum, applying an illumination correction, aligning the cubes, and then combinging them. The result is a set of files which contain the combined datacube and associated noise cube for each of the 24 integral field unit (IFUs). The pipeline includes simple error propagation.

[ascl:1905.012] Fitsverify: FITS file format-verification tool

Fitsverify rigorously checks whether a FITS (Flexible Image Transport System) data file conforms to the requirements defined in Version 3.0 of the FITS Standard document; it is a standalone version of the ftverify and fverify tasks that are distributed as part of the ftools (ascl:9912.002) software package. The source code must be compiled and linked with the CFITSIO (ascl:1010.001) library. An interactive web is also available that can verify the format of any FITS data file on a local computer or on the Web.

[ascl:1905.011] Fermitools: Fermi Science Tools

Fermi Science Tools is a suite of tools for the analysis of both the Large-Area Telescope (LAT) and the Gamma-ray Burst Monitor (GBM) data, including point source analysis for generating maps, spectra, and light curves, pulsar timing analysis, and source identification.

[ascl:1905.010] FastPM: Scaling N-body Particle Mesh solver

FastPM solves the gravity Possion equation with a boosted particle mesh. Arbitrary time steps can be used. The code is intended to study the formation of large scale structure and supports plain PM and Comoving-Lagranian (COLA) solvers. A broadband correction enforces the linear theory model growth factor at large scale. FastPM scales extremely well to hundred thousand MPI ranks, which is possible through the use of the PFFT Fourier Transform library. The size of mesh in FastPM can vary with time, allowing one to use coarse force mesh at high redshift with increase temporal resolution for accurate large scale modes. The code supports a variety of Greens function and differentiation kernels, though for most practical simulations the choice of kernels does not make a difference. A parameter file interpreter is provided to validate and execute the configuration files without running the simulation, allowing creative usages of the configuration files.

[ascl:1905.009] HAOS-DIPER: HAO Spectral Diagnostic Package For Emitted Radiation

HAOS-DIPER works with and manipulates data for neutral atoms and atomic ions to understand radiation emitted by some space plasmas, notably the solar atmosphere and stellar atmospheres. HAOS-DIPER works with quantum numbers for atomic levels, enabling it to perform tasks otherwise difficult or very tedious, including a variety of data checks, calculations based upon the atomic numbers, and searching and manipulating data based upon these quantum numbers. HAOS-DIPER handles conditions from LTE to coronal-like conditions, in a manner controlled by one system variable !REGIME, and has some capability for estimating data for which no accurate parameters are available and for accounting for the effects of missing atomic levels.

[ascl:1905.008] Q3C: A PostgreSQL package for spatial queries and cross-matches of large astronomical catalogs

Q3C (Quad Tree Cube) enables fast cone, ellipse and polygonal searches and cross-matches between large astronomical catalogs inside a PostgreSQL database. The package supports searches even if objects have proper motions.

[ascl:1905.007] Astrocut: Tools for creating cutouts of TESS images

The Transiting Exoplanet Survey Satellite (TESS) produces Full Frame Images (FFIs) at a half hour cadence and keeps the same pointing for ~27 days at a time. Astrocut performs the same cutout across all FFIs that share a common pointing to create a time series of images on a small portion of the sky.

The Astrocut package has two parts: the CubeFactory and the CutoutFactory. The CubeFactory class creates a large image cube from a list of FFI files, which allows the cutout operation to be performed efficiently. The CutoutFactory class performs the actual cutout and builds a target pixel file (TPF) that is compatible with TESS pipeline TPFs. Because this software operates on TESS mission-produced FFIs, the resulting TPFs are not background-subtracted. In addition to the Astrocut software itself, the Mikulski Archive for Space Telescopes (MAST) provides a cutout service, TESScut, which runs Astrocut on MAST servers, and allows users to simply request cutouts through a web form or direct HTTP API query.

[submitted] MiraPy: Python package for Deep Learning in Astronomy

MiraPy is a Python package for problem-solving in astronomy using Deep Learning for astrophysicist, researchers and students. Current applications of MiraPy are X-Ray Binary classification, ATLAS variable star feature classification, OGLE variable star light-curve classification, HTRU1 dataset classification and Astronomical image reconstruction using encoder-decoder network. It also contains modules for loading various datasets, curve-fitting, visualization and other utilities. It is built using Keras for developing ML models to run on CPU and GPU seamlessly.

[ascl:1905.006] beamModelTester: Model evaluation for fixed antenna phased array radio telescopes

beamModelTester enables evaluation of models of the variation in sensitivity and apparent polarization of fixed antenna phased array radio telescopes. The sensitivity of such instruments varies with respect to the orientation of the source to the antenna, resulting in variation in sensitivity over altitude and azimuth that is not consistent with respect to frequency due to other geometric effects. In addition, the different relative orientation of orthogonal pairs of linear antennae produces a difference in sensitivity between the antennae, leading to an artificial apparent polarization. Comparing the model with observations made using the given telescope makes it possible evaluate the model's performance; the results of this evaluation can provide a figure of merit for the model and guide improvements to it. This system also enables plotting of results from a single station observation on a variety of parameters.

[ascl:1905.005] MMIRS-DRP: MMIRS Data Reduction Pipeline

The MMIRS data reduction pipeline provides complete and flexible data reduction for long-slit and multi-slit spectroscopic observations collected using the MMT and Magellan Infrared Spectrograph (MMIRS). Written in IDL, it offers sky subtraction, correction for telluric absorpition, and is fast enough to permit real-time data reduction for quality control.

[ascl:1905.004] Binospec: Data reduction pipeline for the Binospec imaging spectrograph

Binospec reduces data for the Binospec imaging spectrograph. The software is also used for observation planning and instrument control, and is automated to decrease the number of tasks the user has to perform. Binospec uses a database-driven approach for instrument configuration and sequencing of observations to maximize efficiency, and a web-based interface is available for defining observations, monitoring status, and retrieving data products.

[ascl:1905.003] evolstate: Assign simple evolutionary states to stars

evolstate assigns crude evolutionary states (main-sequence, subgiant, red giant) to stars given an input temperature and radius/surface gravity, based on physically motivated boundaries from solar metallicity interior models.

[ascl:1905.002] Py4CAtS: PYthon for Computational ATmospheric Spectroscopy

Py4CAtS (PYthon scripts for Computational ATmospheric Spectroscopy) implements the individual steps of an infrared or microwave radiative transfer computation in separate scripts (and corresponding functions) to extract lines of relevant molecules in the spectral range of interest, compute line-by-line cross sections for given pressure(s) and temperature(s), combine cross sections to absorption coefficients and optical depths, and integrate along the line-of-sight to transmission and radiance/intensity. The code is a Python re-implementation of the Fortran code GARLIC (Generic Atmospheric Radiation Line-by-line Code) and uses the Numeric/Scientific Python modules for computationally-intensive highly optimized array-processing. Py4CAtS can be used in the console/terminal, inside the (I)Python interpreter, and in Jupyter notebooks.

[ascl:1905.001] Grizli: Grism redshift and line analysis software

Grizli produces quantitative and comprehensive modeling and fitting of slitless spectroscopic observations, which typically involve overlapping spectra of hundreds or thousands of objects in exposures taken with one or more separate grisms and at multiple dispersion position angles. This type of analysis provides complete and uniform characterization of the spectral properties (e.g., continuum shape, redshifts, line fluxes) of all objects in a given exposure taken in the slitless spectroscopic mode.

[ascl:1904.030] nudec_BSM: Neutrino Decoupling Beyond the Standard Model

nudec_BSM uses a simplified approach to solve for the neutrino decoupling, allowing one to capture the time dependence of the process while accounting for all possible interactions that can alter it.

[ascl:1904.029] JVarStar: Variable Star Analysis Library

JVarStar (Java Variable Star Analysis) performs pattern classification by analyzing variable star data. This all-in-one library package includes machine learning techniques, fundamental mathematical methods, and digital signal processing functions that can be externally referenced (i.e., from Python), or can be used for further Java development. This library has dependencies on several open source packages that, along with the developed functionality, provides a developer with an easily accessible library from which to construct stable variable star analysis and classification code.

[ascl:1904.028] covdisc: Disconnected covariance of 2-point functions in large-scale structure of the Universe

covdisc computes the disconnected part of the covariance matrix of 2-point functions in large-scale structure studies, accounting for the survey window effect. This method works for both power spectrum and correlation function, and applies to the covariances for various probes including the multi- poles and the wedges of 3D clustering, the angular and the projected statistics of clustering and lensing, as well as their cross covariances.

[ascl:1904.027] nbodykit: Massively parallel, large-scale structure toolkit

nbodykit provides algorithms for analyzing cosmological datasets from N-body simulations and large-scale structure surveys, and takes advantage of the abundance and availability of large-scale computing resources. The package provides a unified treatment of simulation and observational datasets by insulating algorithms from data containers, and reduces wall-clock time by scaling to thousands of cores. All algorithms are parallel and run with Message Passing Interface (MPI); the code is designed to be deployed on large super-computing facilities. nbodykit offers an interactive user interface that performs as well in a Jupyter notebook as on super-computing machines.

[ascl:1904.026] pyRSD: Accurate predictions for the clustering of galaxies in redshift-space in Python

pyRSD computes the theoretical predictions of the redshift-space power spectrum of galaxies. It also includes functionality for fitting data measurements and finding the optimal model parameters, using both MCMC and nonlinear optimization techniques.

[ascl:1904.025] Properimage: Image coaddition and subtraction

Properimage processes astronomical image; it is specially written for coaddition and image subtraction. It performs the statistical proper-coadd of several images using a spatially variant PSF estimation, and also difference image analysis by several strategies developed by others. Most of the code is based on a class called SingleImage, which provides methods and properties for image processing such as PSF determination.

[ascl:1904.024] OoT: Out-of-Transit Light Curve Generator

OoT (Out-of-Transit) calculates the light curves and radial velocity signals due to a planet orbiting a star. It explicitly models the effects of tides, orbital motion. relativistic beaming, and reflection of the stars light by the planet. The code can also be used to model secondary eclipses.

[ascl:1904.023] digest2: NEO binary classifier

digest2 classifies Near-Earth Object (NEO) candidates by providing a score, D2, that represents a pseudo-probability that a tracklet belongs to a given solar system orbit type. The code accurately and precisely distinguishes NEOs from non-NEOs, thus helping to identify those to be prioritized for follow-up observation. This fast, short-arc orbit classifier for small solar system bodies code is built upon the Pangloss code developed by Robert McNaught and further developed by Carl Hergenrother and Tim Spahr and Robert Jedicke's 223.f code.

[ascl:1904.022] eleanor: Extracted and systematics-corrected light curves for TESS-observed stars

eleanor extracts target pixel files from TESS Full Frame Images and produces systematics-corrected light curves for any star observed by the TESS mission. eleanor takes a TIC ID, a Gaia source ID, or (RA, Dec) coordinates of a star observed by TESS and returns, as a single object, a light curve and accompanying target pixel data. The process can be customized, allowing, for example, examination of intermediate data products and changing the aperture used for light curve extraction. eleanor also offers tools that make it easier to work with stars observed in multiple TESS sectors.

[ascl:1904.021] TP2VIS: Total Power Map to Visibilities

TP2VIS creates visibilities from a single dish cube; the TP visibilities can be combined with the interferometric visibilities in a joint deconvolution using, for example, CASA's tclean() method. TP2VIS requires CASA 5.4 (ascl:1107.013) or above.

[ascl:1904.020] SARAH: SUSY and non-SUSY model builder and analyzer

SARAH builds and analyzes SUSY and non-SUSY models. It calculates all vertices, mass matrices, tadpoles equations, one-loop corrections for tadpoles and self-energies, and two-loop RGEs for a given model. SARAH writes model files for a variety of other software packages for dark matter studies, includes many SUSY and non-SUSY models, and makes implementing new models efficient and straightforward. Written in Mathematica, SARAH can also use output from Vevacious (ascl:1904.019) to check for the global minimum for a given model and parameter point.

[ascl:1904.019] Vevacious: Global minima of one-loop effective potentials generator

Vevacious takes a generic expression for a one-loop effective potential energy function and finds all the tree-level extrema, which are then used as the starting points for gradient-based minimization of the one-loop effective potential. The tunneling time from a given input vacuum to the deepest minimum, if different from the input vacuum, can be calculated. The parameter points are given as files in the SLHA format (though is not restricted to supersymmetric models), and new model files can be easily generated automatically by the Mathematica package SARAH (ascl:1904.020).

[ascl:1904.018] Specstack: A simple spectral stacking tool

Specstack creates stacked spectra using a simple algorithm with sigma-clipping to combine the spectra of galaxies in the rest-frame into a single averaged spectrum. Though written originally for galaxy spectra, it also works for other types of objects. It is written in Python and is started from the command-line.

[ascl:1904.017] dfitspy: A dfits/fitsort implementation in Python

dfitspy searches and displays metadata contained in FITS files. Written in Python, it displays the results of a metadata search and is able to grep certain values of keywords inside large samples of files in the terminal. dfitspy can be used directly with the command line interface and can also be imported as a python module into other python code or the python interpreter.

[ascl:1904.016] simuTrans: Gravity-darkened exoplanet transit simulator

simuTrans models transit light curves affected by gravity-darkened stars. The code defines a star on a grid by modeling the brightness of each point as blackbody emission, then sets a series of parameters and uses emcee (ascl:1303.002) to explore the posterior probability distribution for the remaining fitted parameters and determine their best-fit values.

[ascl:1904.015] SBGAT: Small Bodies Geophysical Analysis Tool

SBGAT (Small Body Geophysical Analysis Tool) generates simulated data originating from small bodies shape models, combined with advanced shape-modification properties. It uses polyhedral shape models from which can be computed mass properties such as volume, center of mass, and inertia, synthetic observations such as lightcurves and radar, and which can be used within dynamical models, such as spherical harmonics and polyhedron gravity modeling. SBGAT can generate spherical harmonics expansions from constant-density polyhedra (and export them to JSON) and evaluate the spherical harmonics expansions. It can also generate YORP coefficients, multi-threaded Polyhedron Gravity Model gravity and potential evaluations, and synthetic light-curve and radar observations for single/primary asteroids.

SBGAT has two distinct packages: a dynamic library SBGAT Core that contains the data structure and algorithm backbone of SBGAT, and SBGAT Gui, which wraps the former inside a VTK, Qt user interface to facilitate user/data interaction. SBGAT Core can be used without the SBGAT Gui wrapper.

[ascl:1904.014] rate: Reliable Analytic Thermochemical Equilibrium

rate computes thermochemical-equilibrium abundances for a H-C-N-O system with known pressure, temperature, and elemental abundances. The output abundances are H2O, CH4, CO, CO2, NH3, C2H2, C2H4, HCN, and N2, H2, H, and He.

[ascl:1904.013] EightBitTransit: Calculate light curves from pixel grids

EightBitTransit calculates the light curve of any pixelated image transiting a star and inverts a light curve to recover the "shadow image" that produced it.

[ascl:1904.012] CausticFrog: 1D Lagrangian Simulation Package

CausticFrog models the reaction of a system of orbiting particles to instantaneous mass loss. It applies to any spherically symmetric potential, and follows the radial evolution of shells of mass. CausticFrog tracks the inner and outer edge of each shell, whose radius evolves as a test particle. The amount of mass in each shell is fixed but multiple shells can overlap leading to higher densities.

[ascl:1904.011] FortesFit: Flexible spectral energy distribution modelling with a Bayesian backbone

FortesFit efficiently explores and discriminates between various spectral energy distributions (SED) models of astronomical sources. The Python package adds Bayesian inference to a framework that is designed for the easy incorporation and relative assessment of SED models, various fitting engines, and a powerful treatment of priors, especially those that may arise from non-traditional wave-bands such as the X-ray or radio emission, or from spectroscopic measurements. It has been designed with particular emphasis for its scalability to large datasets and surveys.

[ascl:1904.010] CLEAR: CANDELS Ly-alpha Emission at Reionization processing pipeline and library

The CLEAR pipeline and library performs various tasks for the CANDELS Ly-alpha Emission at Reionization (CLEAR) experiment of deep Hubble grism observations of high-z galaxies. It interlaces images, models contamination of overlapping grism spectra, extracts source spectra, stacks the extracted source spectra, and estimates fits for sources redshifts and emission lines.

[ascl:1904.009] deproject: Deprojection of two-dimensional annular X-ray spectra

Deproject extends Sherpa (ascl:1107.005) to facilitate deprojection of two-dimensional annular X-ray spectra to recover the three-dimensional source properties. For typical thermal models, this includes the radial temperature and density profiles. This basic method is used for X-ray cluster analysis and is the basis for the XSPEC (ascl:9910.005) model project. The deproject module is written in Python and is straightforward to use and understand. The basic physical assumption of deproject is that the extended source emissivity is constant and optically thin within spherical shells whose radii correspond to the annuli used to extract the specta. Given this assumption, one constructs a model for each annular spectrum that is a linear volume-weighted combination of shell models.

[ascl:1904.008] repack: Repack and compress line-transition data

repack re-packs and compresses line-transition data for radiative-transfer calculations. It identifies the strong lines that dominate the spectrum from the large-majority of weaker lines, returning a binary line-by-line (LBL) file with the strong lines info (wavenumber, Elow, gf, and isotope ID), and an ASCII file with the combined contribution of the weaker lines compressed into a continuum extinction coefficient (in cm-1 amagat-1) as function of wavenumber and temperature.

[ascl:1904.007] AutoBayes: Automatic design of customized analysis algorithms and programs

AutoBayes automatically generates customized algorithms from compact, declarative specifications in the data analysis domain, taking a statistical model as input and creating documented and optimized C/C++ code. The synthesis process uses Bayesian networks to enable problem decompositions and guide the algorithm derivation. Program schemas encapsulate advanced algorithms and data structures, and a symbolic-algebraic system finds closed-form solutions for problems and emerging subproblems. AutoBayes has been used to analyze planetary nebulae images taken by the Hubble Space Telescope, and can be applied to other scientific data analysis tasks.

[ascl:1904.006] CDAWeb: Coordinated Data Analysis Web

CDAWeb (Coordinated Data Analysis Workshop Web) enables viewing essentially any data produced in Common Data Format/CDF with the ISTP/IACG Guidelines and supports interactive plotting of variables from multiple instruments on multiple investigations simultaneously on arbitrary, user-defined time-scales. It also supports data retrieval in both CDF or ASCII format. NASA's GSFC Space Physics Data Facility maintains a publicly available database that includes approximately 600 data variables from Geotail, Wind, Interball, Polar, SOHO, ancilliary spacecraft and ground-based investigations. CDAWeb includes high resolution digital data products that support event correlative science. The system combines the client-server user interface technology of the Web with a powerful set of customized routines based in the COTS Interactive Data Language (IDL) package to leverage the data format standards.

[ascl:1904.005] SMILI: Sparse Modeling Imaging Library for Interferometry

SMILI uses sparse sampling techniques and other regularization methods for interferometric imaging. The python-interfaced library is mainly designed for very long baseline interferometry, and has been under the active development primarily for the Event Horizon Telescope (EHT).

[ascl:1904.004] ehtim: Imaging, analysis, and simulation software for radio interferometry

ehtim (eht-imaging) simulates and manipulates VLBI data and produces images with regularized maximum likelihood methods. The package contains several primary classes for loading, simulating, and manipulating VLBI data. The main classes are the Image, Array, Obsdata, Imager, and Caltable classes, which provide tools for loading images and data, producing simulated data from realistic u-v tracks, calibrating, inspecting, and plotting data, and producing images from data sets in various polarizations using various data terms and regularizers.

[ascl:1904.003] CGS: Collisionless Galactic Simulator

CGS (Collisionless Galactic Simulator) uses Fourier techniques to solve the Possion equation ∇2Φ = 4πGρ, relating the mean potential Φ of a system to the mass density ρ. The angular dependence of the force is treated exactly in terms of the single-particle Legendre polynomials, which preserves accuracy and avoids systematic errors. The density is assigned to a radial grid by means of a cloud-in-cell scheme with a linear kernel, i.e., a particle contributes to the density of the two closest cells with a weight depending linearly on the distance from the center of the cell considered. The same kernel is then used to assign the force from the grid to the particle. The time step is chosen adaptively in such a way that particles are not allowed to cross more than one radial cell during one step. CGS is based on van Albada's code (1982) and is distributed in the NEMO (ascl:1010.051) Stellar Dynamics Toolbox.

[ascl:1904.002] GALAXY: N-body simulation software for isolated, collisionless stellar systems

GALAXY evolves (almost) isolated, collisionless stellar systems, both disk-like and ellipsoidal. In addition to the N-body code galaxy, which offers eleven different methods to compute the gravitational accelerations, the package also includes sophisticated set-up and analysis software. While not as versatile as tree codes, for certain restricted applications the particle-mesh methods in GALAXY are 50 to 200 times faster than a widely-used tree code. After reading in data providing the initial positions, velocities, and (optionally) masses of the particles, GALAXY compute the gravitational accelerations acting on each particle and integrates forward the velocities and positions of the particles for a short time step, repeating these two steps as desired. Intermediate results can be saved, as can the final moment in a state from which the integration could be resumed. Particles can have individual masses and their motion can be integrated using a range of time steps for greater efficiency; message-passing-interface (MPI) calls are available to enable GALAXY's use on parallel machines with high efficiency.

[ascl:1904.001] sxrbg: ROSAT X-Ray Background Tool

The ROSAT X-Ray Background Tool (sxrbg) calculates the average X-ray background count rate and statistical uncertainty in each of the six standard bands of the ROSAT All-Sky Survey (RASS) diffuse background maps (R1, R2, R4, R5, R6, R7) for a specified astronomical position and a search region consisting of either a circle with a specified radius or an annulus with specified inner and outer radii centered on the position. The values returned by the tool are in units of 10^-6 counts/second/arcminute^2. sxrbg can also create a count-rate-based spectrum file which can be used with XSpec (ascl:9910.005) to calculate fluxes and offers support for counts statistics (cstat), an alternative method for generating a background spectrum. HEASoft (ascl:1408.004) is a prerequisite for building. The code is in the public domain.

[ascl:1903.017] HelioPy: Heliospheric and planetary physics library

HelioPy provides a set of tools to download and read in data, and carry out other common data processing tasks for heliospheric and planetary physics. It handles a wide variety of solar and satellite data and builds upon the SpiceyPy package (ascl:1903.016) to provide an accessible interface for performing orbital calculations. It has also implemented a framework to perform transformations between some common coordinate systems.

[ascl:1903.016] SpiceyPy: Python wrapper for the NAIF C SPICE Toolkit

SpiceyPy is a Python wrapper for the NAIF C SPICE Toolkit (ascl:1903.015). It is compatible with Python 2 and 3, and was written using ctypes.

[ascl:1903.015] SPICE: Observation Geometry System for Space Science Missions

The SPICE (Spacecraft Planet Instrument C-matrix [“Camera matrix”] Events) toolkit offers a set of building blocks for constructing tools supporting multi-mission, international space exploration programs and research in planetary science, heliophysics, Earth science, and for observations from terrestrial observatories. It computes many kinds of observation geometry parameters, including the ephemerides, orientations, sizes, and shapes of planets, satellites, comets and asteroids. It can also compute the orientation of a spacecraft, its various moving structures, and an instrument's field-of-view location on a planet's surface or atmosphere. It can determine when a specified geometric event occurs, such as when an object is in shadow or is in transit across another object. The SPICE toolkit is available in FORTRAN 77, ANSI C, IDL, and MATLAB.

[ascl:1903.014] PLATON: PLanetary Atmospheric Transmission for Observer Noobs

PLATON (PLanetary Atmospheric Transmission for Observer Noobs) calculates transmission spectra for exoplanets and retrieves atmospheric characteristics based on observed spectra; it is based on ExoTransmit (ascl:1611.005). PLATON supports the most common atmospheric parameters, such as temperature, metallicity, C/O ratio, cloud-top pressure, and scattering slope. It also has less commonly included features, such as a Mie scattering cloud model and unocculted starspot corrections.

[ascl:1903.013] NFWdist: Density, distribution function, quantile function and random generation for the 3D NFW profile

Available in R and Python, the simple analytic scheme NFWdist performs highly efficient and exact sampling of the Navarro, Frenk & White (NFW) profile as a true probability distribution function, with the only variable being the concentration.

[ascl:1903.012] DAVE: Discovery And Vetting of K2 Exoplanets

DAVE implements a pipeline to find and vet planets planets using data from NASA's K2 mission. The pipeline contains several modules tailored to particular aspects of the vetting procedures, using photocenter analysis to rule out background eclipsing binaries and flux time-series analysis to rule out odd–even differences, secondary eclipses, low-S/N events, variability other than a transit, and size of the transiting object.

[ascl:1903.011] AsPy: Aspherical fluctuations on the spherical collapse background

AsPy computes the determinants of aspherical fluctuations on the spherical collapse background. Written in Python, this procedure includes analytic factorization and cancellation of the so-called `IR-divergences'—spurious enhanced contributions that appear in the dipole sector and are associated with large bulk flows.

[ascl:1903.010] GalIMF: Galaxy-wide Initial Mass Function

GalIMF (Galaxy-wide Initial Mass Function) computes the galaxy-wide initial stellar mass function by integrating over a whole galaxy, parameterized by star formation rate and metallicity. The generated stellar mass distribution depends on the galaxy-wide star formation rate (SFR, which is related to the total mass of a galalxy) and the galaxy-wide metallicity. The code can generate a galaxy-wide IMF (IGIMF) and can also generate all the stellar masses within a galaxy with optimal sampling (OSGIMF). To compute the IGIMF or the OSGIMF, the GalIMF module contains all local IMF properties (e.g. the dependence of the stellar IMF on the metallicity, on the density of the star-cluster forming molecular cloud cores), and this software module can, therefore, be also used to obtain only the stellar IMF with various prescriptions, or to investigate other features of the stellar population such as what is the most massive star that can be formed in a star cluster.

[ascl:1903.009] PRF: Probabilistic Random Forest

PRF (Probabilistic Random Forest) is a machine learning algorithm for noisy datasets. The PRF is a modification of the long-established Random Forest (RF) algorithm, and takes into account uncertainties in the measurements (i.e., features) as well as in the assigned classes (i.e., labels). To do so, the Probabilistic Random Forest (PRF) algorithm treats the features and labels as probability distribution functions, rather than as deterministic quantities.

[ascl:1903.008] NIFTy5: Numerical Information Field Theory v5

NIFTy (Numerical Information Field Theory) facilitates the construction of Bayesian field reconstruction algorithms for fields being defined over multidimensional domains. A NIFTy algorithm can be developed for 1D field inference and then be used in 2D or 3D, on the sphere, or on product spaces thereof. NIFTy5 is a complete redesign of the previous framework (ascl:1302.013), and requires only the specification of a probabilistic generative model for all involved fields and the data in order to be able to recover the former from the latter. This is achieved via Metric Gaussian Variational Inference, which also provides posterior samples for all unknown quantities jointly.

[ascl:1903.007] ICSF: Intensity Conserving Spectral Fitting

ICSF (Intensity Conserving Spectral Fitting) "corrects" (x,y) data in which the ordinate represents the average of a quantity over a finite interval in the abscissa. A typical example is spectral data, where the average intensity over a wavelength bin (the measured quantity) is assigned to the center of the bin. If the profile is curved, the average will be different from the discrete value at the bin center location. ICSF, written in IDL and available separately and as part of SolarSoft (ascl:1208.013), corrects the intensity using an iterative procedure and cubic spline. The corrected intensity equals the "true" intensity at bin center, rather than the average over the bin. Unlike other methods that are restricted to a single fitting function, typically a spline, ICSF can be used with any function, such as a cubic spline or a Gaussian, with slight changes to the code.

[ascl:1903.006] SimSpin: Kinematic analysis of galaxy simulations

The R-package SimSpin measures the kinematics of a galaxy simulation as if it had been observed using an IFU. The functions included in the package can produce a kinematic data cube and measure the "observables" from this data cube, specifically the observable spin parameter λr. This package, once installed, is fully documented and tested.

[ascl:1903.005] Galmag: Computation of realistic galactic magnetic fields

Galmag computes galactic magnetic fields based on mean field dynamo theory. Written in Python, Galmag allows quick exploration of solutions to the mean field dynamo equation based on galaxy parameters specified by the user, such as the scale height profile and the galaxy rotation curves. The magnetic fields are solenoidal by construction and can be helical.

[ascl:1903.004] brutifus: Python module to post-process datacubes from integral field spectrographs

brutifus aids in post-processing datacubes from integral field spectrographs. The set of Python routines in the package handle generic tasks, such as the registration of a datacube WCS solution with the Gaia catalogue, the correction of Galactic reddening, or the subtraction of the nebular/stellar continuum on a spaxel-per-spaxel basis, with as little user interactions as possible. brutifus is modular, in that the order in which the post-processing routines are run is entirely customizable.

[ascl:1903.003] allesfitter: Flexible star and exoplanet inference from photometry and radial velocity

allesfitter provides flexible and robust inference of stars and exoplanets given photometric and radial velocity (RV) data. The software offers a rich selection of orbital and transit models, accommodating multiple exoplanets, multi-star systems, star spots, stellar flares, and various noise models. It features both parameter estimation and model selection. A graphical user interface is used to specify input parameters, and to easily run a nested sampling or Markov Chain Monte Carlo (MCMC) fit, producing publication-ready tables, LaTex code, and plots. allesfitter provides an inference framework that unites the versatile packages ellc (ascl:1603.016), aflare (flare model; Davenport et al. 2014), dynesty (ascl:1809.013), emcee (ascl:1303.002) and celerite (ascl:1709.008).

[ascl:1903.002] SIXTE: Simulation of X-ray Telescopes

SIXTE simulates X-Ray telescope observation; the software performs instrument performance analyses and produces simulated event files for mission and analysis studies. SIXTE strives to find a compromise between exactness of the simulation and speed. Using calibration files such as the PSF, RMF and ARF makes efficient simulations possible at comparably high speed, even though they include nonlinear effects such as pileup. Setups for some current and future missions, such as XMM-Newton and Athena, are included in the package; others can be added by the user with relatively little effort through specifying the main instrument characteristics in a flexible, human-readable XML-based format. Properties of X-ray sources to be simulated are described in a detector-independent format, i.e., the same input can be used for simulating observations with all available instruments, and the same input can also be used for simulations with the SIMX simulator. The input files are easily generated from standard data such as XSPEC (ascl:9910.005) spectral models or FITS images with tools provided with the SIXTE distribution. The input data scale well from single point sources up to very complicated setups.

[ascl:1902.012] Specutils: Spectroscopic analysis and reduction

Specutils provides a basic interface for the loading, manipulation, and common forms of analysis of spectroscopic data. Its generic data containers and accompanying modules can be used to build a particular scientific workflow or higher-level analysis tool. It is an AstroPy (ascl:1304.002) affiliated package, and SpecViz (ascl:1902.011), which is built on top of Specutils, provides a visual, interactive interface to its analysis capabilities.

[ascl:1902.011] SpecViz: 1D Spectral Visualization Tool

SpecViz interactively visualizes and analyzes 1D astronomical spectra. It reads data from FITS and ASCII tables and allows spectra to be easily plotted and examined. It supports instrument-specific data quality handling, flexible spectral units conversions, custom plotting attributes, plot annotations, tiled plots, among other features. SpecViz includes a measurement tool for spectral lines for performing and recording measurements and a model fitting capability for creating simple (e.g., single Gaussian) or multi-component models (e.g., multiple Gaussians for emission and absorption lines in addition to regions of flat continua). SpecViz is built on top of the Specutils (ascl:1902.012) Astropy-affiliated python library, providing a visual, interactive interface to the analysis capabilities in that library.

The functionality of SpecViz is now actively developed as part of Jdaviz (ascl:2307.001).

[ascl:1902.010] dyPolyChord: Super fast dynamic nested sampling with PolyChord

dyPolyChord implements dynamic nested sampling using the efficient PolyChord (ascl:1502.011) sampler to provide state-of-the-art nested sampling performance. Any likelihoods and priors which work with PolyChord can be used (Python, C++ or Fortran), and the output files produced are in the PolyChord format.

[ascl:1902.009] ExPRES: Exoplanetary and Planetary Radio Emissions Simulator

ExPRES (Exoplanetary and Planetary Radio Emission Simulator) reproduces the occurrence of CMI-generated radio emissions from planetary magnetospheres, exoplanets or star-planet interacting systems in time-frequency plane, with special attention given to computation of the radio emission beaming at and near its source. Physical information drawn from such radio observations may include the location and dynamics of the radio sources, the type of current system leading to electron acceleration and their energy and, for exoplanetary systems, the magnetic field strength, the orbital period of the emitting body and the rotation period, tilt and offset of the planetary magnetic field. Most of these parameters can be remotely measured only via radio observations. ExPRES code provides the proper framework of analysis and interpretation for past (Cassini, Voyager, Galileo), current (Juno, ground-based radio telescopes) and future (BepiColombo, Juice) observations of planetary radio emissions, as well as for future detection of radio emissions from exoplanetary systems.

[ascl:1902.008] Radynversion: Solar atmospheric properties during a solar flare

Radynversion infers solar atmospheric properties during a solar flare. The code is based on an Invertible Neural Network (INN) that is trained to learn an approximate bijective mapping between the atmospheric properties of electron density, temperature, and bulk velocity (all as a function of altitude), and the observed Hα and Ca II λ8542 line profiles. As information is lost in the forward process of radiation transfer, this information is injected back into the model during the inverse process by means of a latent space; the training allows this latent space to be filled using an n-dimensional unit Gaussian distribution, where n is the dimensionality of the latent space. The code is based on a model trained by simulations made by RADYN, a 1D non-equilibrium radiation hydrodynamic model with good optically thick radiation treatment that does not consider magnetic effects.

[submitted] BELLAMY: A cross-matching package for the cynical astronomer

BELLAMY is a cross-matching algorithm designed primarily for radio images, that aims to match all sources in the supplied target catalogue to sources in a reference catalogue by calculating the probability of a match. BELLAMY utilises not only the position of a source on the sky, but also the flux data to calculate this probability, determining the most probable match in the reference catalog to the target source. Additionally, BELLAMY attempts to undo any spatial distortion that may be affecting the target catalogue, by creating a model of the offsets of matched sources which is then applied to unmatched sources. This combines to produce an iterative cross-matching algorithm that provides the user with an obvious measure of how confident they should be with the results of a cross-match.

[ascl:1902.007] PINT: High-precision pulsar timing analysis package

PINT (PINT Is Not Tempo3) analyzes high-precision pulsar timing data, enabling interactive data analysis and providing an extensible and flexible development platform for timing applications. PINT utilizes well-debugged public Python packages and modern software development practices (e.g., the NumPy and Astropy libraries, version control and development with git and GitHub, and various types of testing) for increased development efficiency and enhanced stability. PINT has been developed and implemented completely independently from traditional pulsar timing software such as TEMPO (ascl:1509.002) and Tempo2 (ascl:1210.015) and is a robust tool for cross-checking timing analyses and simulating data.

[ascl:1902.006] RPFITS: Routines for reading and writing RPFITS files

The RPFITS data file format records synthesis visibility data obtained from the Australia Telescope Compact Array (ATCA) at Narrabri, NSW. It is also used for single-dish spectral line data obtained from Parkes and Mopra, including Parkes multibeam data. RPFITS superficially resembles random group FITS, but differs in important respects, making it incompatible with standard FITS software such as FITSIO (ascl:1010.001) and FTOOLS (ascl:9912.002) and, in particular, it precludes the use of fv (ascl:1205.005). The RPFITS Fortran library contains routines for reading and writing RPFITS files. A header file, RPFITS.h, is provided to facilitate usage by C and C++ applications. Also included is rpfhdr, a utility for viewing RPFITS headers (it also works for standard FITS), and rpfex for extracting selected scans from an RPFITS file.

[ascl:1902.005] LiveData: Data reduction pipeline

LiveData is a multibeam single-dish data reduction system for bandpass calibration and gridding. It is used for processing Parkes multibeam and Mopra data.

[ascl:1902.004] GraviDy: Gravitational Dynamics

GraviDy performs N-body 3D visualizations; it is a GPU, direct-summation N-body integrator based on the Hermite scheme and includes relativistic corrections for sources of gravitational radiation. The software is modular, allowing users to readily introduce new physics, and exploits available computational resources. The software can be used in parallel on multiple CPUs and GPUs, with a considerable speed-up benefit. The single-GPU version is between one and two orders of magnitude faster than the single-CPU version.

[ascl:1902.003] PyMF: Matched filtering techniques for astronomical images

PyMF performs spatial filtering (matched filter, matched multifilter, constrained matched filter and constrained matched mutifilter) image processing that provides optimal reduction of the contamination introduced by sources that can be approximated by templates. These techniques use the flat-sky approximation.

[ascl:1902.002] LPNN: Limited Post-Newtonian N-body code for collisionless self-gravitating systems

The Limited Post-Newtonian N-body code (LPNN) simulates post-Newtonian interactions between a massive object and many low-mass objects. The interaction between one massive object and low-mass objects is calculated by post-Newtonian approximation, and the interaction between low-mass objects is calculated by Newtonian gravity. This code is based on the sticky9 code, and can be accelerated with the use of GPU in a CUDA (version 4.2 or earlier) environment.

[ascl:1902.001] SNTD: Supernova Time Delays

Supernova Time Delays (SNTD) simulates and measures time delay of multiply-imaged supernovae, and offers an improved characterization of the uncertainty caused by microlensing. Lensing time delays can be determined by fitting the multiple light curves of these objects; measuring these delays provide precise tests of lens models or constraints on the Hubble constant and other cosmological parameters that are independent of the local distance ladder. Fitting the effects of microlensing without an accurate prior often leads to biases in the time delay measurement and over-fitting to the data; this can be mitigated by using a Gaussian Process Regression (GPR) technique to determine the uncertainty due to microlensing. SNTD can produce accurate simulations for wide-field time domain surveys such as LSST and WFIRST.

[ascl:1901.012] stellarWakes: Dark matter subhalo searches using stellar kinematic data

stellarWakes uses stellar kinematic data to search for dark matter (DM) subhalos through their gravitational perturbations to the stellar phase-space distribution.

[ascl:1901.011] Bilby: Bayesian inference library

Bilby provides a user-friendly interface to perform parameter estimation. It is primarily designed and built for inference of compact binary coalescence events in interferometric data, such as analysis of compact binary mergers and other types of signal model including supernovae and the remnants of binary neutron star mergers, but it can also be used for more general problems. The software is flexible, allowing the user to change the signal model, implement new likelihood functions, and add new detectors. Bilby can also be used to do population studies using hierarchical Bayesian modelling.

[ascl:1901.010] eddy: Extracting Disk DYnamics

The Python suite eddy recovers precise rotation profiles of protoplanetary disks from Doppler shifted line emission, providing an easy way to fit first moment maps and the inference of a rotation velocity from an annulus of spectra.

[ascl:1901.009] bettermoments: Line-of-sight velocity calculation

bettermoments measures precise line-of-sight velocities from Doppler shifted lines to determine small scale deviations indicative of, for example, embedded planets.

[ascl:1901.008] SEDobs: Observational spectral energy distribution simulation

SEDobs uses state-of-the-art theoretical galaxy SEDs (spectral energy distributions) to create simulated observations of distant galaxies. It used BC03 and M05 theoretical models and allows the user to configure the simulated observation that are needed. For a given simulated galaxy, the user is able to simulate multi-spectral and multi-photometric observations.

[ascl:1901.007] Photon: Python tool for data plotting

Photon makes simple 1D plots in python. It uses mainly matplotlib and PyQt5 and has been build to be fully customizable, allowing the user to change the fontstyle, fontsize, fontcolors, linewidth of the axes, thickness, and other parameters, and see the changes directly in the plot. Once a customization is created, it can be saved in a configuration file and reloaded for future use, allowing reuse of the customization for other plots. The main tool is a graphical user interface and it is started using a command line interface.

[ascl:1901.006] ssos: Solar system objects detection pipeline

The ssos pipeline detects and identifies known and unknown Solar System Objects (SSOs) in astronomical images. ssos requires at least 3 images with overlapping field-of-views in the sky taken within a reasonable amount of time (e.g., 2 hours, 1 night). SSOs are detected mainly by judging the apparent motion of all sources in the images. The pipeline serves as a wrapper for the SExtractor (ascl:1010.064) and SCAMP (ascl:1010.063) software suites and allows different source extraction strategies to be chosen. All sources in the images are subject to a highly configurable filter pipeline. ssos is a versatile, light-weight, and easy-to-use software for surveys or PI-observation campaigns lacking a dedicated SSO detection pipeline.

[ascl:1901.005] Galaxia_wrap: Galaxia wrapper for generating mock stellar surveys

Galaxia_wrap is a python wrap around the popular Galaxia tool (ascl:1101.007) for generating mock stellar surveys, such as a magnitude limited survey, using a built-in Galaxy model or directly from n-body data. It also offers n-body functionality and has been used to infer the age distribution of a specific stellar tracer population.

[ascl:1901.004] unwise_psf: PSF models for unWISE coadds

The unwise_psf Python module renders point spread function (PSF) models appropriate for use in modeling of unWISE coadd images. unwise_psf translates highly detailed single-exposure WISE PSF models in detector coordinates to the corresponding pixelized PSF models in coadd space, accounting for subtleties including the WISE scan direction and its considerable variation near the ecliptic poles. Applications of the unwise_psf module include performing forced photometry on unWISE coadds, constructing WISE-selected source catalogs based on unWISE coadds and masking unWISE coadd regions contaminated by bright stars.

[ascl:1901.003] CCL: Core Cosmology Library

The Core Cosmology Library (CCL) computes basic cosmological observables and provides predictions for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias and the halo mass function through state-of-the-art modeling prescriptions. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. Predictions for correlation functions of galaxy clustering, galaxy-galaxy lensing and cosmic shear are within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is written in C and has a python interface.

[ascl:1901.002] OCFit: Python package for fitting of O-C diagrams

OCFit fits and analyzes O-C diagrams using Genetic Algorithms and Markov chain Monte Carlo methods. The MC method is used to determine a very good estimation of errors of the parameters. Unlike some other fitting routines, OCFit does not need any initial values of fitted parameters. An intuitive graphic user interface is provided for ease of fitting, and nine common models of periodic O-C changes are included.

[ascl:1901.001] cFE: Core Flight Executive

The Core Flight Executive is a portable, platform-independent embedded system framework that is the basis for flight software for satellite data systems and instruments; cFE can be used on other embedded systems as well. The Core Flight Executive is written in C and depends on the software library Operating System Abstraction Layer (OSAL), which is available at https://sourceforge.net/projects/osal/.

[ascl:1812.018] OctApps: Octave functions for continuous gravitational-wave data analysis

The OctApps library provides various functions, written in Octave, for performing searches for the weak signatures of continuous gravitational waves from rapidly-rotating neutron stars amidst the instrumental noise of the LIGO and Virgo detectors.

[ascl:1812.017] psrqpy: Python module to query the ATNF Pulsar Catalogue

psrqpy directly queries the Australia Telescope National Facility (ATNF) Pulsar Catalogue by downloading and parsing the full catalog database, which is cached and can be reused. The module assists astronomers who want access to the latest pulsar information via a script rather than through the standard web interface.

[ascl:1812.016] Juliet: Transiting and non-transiting exoplanetary systems modelling tool

Juliet essentially serves as a wrapper of other tools, including Batman (ascl:1510.002), George (ascl:1511.015), Dynesty (ascl:1809.013) and AstroPy (ascl:1304.002), to analyze and model transits, radial-velocities, or both from multiple instruments at the same time. Using nested sampling algorithms, it performs a thorough sampling of the parameter space and a model comparison via Bayesian evidences. Juliet also fits transiting and non-transiting multi-planetary systems, and Gaussian Processes (GPs) which might share hyperparameters between the photometry and radial-velocities simultaneously (e.g., stellar rotation periods).

[ascl:1812.015] AUTOSPEC: Automated Spectral Extraction Software for integral field unit data cubes

AUTOSPEC provides fast, automated extraction of high quality 1D spectra from astronomical datacubes with minimal user effort. AutoSpec takes an integral field unit (IFU) datacube and a simple parameter file in order to extract a 1D spectra for each object in a supplied catalogue. A custom designed cross-correlation algorithm improves signal to noise as well as isolates sources from neighboring contaminants.

[submitted] UMIST

Astrochemistry database of chemical species.

[ascl:1812.014] GENGA: Gravitational ENcounters with Gpu Acceleration

GENGA (Gravitational ENcounters with Gpu Acceleration) integrates planet and planetesimal dynamics in the late stage of planet formation and stability analyses of planetary systems. It uses mixed variable integration when the motion is a perturbed Kepler orbit and combines this with a direct N-body Bulirsch-Stoer method during close encounters. It supports three simulation modes: 1.) integration of up to 2048 massive bodies; 2.) integration with up to a million test particles; and 3.) parallel integration of a large number of individual planetary systems.

[ascl:1812.013] Lightkurve: Kepler and TESS time series analysis in Python

Lightkurve analyzes astronomical flux time series data, in particular the pixels and light curves obtained by NASA’s Kepler, K2, and TESS exoplanet missions. This community-developed Python package is designed to be user friendly to lower the barrier for students, astronomers, and citizen scientists interested in analyzing data from these missions. Lightkurve provides easy tools to download, inspect, and analyze time series data and its documentation is supported by a large syllabus of tutorials.

[ascl:1812.012] distlink: Minimum orbital intersection distance (MOID) computation library

distlink computes the minimum orbital intersection distance (MOID), or global minimum of the distance between the points lying on two Keplerian ellipses by finding all stationary points of the distance function, based on solving an algebraic polynomial equation of 16th degree. The program tracks numerical errors and carefully treats nearly degenerate cases, including practical cases with almost circular and almost coplanar orbits. Benchmarks confirm its high numeric reliability and accuracy, and even with its error-controlling overheads, this algorithm is a fast MOID computation method that may be useful in processing large catalogs. Written in C++, the library also includes auxiliary functions.

[ascl:1812.011] GRAND-HOD: GeneRalized ANd Differentiable Halo Occupation Distribution

GRAND-HOD (GeneRalized ANd Differentiable Halo Occupation Distribution) takes a generalized Halo Occupation Distribution (HOD) prescription as input and outputs the corresponding mock galaxy catalogs in binary files. The code is differentiable and incorporates various generalizations to the standard HOD. It is written for the Abacus simulations, but the main functionalities can be easily adapted for other halo catalogs with the appropriate properties.

[ascl:1812.010] PynPoint 0.6.0: Pipeline for processing and analysis of high-contrast imaging data

PynPoint processes and analyzes high-contrast imaging data of exoplanets and circumstellar disks. The generic, end-to-end pipeline's modular architecture separates the core functionalities and the pipeline modules. These modules have specific tasks such as background subtraction, frame selection, centering, PSF subtraction with principal component analysis, estimation of detection limits, and photometric and astrometric analysis. All modules store their results in a central database. Management of the available hardware by the backend of the pipeline is in particular an advantage for data sets containing thousands of images, as is common in the mid-infrared wavelength regime. This version of PynPoint is a significant rewrite of the earlier PynPoint package (ascl:1501.001).

[ascl:1812.009] galclassify: Stellar classifications using a galactic population synthesis model

The stellar classification code galclassify is a stand-alone version of Galaxia (ascl:1101.007). It classifies and generates a synthetic population for each star using input containing observables in a fixed format rather than using a precomputed population over a large field. It is suitable for individual stellar classifications, but slow if you want to classify large samples of stars.

[ascl:1812.008] easyaccess: SQL command line interpreter for astronomical surveys

easyaccess facilitates access to astronomical catalogs stored in SQL Databases. It is an enhanced command line interpreter and provides a custom interface with custom commands and was specifically designed to access data from the Dark Energy Survey Oracle database, including autocompletion of tables, columns, users and commands, simple ways to upload and download tables using csv, fits and HDF5 formats, iterators, search and description of tables among others. It can easily be extended to other surveys or SQL databases. The package is written in Python and supports customized addition of commands and functionalities.

[ascl:1812.007] ExoGAN: Exoplanets Generative Adversarial Network

ExoGAN (Exoplanets Generative Adversarial Network) analyzes exoplanetary atmospheres using an unsupervised deep-learning algorithm that recognizes molecular features, atmospheric trace-gas abundances, and planetary parameters. After training, ExoGAN can be applied to a large number of instruments and planetary types and can be used either as a final atmospheric analysis or to provide prior constraints to subsequent retrieval.

[ascl:1812.006] Fermipy: Fermi-LAT data analysis package

Fermipy facilitates analysis of data from the Large Area Telescope (LAT) with the Fermi Science Tools. It is built on the pyLikelihood interface of the Fermi Science Tools and provides a set of high-level tools for performing common analysis tasks, including data and model preparation with the gt-tools, extracting a spectral energy distribution (SED) of a source, and generating TS and residual maps for a region of interest. Fermipy also finds new source candidates and can localize a source or fit its spatial extension. The package uses a configuration-file driven workflow in which the analysis parameters (data selection, IRFs, and ROI model) are defined in a YAML configuration file. Analysis is executed through a python script that calls the methods of GTAnalysis to perform different analysis operations.

[ascl:1812.005] SPAMCART: Smoothed PArticle Monte CArlo Radiative Transfer

SPAMCART generates synthetic spectral energy distributions and intensity maps from smoothed particle hydrodynamics simulation snapshots. It follows discrete luminosity packets as they propagate through a density field, and computes the radiative equilibrium temperature of the ambient dust from their trajectories. The sources can be extended and/or embedded, and discrete and/or diffuse. The density is not mapped on to a grid, and therefore the calculation is performed at exactly the same resolution as the hydrodynamics. The code strictly adheres to Kirchhoff's law of radiation. The algorithm is based on the Lucy Monte Carlo radiative transfer method and is fairly simple to implement, as it uses data structures that are already constructed for other purposes in modern particle codes

[ascl:1812.004] aesop: ARC Echelle Spectroscopic Observation Pipeline

aesop (ARC Echelle Spectroscopic Observation Pipeline) analyzes echelle spectra for observations made by the Astrophysics Research Consortium (ARC) Echelle Spectrograph on the ARC 3.5 m Telescope at Apache Point Observatory. It is a high resolution spectroscopy software toolkit that picks up where the traditional IRAF reduction scripts leave off, and offers blaze function normalization by polynomial fits to observations of early-type stars, a robust least-squares normalization method, and radial velocity measurements (or offset removals) via cross-correlation with model spectra, including barycentric radial velocity calculations. It also concatenates multiple echelle orders into a simple 1D spectrum and provides approximate flux calibration.

[ascl:1812.003] PFANT: Stellar spectral synthesis code

PFANT computes a synthetic spectrum assuming local thermodynamic equilibrium from a given stellar model atmosphere and lists of atomic and molecular lines; it provides large wavelength coverage and line lists from ultraviolet through the visible and near-infrared. PFANT has been optimized for speed, offers error reporting, and command-line configuration options.

[ascl:1812.002] GLADIS: GLobal Accretion Disk Instability Simulation

GLADIS (GLobal Accretion Disk Instability Simulation) computes the time-dependent evolution of a black hole accretion disk, in one-dimensional, axisymmetric, vertically integrated scheme. The code solves two partial-differential equations of hydrodynamics for surface density and temperature evolution, i.e., given by viscous diffusion and energy conservation. Accretion disks can be subject to radiation-pressure instability if the stress tensor is proportional to the total (gas plus radiation) pressure. In the gas-pressure dominated case there is no instability. An intermediate case is provided in the code by the square root of the gas and total pressures. GLADIS is parallelized with MPI, and sample .ini and run command files are provided with the code.

[ascl:1812.001] WISP: Wenger Interferometry Software Package

WISP (Wenger Interferometry Software Package) is a radio interferometry calibration, reduction, imaging, and analysis package. WISP is a collection of Python code implemented through CASA (ascl:1107.013). Its generic and modular framework is designed to handle any continuum or spectral line radio interferometry data.

[submitted] taktent: A Python framework for agent-based simulations of SETI observations

This Python package allows the user to setup and run an agent-based simulation of a SETI survey. The package allows the creation of a population of observing and transmitting civilisations. Each transmitter and observer conducts their activities according to an input strategy. The success of observers and transmitters can then be recorded, and multiple simulations can be run for Monte Carlo Realisation.

This package is therefore a flexible framework in which to simulate and test different SETI strategies, both as an Observer and as a Transmitter. It is primarily designed with radio SETI in mind, but is sufficiently flexible to simulate all forms of electromagnetic SETI, and potentially neutrino and gravitational wave SETI.

[ascl:1811.020] PulsarHunter: Searching for and confirming pulsars

Pulsarhunter searches for and confirms pulsars; it provides a set of time domain optimization tools for processing timeseries data produced by SIGPROC (ascl:1107.016). The software can natively write candidate lists for JReaper (included in the package), removing the need to manually import candidates into JReaper; JReaper also reads the PulsarHunter candidate file format.

[ascl:1811.019] PENTACLE: Large-scale particle simulations code for planet formation

PENTACLE calculates gravitational interactions between particles within a cut-off radius and a Barnes-Hut tree method for gravity from particles beyond. It uses FDPS (ascl:1604.011) to parallelize a Barnes-Hut tree algorithm for a memory-distributed supercomputer. The software can handle 1-10 million particles in a high-resolution N-body simulation on CPU clusters for collisional dynamics, including physical collisions in a planetesimal disc.

[ascl:1811.018] gdr2_completeness: GaiaDR2 data retrieval and manipulation

gdr2_completeness queries Gaia DR2 TAP services and divides the queries into sub-queries chunked into arbitrary healpix bins. Downloaded data are formatted into arrays. Internal completeness is calculated by dividing the total starcount and starcounts with an applied cut (e.g., radial velocity measurement and good parallax). Independent determination of the external GDR2 completeness per healpix (level 6) and G magnitude bin (3 coarse bins: 8-12,12-15,15-18) is inferred from a crossmatch with 2MASS data. The overall completeness of a specific GDR2 sample can be approximated by multiplying the internal with the external completeness map, which is useful when data are compared to models thereof. Jupyter notebooks showcasing both utilities enable the user to easily construct the overall completeness for arbitrary samples of the GDR2 catalogue.

[ascl:1811.017] VPLanet: Virtual planet simulator

VPLanet (Virtual Planetary Laboratory) simulates planetary system evolution with a focus on habitability. Physical models, typically consisting of ordinary differential equations for stellar, orbital, tidal, rotational, atmospheric, internal, magnetic, climate, and galactic evolution, are coupled together to simulate evolution for the age of a system.

[ascl:1811.016] VoigtFit: Absorption line fitting for Voigt profiles

VoigtFit fits Voigt profiles to absorption lines. It fits multiple components for various atomic lines simultaneously, allowing parameters to be tied and fixed, and can automatically fit a polynomial continuum model together with the line profiles. A physical model can be used to constrain thermal and turbulent broadening of absorption lines as well as implementing molecular excitation models. The code uses a χ2 minimization approach to find the best solution and offers interactive features such as manual continuum placement locally around each line, manual masking of undesired fitting regions, and interactive definition of velocity components for various elements, improving the ease of estimating initial guesses.

[ascl:1811.015] radon: Streak detection using the Fast Radon Transform

radon performs a Fast Radon Transform (FRT) on image data for streak detection. The software finds short streaks and multiple streaks, convolves the images with a given PSF, and tracks the best S/N results and find a automatic threshold. It also calculates the streak parameters in the input image and the streak parameters in the input image. radon has a simulator that can make multiple streaks of different intensities and coordinates, and can simulate random streaks with parameters chosen uniformly in a user-defined range.

[ascl:1811.014] pygad: Analyzing Gadget Simulations with Python

pygad provides a framework for dealing with Gadget snapshots. The code reads any of the many different Gadget (ascl:0003.001) formats, allows easy masking snapshots to particles of interest, decorates the data blocks with units, allows to add automatically updating derived blocks, and provides several binning and plotting routines, among other tasks, to provide convenient, intuitive handling of the Gadget data without the need to worry about technical details. pygad provides access to single stellar population (SSP) models, has an interface to Rockstar (ascl:1210.008) output files, provides its own friends-of-friends (FoF) finder, calculates spherical overdensities, and has a sub-module to generate mock absorption lines.

[ascl:1811.013] DiskSim: Modeling Accretion Disk Dynamics with SPH

DiskSim is a source-code distribution of the SPH accretion disk modeling code previously released in a Windows executable form as FITDisk (ascl:1305.011). The code released now is the full research code in Fortran and can be modified as needed by the user.

[ascl:1811.012] muLAn: gravitational MICROlensing Analysis Software

muLAn analyzes and fits light curves of gravitational microlensing events. The code includes all classical microlensing models (for example, single and binary microlenses, ground- and space-based parallax effects, orbital motion, finite-source effects, and limb-darkening); these can be combined into several time intervals of the analyzed light curve. Minimization methods include an Affine-Invariant Ensemble Sampler to generate a multivariate proposal function while running several Markov Chain Monte Carlo (MCMC) chains, for the set of parameters which is chosen to be fit; non-fitting parameters can be either kept fixed or set on a grid defined by the user. Furthermore, the software offers a model-free option to align all data sets together and allow inspection the light curve before any modeling work. It also comes with many useful routines (export publication-quality figures, data formatting and cleaning) and state-of-the-art statistical tools.

Modeling results can be interpreted using an interactive html page which contains all information about the light curve model, caustics, source trajectory, best-fit parameters and chi-square. Parameters uncertainties and statistical properties (such as multi-modal features of the posterior density) can be assessed from correlation plots. The code is modular, allowing the addition of other computation or minimization routines by directly adding their Python files without modifying the main code. The software has been designed to be easy to use even for the newcomer in microlensing, with external, synthetic and self-explanatory setup files containing all important commands and option settings. The user may choose to launch the code through command line instructions, or to import muLAn within another Python project like any standard Python package.

[ascl:1811.011] SIM5: Library for ray-tracing and radiation transport in general relativity

The SIM5 library contains routines for relativistic raytracing and radiation transfer in GR. Written C with a Python interface, it has a special focus on raytracing from accretion disks, tori, hot spots or any other 3D configuration of matter in Kerr geometry, but it can be used with any other metric as well. It handles both optically thick and thin sources as well as transport of polarization of the radiation and calculates the propagation of light rays from the source to an observer through a curved spacetime. It supports parallelization and runs on GPUs.

[ascl:1811.010] MillCgs: Searching for Compact Groups in the Millennium Simulation

MillCgs clusters galaxies from the semi-analytic models run on top of the Millennium Simulation to identify Compact Groups. MillCgs uses a machine learning clustering algorithm to find the groups and then runs analytics to filter out the groups that do not fit the user specified criteria. The package downloads the data, processes it, and then creates graphs of the data.

[ascl:1811.009] RLOS: Time-resolved imaging of model astrophysical jets

RLOS (Relativistic Line Of Sight) uses hydrocode output data, such as that from PLUTO (ascl:1010.045), to create synthetic images depicting what a model relativistic astrophysical jet looks like to a stationary observer. The approximate time-delayed imaging algorithm used is implemented within existing line-of-sight code. The software has the potential to study a variety of dynamical astrophysical phenomena in collaboration with other imaging and simulation tools.

[ascl:1811.008] Pylians: Python libraries for the analysis of numerical simulations

Pylians facilitates the analysis of numerical simulations (both N-body and hydro). This set of libraries, written in python, cython and C, compute power spectra, bispectra, and correlation functions, identifies voids, and populates halos with galaxies using an HOD. Pylians can also apply HI+H2 corrections to the output of hydrodynamic simulations, makes 21cm maps, computes DLAs column density distribution functions, and plots density fields.

[ascl:1811.007] Flame: Near-infrared and optical spectroscopy data reduction pipeline

Flame reduces near-infrared and optical multi-object spectroscopic data. Although the pipeline was created for the LUCI instrument at the Large Binocular Telescope, Flame, written in IDL, is modular and can be adapted to work with data from other instruments. The software uses 2D transformations, thus using one interpolation step to wavelength calibrate and rectify the data. The γ(x, y) transformation also includes the spatial misalignment between frames, which can be measured from a reference star observed simultaneously with the science targets; sky subtraction can be performed via nodding and/or modelling of the sky spectrum.

[ascl:1811.006] QuickSip: Project survey image properties onto the sky into Healpix maps

QuickSip quickly projects Survey Image Properties (e.g. seeing, sky noise, airmass) into Healpix sky maps with flexible weighting schemes. It was initially designed to produce observing condition "systematics" maps for the Dark Energy Survey (DES), but will work with any multi-epoch survey and images with valid WCS. QuickSip can reproduce the Mangle (ascl:1202.005) magnitude limit maps at sub-percent accuracy but doesn't support additional masks (stars, trails, etc), in which case Mangle should be used. Thus, QuickSip can be seen as a simplified Mangle to project image properties into Healpix maps in a fast and more flexible manner.

[ascl:1811.005] Shark: Flexible semi-analytic galaxy formation model

Shark is a flexible semi-analytic galaxy formation model for easy exploration of different physical processes. Shark has been implemented with several models for gas cooling, active galactic nuclei, stellar and photo-ionization feedback, and star formation (SF). The software can determine the stellar mass function and stellar–halo mass relation at z=0–4; cosmic evolution of the star formation rate density, stellar mass, atomic and molecular hydrogen; local gas scaling relations; and structural galaxy properties. It performs particularly well for the mass–size relation for discs/bulges, the gas–stellar mass and stellar mass–metallicity relations. Shark is written in C++11 and has been parallelized with OpenMP.

[ascl:1811.004] SEP: Source Extraction and Photometry

SEP (Source Extraction and Photometry) makes the core algorithms of Source Extractor (ascl:1010.064) available as a library of standalone functions and classes. These operate directly on in-memory arrays (no FITS files or configuration files). The code is derived from the Source Extractor code base (written in C) and aims to produce results compatible with Source Extractor whenever possible. SEP consists of a C library with no dependencies outside the standard library and a Python module that wraps the C library in a Pythonic API. The Python wrapper operates on NumPy arrays with NumPy as its only dependency. It is generated using Cython.

From Source Extractor, SEP includes background estimation, image segmentation (including on-the-fly filtering and source deblending), aperture photometry in circular and elliptical apertures, and source measurements such as Kron radius, "windowed" position fitting, and half-light radius. It also adds the following features that are not available in Source Extractor: optimized matched filter for variable noise in source extraction; circular annulus and elliptical annulus aperture photometry functions; local background subtraction in shape consistent with aperture in aperture photometry functions; exact pixel overlap mode in all aperture photometry functions; and masking of elliptical regions on images.

[ascl:1811.003] binaryBHexp: On-the-fly visualizations of precessing binary black holes

binaryBHexp (binary black hole explorer) uses surrogate models of numerical simulations to generate on-the-fly interactive visualizations of precessing binary black holes. These visualizations can be generated in a few seconds and at any point in the 7-dimensional parameter space of the underlying surrogate models. These visualizations provide a valuable means to understand and gain insights about binary black hole systems and gravitational physics such as those detected by the LIGO gravitational wave detector.

[ascl:1811.002] DRAGONS: Gemini Observatory data reduction platform

DRAGONS (Data Reduction for Astronomy from Gemini Observatory North and South) is Gemini's Python-based data reduction platform. DRAGONS offers an automation system that allows for hands-off pipeline reduction of Gemini data, or of any other astronomical data once configured. The platform also allows researchers to control input parameters and in some cases will offer to interactively optimize some data reduction steps, e.g. change the order of fit and visualize the new solution.

[ascl:1811.001] synphot: Synthetic photometry using Astropy

Synphot simulates photometric data and spectra, observed or otherwise. It can incorporate the user's filters, spectra, and data, and use of a pre-defined standard star (Vega), bandpass, or extinction law. synphot can also construct complicated composite spectra using different models, simulate observations, and compute photometric properties such as count rate, effective wavelength, and effective stimulus. It can manipulate a spectrum by, for example, applying redshift, or normalize it to a given flux value in a given bandpass. Synphot can also sample a spectrum at given wavelengths, plot a quick-view of a spectrum, and perform repetitive operations such as simulating the observations of multiple type of sources through multiple bandpasses. Synphot understands Astropy (ascl:1304.002) models and units and is an Astropy affiliated package. Support for HST and JWST is available through the extension stsynphot (ascl:2010.003).

[submitted] stginga: Ginga for STScI

stginga customizes Ginga to aid data analysis for the data supported by STScI (e.g., HST or JWST). For instance, it provides plugins and configuration files that understand HST and JWST data products.

[ascl:1810.021] Firefly: Interactive exploration of particle-based data

Firefly provides interactive exploration of particle-based data in the browser. The user can filter, display vector fields, and toggle the visibility of their customizable datasets all on-the-fly. Different Firefly visualizations, complete with preconfigured data and camera view-settings, can be shared by URL. As Firefly is written in WebGL, it can be hosted online, though Firefly can also be used locally, without an internet connection. Firefly was developed with simulations of galaxy formation in mind but is flexible enough to display any particle-based data. Other features include a stereoscopic 3D picture mode and mobile compatibility.

[ascl:1810.020] DDS: Debris Disk Radiative Transfer Simulator

DDS simulates scattered light and thermal reemission in arbitrary optically dust distributions with spherical, homogeneous grains where the dust parameters (optical properties, sublimation temperature, grain size) and SED of the illuminating/ heating radiative source can be arbitrarily defined. The code is optimized for studying circumstellar debris disks where large grains (i.e., with large size parameters) are expected to determine the far-infrared through millimeter dust reemission spectral energy distribution. The approach to calculate dust temperatures and dust reemission spectra is only valid in the optically thin regime. The validity of this constraint is verified for each model during the runtime of the code. The relative abundances of different grains can be arbitrarily chosen, but must be constant outside the dust sublimation region., i.e., the shape of the (arbitrary) radial dust density distribution outside the dust sublimation region is the same for all grain sizes and chemistries.

[ascl:1810.019] MIEX: Mie scattering code for large grains

Miex calculates Mie scattering coefficients and efficiency factors for broad grain size distributions and a very wide wavelength range (λ ≈ 10-10-10-2m) of the interacting radiation and incorporates standard solutions of the scattering amplitude functions. The code handles arbitrary size parameters, and single scattering by particle ensembles is calculated by proper averaging of the respective parameters.

[ascl:1810.018] APPLawD: Accurate Potentials in Power Law Disks

APPLawD (Accurate Disk Potentials for Power Law Surface densities) determines the gravitational potential in the equatorial plane of a flat axially symmetric disk (inside and outside) with finite size and power law surface density profile. Potential values are computed on the basis of the density splitting method, where the residual Poisson kernel is expanded over the modulus of the complete elliptic integral of the first kind. In contrast with classical multipole expansions of potential theory, the residual series converges linearly inside sources, leading to very accurate potential values for low order truncations of the series. The code is easy to use, works under variable precision, and is written in Fortran 90 with no external dependencies.

[ascl:1810.017] SOPHISM: Software Instrument Simulator

SOPHISM models astronomical instrumentation from the entrance of the telescope to data acquisition at the detector, along with software blocks dealing with, for example, demodulation, inversion, and compression. The code performs most analyses done with light in astronomy, such as differential photometry, spectroscopy, and polarimetry. The simulator offers flexibility and implementation of new effects and subsystems, making it user-adaptable for a wide variety of instruments. SOPHISM can be used for all stages of instrument definition, design, operation, and lifetime tracking evaluation.

[ascl:1810.016] XCLASS: eXtended CASA Line Analysis Software Suite

XCLASS (eXtended CASA Line Analysis Software Suite) extends CASA (ascl:1107.013) with new functions for modeling interferometric and single dish data. It provides a tool for calculating synthetic spectra by solving the radiative transfer equation for an isothermal object in one dimension, taking into account the finite source size and dust attenuation. It also includes an interface for MAGIX (ascl:1303.009) to find the parameter set that most closely reproduces the data.

[ascl:1810.015] cuFFS: CUDA-accelerated Fast Faraday Synthesis

cuFFS (CUDA-accelerated Fast Faraday Synthesis) performs Faraday rotation measure synthesis; it is particularly well-suited for performing RM synthesis on large datasets. Compared to a fast single-threaded and vectorized CPU implementation, depending on the structure and format of the data cubes, cuFFs achieves an increase in speed of up to two orders of magnitude. The code assumes that the pixels values are IEEE single precision floating points (BITPIX=-32), and the input cubes must have 3 axes (2 spatial dimensions and 1 frequency axis) with frequency axis as NAXIS1. A package is included to reformat data with individual stokes Q and U channel maps to the required format. The code supports both the HDFITS format and the standard FITS format, and is written in C with GPU-acceleration achieved using Nvidia's CUDA parallel computing platform.

[ascl:1810.014] STiC: Stockholm inversion code

STiC is a MPI-parallel non-LTE inversion code for observed full-Stokes observations. The code processes lines from multiple atoms in non-LTE, including partial redistribution effects of scattered photons in angle and frequency of scattered photons (PRD), and can be used with model atmospheres that have a complex depth stratification without introducing artifacts.

[ascl:1810.013] catsHTM: Catalog cross-matching tool

The catsHTM package quickly accesses and cross-matches large astronomical catalogs that have been reformatted into the HDF5-based file format. It performs efficient cone searches at resolutions from a few arc-seconds to degrees within a few milliseconds time, cross-match numerous catalogs, and can do general searches.

[ascl:1810.012] GiRaFFE: General relativistic force-free electrodynamics code

GiRaFFE leverages the Einstein Toolkit's (ascl:1102.014) highly-scalable infrastructure to create large-scale simulations of magnetized plasmas in strong, dynamical spacetimes on adaptive-mesh refinement (AMR) grids. It is based on IllinoisGRMHD (ascl:2004.003), a user-friendly, open-source, dynamical-spacetime GRMHD code, and is highly scalable, to tens of thousands of cores.

[ascl:1810.011] Eclairs: Efficient Codes for the LArge scales of the unIveRSe

Eclairs calculates matter power spectrum based on standard perturbation theory and regularized pertubation theory. The codes are written in C++ with a python wrapper which is designed to be easily combined with MCMC samplers.

[ascl:1810.010] ODTBX: Orbit Determination Toolbox

ODTBX (Orbit Determination Toolbox) provides orbit determination analysis, advanced mission simulation, and analysis for concept exploration, proposal, early design phase, and/or rapid design center environments. The core ODTBX functionality is realized through a set of estimation commands that incorporate Monte Carlo data simulation, linear covariance analysis, and measurement processing at a generic level; its functions and utilities are combined in a flexible architecture to allow modular development of navigation algorithms and simulations. ODTBX is written in Matlab and Java.

[ascl:1810.009] PyUltraLight: Pseudo-spectral Python code to compute ultralight dark matter dynamics

PyUltraLight computes non-relativistic ultralight dark matter dynamics in a static spacetime background. It uses pseudo-spectral methods to compute the evolution of a complex scalar field governed by the Schrödinger-Poisson system of coupled differential equations. Computations are performed on a fixed-grid with periodic boundary conditions, allowing for a decomposition of the field in momentum space by way of the discrete Fourier transform. The field is then evolved through a symmetrized split-step Fourier algorithm, in which nonlinear operators are applied in real space, while spatial derivatives are computed in Fourier space. Fourier transforms within PyUltraLight are handled using the pyFFTW pythonic wrapper around FFTW (ascl:1201.015).

[ascl:1810.008] pycraf: Spectrum-management compatibility

The pycraf Python package provides functions and procedures for spectrum-management compatibility studies, such as calculating the interference levels at a radio telescope produced from a radio broadcasting tower. It includes an implementation of ITU-R Recommendation P.452-16 for calculating path attenuation for the distance between an interferer and the victim service. It supports NASA's Shuttle Radar Topography Mission (SRTM) data for height-profile generation, includes a full implementation of ITU-R Rec. P.676-10, which provides two atmospheric models to calculate the attenuation for paths through Earth's atmosphere, and provides various antenna patterns necessary for compatibility studies (e.g., RAS, IMT, fixed-service links). The package can also convert power flux densities, field strengths, transmitted and received powers at certain distances and frequencies into each other.

[ascl:1810.007] ARTES: 3D Monte Carlo scattering radiative transfer in planetary atmospheres

The 3D Monte Carlo radiative transfer code ARTES calculates reflected light and thermal radiation in a spherical grid with a parameterized distribution of gas, clouds, hazes, and circumplanetary material. Designed specifically for (polarized) scattered light simulations of planetary atmospheres, it can compute both reflected stellar light and thermal emission from the planet for an arbitrary atmospheric structure and distribution of opacity sources. Multiple scattering, absorption, and polarization are fully treated and the output includes an image, spectrum, or phase curve. Several tools are included to create opacities and scattering matrices for molecules and clouds.

[ascl:1810.006] Echelle++: Generic spectrum simulator

Echelle++ simulates realistic raw spectra based on the Zemax model of any spectrograph, with a particular emphasis on cross-dispersed Echelle spectrographs. The code generates realistic spectra of astronomical and calibration sources, with accurate representation of optical aberrations, the shape of the point spread function, detector characteristics, and photon noise. It produces high-fidelity spectra fast, an important feature when testing data reduction pipelines with a large set of different input spectra, when making critical choices about order spacing in the design phase of the instrument, or while aligning the spectrograph during construction. Echelle++ also works with low resolution, low signal to noise, multi-object, IFU, or long slit spectra, for simulating a wide array of spectrographs.

[ascl:1810.005] STARRY: Analytic computation of occultation light curves

STARRY computes light curves for various applications in astronomy: transits and secondary eclipses of exoplanets, light curves of eclipsing binaries, rotational phase curves of exoplanets, light curves of planet-planet and planet-moon occultations, and more. By modeling celestial body surface maps as sums of spherical harmonics, STARRY does all this analytically and is therefore fast, stable, and differentiable. Coded in C++ but wrapped in Python, STARRY is easy to install and use.

[ascl:1810.004] VaeX: Visualization and eXploration of Out-of-Core DataFrames

VaeX (Visualization and eXploration) interactively visualizes and explores big tabular datasets. It can calculate statistics such as mean, sum, count, and standard deviation on an N-dimensional grid up to a billion (109) objects/rows per second. Visualization is done using histograms, density plots, and 3d volume rendering, allowing interactive exploration of big data. VaeX uses memory mapping, zero memory copy policy and lazy computations for best performance, and integrates well with the Jupyter/IPython notebook/lab ecosystem.

[ascl:1810.003] JETGET: Hydrodynamic jet simulation visualization and analysis

JETGET accesses, visualizes, and analyses (magnetized-)fluid dynamics data stored in Hierarchical Data Format (HDF) and ASCII files. Although JETGET has been optimized to handle data output from jet simulations using the Zeus code (ascl:1306.014) from NCSA, it is also capable of analyzing other data output from simulations using other codes. JETGET can select variables from the data files, render both two- and three-dimensional graphics and analyze and plot important physical quantities. Graphics can be saved in encapsulated Postscript, JPEG, VRML, or saved into an MPEG for later visualization and/or presentations. The strength of JETGET in extracting the physics underlying such phenomena is demonstrated as well as its capabilities in visualizing the 3-dimensional features of the simulated magneto-hydrodynamic jets. The JETGET tool is written in Interactive Data Language (IDL) and uses a graphical user interface to manipulate the data. The tool was developed on a LINUX platform and can be run on any platform that supports IDL.

[ascl:1810.002] Barcode: Bayesian reconstruction of cosmic density fields

Barcode (BAyesian Reconstruction of COsmic DEnsity fields) samples the primordial density fields compatible with a set of dark matter density tracers after cosmic evolution observed in redshift space. It uses a redshift space model based on the analytic solution of coherent flows within a Hamiltonian Monte Carlo posterior sampling of the primordial density field; this method is applicable to analytically derivable structure formation models, such as the Zel'dovich approximation, but also higher order schemes such as augmented Lagrangian perturbation theory or even particle mesh models. The algorithm is well-suited for analysis of the dark matter cosmic web implied by the observed spatial distribution of galaxy clusters, such as obtained from X-ray, SZ or weak lensing surveys, as well as that of the intergalactic medium sampled by the Lyman alpha forest. In these cases, virialized motions are negligible and the tracers cannot be modeled as point-like objects. Barcode can be used in all of these contexts as a baryon acoustic oscillation reconstruction algorithm.

[ascl:1810.001] galfast: Milky Way mock catalog generator

galfast generates catalogs for arbitrary, user-supplied Milky Way models, including empirically derived ones. The built-in model set is based on fits to SDSS stellar observations over 8000 deg2 of the sky and includes a three-dimensional dust distribution map. Because of the capability to use empirically derived models, galfast typically produces closer matches to the actual observed counts and color-magnitude diagrams. In particular, galfast-generated catalogs are used to derive the stellar component of “Universe Model” catalogs used by the LSST Project. A key distinguishing characteristic of galfast is its speed. Galfast uses the GPU (with kernels written in NVIDIA C/C++ for CUDA) to offload compute intensive model sampling computations to the GPU, enabling the generation of realistic catalogs to full LSST depth in hours (instead of days or weeks), making it possible to study proposed science cases with high precision.

[ascl:1809.016] RequiSim: Variance weighted overlap calculator

RequiSim computes the Variance Weighted Overlap, which is a measure of the bias on the lensing signal from power spectrum modelling bias for any non-linear model. It assumes that the bias on the power spectrum is Gaussian with a covariance described by a user-provided knowledge matrix that describes the covariance in the bias on the power spectrum. The data from the Euclid wide-field survey are included.

[ascl:1809.015] MrMoose: Multi-Resolution Multi-Object/Origin Spectral Energy distribution fitting procedure

MrMoose (Multi-Resolution Multi-Object/Origin Spectral Energy) fits user-defined models onto a set of multi-wavelength data using a Bayesian framework. The code can handle blended sources, large variation in resolution, and even upper limits consistently. It also generates a series of outputs allowing for an quick interpretation of the results. The code uses emcee (ascl:1303.002), and saves the emcee sampler object, thus allowing users to transfer the output to a personal graphical interface.

[ascl:1809.014] stepped_luneburg: Stacked-based ray tracing code to model a stepped Luneburg lens

stepped_luneburg investigates the scattered light properties of a Luneburg lens approximated as a series of concentric shells with discrete refractive indices. The optical Luneburg lens has promising applications for low-cost, continuous all-sky monitoring to obtain transit light curves of bright, nearby stars. This code implements a stack-based algorithm that tracks all reflected and refracted rays generated at each optical interface of the lens as described by Snell's law. The Luneburg lens model parameters, such as number of lens layers, the power-law that describes the refractive indices, the number of incident rays, and the initial direction of the incident wavefront can be altered to optimize lens performance. The stepped_luneburg module can be imported within the Python environment or used with scripting, and it is accompanied by two other modules, enc_int and int_map, that help the user to determine the resolving power of the lens and the strength of scattered light haloes for the purpose of quality assessment.

[ascl:1809.013] dynesty: Dynamic Nested Sampling package

dynesty is a Dynamic Nested Sampling package for estimating Bayesian posteriors and evidences. dynesty samples from a given distribution when provided with a loglikelihood function, a prior_transform function (that transforms samples from the unit cube to the target prior), and the dimensionality of the parameter space.

[ascl:1809.012] nestcheck: Nested sampling calculations analysis

Nestcheck analyzes nested sampling runs and estimates numerical uncertainties on calculations using them. The package can load results from a number of nested sampling software packages, including MultiNest (ascl:1109.006), PolyChord (ascl:1502.011), dynesty (ascl:1809.013) and perfectns (ascl:1809.005), and offers the flexibility to add input functions for other nested sampling software packages. Nestcheck utilities include error analysis, diagnostic tests, and plots for nested sampling calculations.

[ascl:1809.011] qp: Quantile parametrization for probability distribution functions

qp manipulates parametrizations of 1-dimensional probability distribution functions, as suitable for photo-z PDF compression. The code helps determine a parameterization for storing a catalog of photo-z PDFs that balances the available storage resources against the accuracy of the photo-z PDFs and science products reconstructed from the stored parameters.

[ascl:1809.010] Isca: Idealized global circulation modeling

Isca provides a framework for the idealized modeling of the global circulation of planetary atmospheres at varying levels of complexity and realism. Though Isca is an outgrowth of models designed for Earth's atmosphere, it may readily be extended into other planetary regimes. Various forcing and radiation options are available. At the simple end of the spectrum a Held-Suarez case is available. An idealized grey radiation scheme, a grey scheme with moisture feedback, a two-band scheme and a multi-band scheme are also available, all with simple moist effects and astronomically-based solar forcing. At the complex end of the spectrum the framework provides a direct connection to comprehensive atmospheric general circulation models.

[ascl:1809.009] NEBULA: Radiative transfer code of ionized nebulae at radio wavelengths

NEBULA performs the radiative transfer of the 3He+ hyperfine transition, radio recombination lines (RRLs), and free-free continuum emission through a model nebula. The model nebula is composed of only H and He within a three-dimension Cartesian grid with arbitrary density, temperature, and ionization structure. The 3He+ line is assumed to be in local thermodynamic equilibrium (LTE), but non-LTE effects and pressure broadening from electron impacts can be included for the RRLs. All spectra are broadened by thermal and microturbulent motions.

[ascl:1809.008] PyQSOFit: Python code to fit the spectrum of quasars

The Python QSO fitting code (PyQSOFit) measures spectral properties of quasars. Based on Shen's IDL version, this code decomposes different components in the quasar spectrum, e.g., host galaxy, power-law continuum, Fe II component, and emission lines. In addition, it can run Monto Carlo iterations using flux randomization to estimate the uncertainties.

[ascl:1809.007] surfinBH: Surrogate final black hole properties for mergers of binary black holes

surfinBH predicts the final mass, spin and recoil velocity of the remnant of a binary black hole merger. Trained directly against numerical relativity simulations, these models are extremely accurate, reproducing the results of the simulations at the same level of accuracy as the simulations themselves. Fits such as these play a crucial role in waveform modeling and tests of general relativity with gravitational waves, performed by LIGO.

[ascl:1809.006] spops: Spinning black-hole binary population synthesis

spops is a database of populations synthesis simulations of spinning black-hole binary systems, together with a python module to query it. Data are obtained with the startrack and precession [ascl:1611.004] numerical codes to consistently evolve binary stars from formation to gravitational-wave detection. spops allows quick exploration of the interplay between stellar physics and black-hole spin dynamics.

[ascl:1809.005] perfectns: "Perfect" dynamic and standard nested sampling for spherically symmetric likelihoods and priors

perfectns performs dynamic nested sampling and standard nested sampling for spherically symmetric likelihoods and priors, and analyses the samples produced. The spherical symmetry allows the nested sampling algorithm to be followed “perfectly” - i.e. without implementation-specific errors correlations between samples. It is intended for use in research into the statistical properties of nested sampling, and to provide a benchmark for testing the performance of nested sampling software packages used for practical problems - which rely on numerical techniques to produce approximately uncorrelated samples.

[ascl:1809.004] VBBINARYLENSING: Microlensing light-curve computation

VBBinaryLensing forward models gravitational microlensing events using the advanced contour integration method; it supports single and binary lenses. The lens map is inverted on a collection of points on the source boundary to obtain a corresponding collection of points on the boundaries of the images from which the area of the images can be recovered by use of Green’s theorem. The code takes advantage of a number of techniques to make contour integration much more efficient, including using a parabolic correction to increase the accuracy of the summation, introducing an error estimate on each arc of the boundary to enable defining an optimal sampling, and allowing the inclusion of limb darkening. The code is written as a C++ library and wrapped as a Python package, and can be called from either C++ or Python.

[ascl:1809.003] PASTA: Python Astronomical Stacking Tool Array

PASTA performs median stacking of astronomical sources. Written in Python, it can filter sources, provide stack statistics, generate Karma annotations, format source lists, and read information from stacked Flexible Image Transport System (FITS) images. PASTA was originally written to examine polarization stack properties and includes a Monte Carlo modeler for obtaining true polarized intensity from the observed polarization of a stack. PASTA is also useful as a generic stacking tool, even if polarization properties are not being examined.

[ascl:1809.002] PCCDPACK: Polarimetry with CCD

PCCDPACK analyzes polarimetry data. The set of routines is written in CL-IRAF (including compiled Fortran codes) and analyzes dozens of point objects simultaneously on the same CCD image. A subpackage, specpol, is included to analyze spectropolarimetry data.

[ascl:1809.001] LEMON: Differential photometry pipeline

LEMON is a differential-photometry pipeline, written in Python, that determines the changes in the brightness of astronomical objects over time and compiles their measurements into light curves. This code makes it possible to completely reduce thousands of FITS images of time series in a matter of only a few hours, requiring minimal user interaction.

[ascl:1808.011] Robbie: Radio transients and variables detection workflow

Robbie automates cataloging sources, finding variables, and identifying transients in the image domain. It works in a batch processing paradigm with a modular design so components can be swapped out or upgraded to adapt to different input data while retaining a consistent and coherent methodological approach. Robbie is based on commonly used and open software, including AegeanTools (ascl:1212.009) and STILS/TOPCAT (ascl:1101.010).

[ascl:1808.010] hi_class: Horndeski in the Cosmic Linear Anisotropy Solving System

hi_class implements Horndeski's theory of gravity in the modern Cosmic Linear Anisotropy Solving System (ascl:1106.020). It can be used to compute any cosmological observable at the level of background or linear perturbations, such as cosmological distances, cosmic microwave background, matter power and number count spectra (including relativistic effects). hi_class can be readily interfaced with Monte Python (ascl:1307.002) to test Gravity and Dark Energy models.

[ascl:1808.009] py-sdm: Support Distribution Machines

py-sdm (Support Distribution Machines) is a Python implementation of nonparametric nearest-neighbor-based estimators for divergences between distributions for machine learning on sets of data rather than individual data points. It treats points of sets of data as samples from some unknown probability distribution and then statistically estimates the distance between those distributions, such as the KL divergence, the closely related Rényi divergence, L2 distance, or other similar distances.

[ascl:1808.008] PyMieDap: Python Mie Doubling Adding Program

PyMieDAP (Python Mie Doubling Adding Program) makes light scattering computations with Mie scattering and radiative transfer computations with full orders of scattering and taking into account the polarization of the light scattered. Full planet modeling at any phase angle is possible. With the included subpackage exopy, it is also possible to simulate systems with a star, a planet and a possible moon.

[ascl:1808.007] 2DSF: Vectorized Structure Function Algorithm

The vectorized physical domain structure function (SF) algorithm calculates the velocity anisotropy within two-dimensional molecular line emission observations. The vectorized approach is significantly faster than brute force iterative algorithms and is very efficient for even relatively large images. Furthermore, unlike frequency domain algorithms which require the input data to be fully integrable, this algorithm, implemented in Python, has no such requirements, making it a robust tool for observations with irregularities such as asymmetric boundaries and missing data.

[ascl:1808.006] Fips: An OpenGL based FITS viewer

FIPS is a cross-platform FITS viewer with a responsive user interface. Unlike other FITS viewers, FIPS uses GPU hardware via OpenGL to provide functionality such as zooming, panning and level adjustments. OpenGL 2.1 and later is supported. FIPS supports all 2D image formats except floating point formats on OpenGL 2.1. FITS image extension has basic limited support.

[ascl:1808.005] hfof: Friends-of-Friends via spatial hashing

hfof is a 3-d friends-of-friends (FoF) cluster finder with Python bindings based on a fast spatial hashing algorithm that identifies connected sets of points where the point-wise connections are determined by a fixed spatial distance. This technique sorts particles into fine cells sufficiently compact to guarantee their cohabitants are linked, and uses locality sensitive hashing to search for neighboring (blocks of) cells. Tests on N-body simulations of up to a billion particles exhibit speed increases of factors up to 20x compared with FOF via trees, and is consistently complete in less than the time of a k-d tree construction, giving it an intrinsic advantage over tree-based methods.

[ascl:1808.004] ImPlaneIA: Image Plane Approach to Interferometric Analysis

Aperture masking interferometric data analysis involves measuring phases and amplitudes of fringes formed by interference between holes in the pupil mask. These fringe observables can be measured by computing an analytic model of the point spread function and fitting the relevant set of spatial frequencies directly in the image plane, without recourse to numerical Fourier transforms. The ImPlaneIA pipeline converts aperture masking images to fringe observables by fitting fringes in the image plane, calibrates data from a target of interest with one or more point source calibrators, and contains some basic model-fitting routines. The pipeline can accept different mask geometries, instruments, and observing modes.

[ascl:1808.003] CPF: Corral Pipeline Framework

Corral generates astronomical pipelines. Data processing pipelines represent an important slice of the astronomical software library that include chains of processes that transform raw data into valuable information via data reduction and analysis. Written in Python, Corral features a Model-View-Controller design pattern on top of an SQL Relational Database capable of handling custom data models, processing stages, and communication alerts. It also provides automatic quality and structural metrics based on unit testing. The Model-View-Controller provides concept separation between the user logic and the data models, delivering at the same time multi-processing and distributed computing capabilities.

[ascl:1808.002] rsigma: Resonant disturbance

rsigma calculates the resonant disturbing function, R(sigma), for a massless particle in an arbitrary orbit perturbed by a planet in circular orbit. This function defines the strength of the resonance (its semi-amplitude) and the location of the stable equilibrium points (the minima). It depends on the variable sigma called critical angle and on the particle's orbital elements a, e, i and the argument of the perihelion. R(sigma) is numerically calculated and the code is valid for arbitrary eccentricities and inclinations, including retrograde orbits.

[ascl:1808.001] Barycorrpy: Barycentric velocity calculation and leap second management

barycorrpy (BCPy) is a Python implementation of Wright and Eastman's 2014 code (ascl:1807.017) that calculates precise barycentric corrections well below the 1 cm/s level. This level of precision is required in the search for 1 Earth mass planets in the Habitable Zones of Sun-like stars by the Radial Velocity (RV) method, where the maximum semi-amplitude is about 9 cm/s. BCPy was developed for the pipeline for the next generation Doppler Spectrometers - Habitable-zone Planet Finder (HPF) and NEID. An automated leap second management routine improves upon the one available in Astropy. It checks for and downloads a new leap second file before converting from the UT time scale to TDB. The code also includes a converter for JDUTC to BJDTDB.

[submitted] 3D texturized model of MARS (MOLA) regions

The Matlab Tool generates a 3D model (WRL, texturized in height false color map) of a defined region of the Mars surface. It defines the region of interest of the Mars surface (by Lat Long), a resolution of the MOLA DTMs to be considered (with a minimum px onground of 468 m), a scale factor to be multiplied to the height of the surface to improve features visibility for bumping or shadowing effect.

[ascl:1807.033] LSC: Supervised classification of time-series variable stars

LSC (LINEAR Supervised Classification) trains a number of classifiers, including random forest and K-nearest neighbor, to classify variable stars and compares the results to determine which classifier is most successful. Written in R, the package includes anomaly detection code for testing the application of the selected classifier to new data, thus enabling the creation of highly reliable data sets of classified variable stars.

[ascl:1807.032] SSMM: Slotted Symbolic Markov Modeling for classifying variable star signatures

SSMM (Slotted Symbolic Markov Modeling) reduces time-domain stellar variable observations to classify stellar variables. The method can be applied to both folded and unfolded data, and does not require time-warping for waveform alignment. Written in Matlab, the performance of the supervised classification code is quantifiable and consistent, and the rate at which new data is processed is dependent only on the computational processing power available.

[ascl:1807.031] xGDS: Exploration Ground Data Systems

xGDS (Exploration Ground Data Systems) synthesizes real world data (from sensors, robots, ROVs, mobile devices, etc) and human observations into rich, digital maps and displays for analysis, decision making, and collaboration. xGDS processes and maps data (including video) in real-time during operations and uses it to support live role-based geolocated note taking. Notes can be used to search for and display important data. The software enables real-time analysis of data, permitting one to make inferences and plan new data collection operations while still in the field.

[ascl:1807.030] ASP: Ames Stereo Pipeline

ASP (Ames Stereo Pipeline) provides fully automated geodesy and stereogrammetry tools for processing stereo imagery captured from satellites (around Earth and other planets), robotic rovers, aerial cameras, and historical imagery, with and without accurate camera pose information. It produces cartographic products, including digital elevation models (DEMs), ortho-projected imagery, 3D models, and bundle-adjusted networks of cameras. ASP's data products are suitable for science analysis, mission planning, and public outreach.

[ascl:1807.029] EVEREST: Tools for de-trending stellar photometry

EVEREST (EPIC Variability Extraction and Removal for Exoplanet Science Targets) removes instrumental noise from light curves with pixel level decorrelation and Gaussian processes. The code, written in Python, generates the EVEREST catalog and offers tools for accessing and interacting with the de-trended light curves. EVEREST exploits correlations across the pixels on the CCD to remove systematics introduced by the spacecraft’s pointing error. For K2, it yields light curves with precision comparable to that of the original Kepler mission. Interaction with the EVEREST catalog catalog is available via the command line and through the Python interface. Though written for K2, EVEREST can be applied to additional surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets.

[ascl:1807.028] ktransit: Exoplanet transit modeling tool in python

The routines in ktransit create and fit a transiting planet model. The underlying model is a Fortran implementation of the Mandel & Agol (2002) limb darkened transit model. The code calculates a full orbital model and eccentricity can be allowed to vary; radial velocity data can also be calculated via the model and included in the fit.

[ascl:1807.027] kplr: Tools for working with Kepler data using Python

kplr provides a lightweight Pythonic interface to the catalog of planet candidates (Kepler Objects of Interest [KOIs]) in the NASA Exoplanet Archive and the data stored in the Barbara A. Mikulski Archive for Space Telescopes (MAST). kplr automatically supports loading Kepler data using pyfits (ascl:1207.009) and supports two types of data: light curves and target pixel files.

[ascl:1807.026] SENR: Simple, Efficient Numerical Relativity

SENR (Simple, Efficient Numerical Relativity) provides the algorithmic framework that combines the C codes generated by NRPy+ (ascl:1807.025) into a functioning numerical relativity code. It is part of the numerical relativity code package SENR/NRPy+. The package extends previous implementations of the BSSN reference-metric formulation to a much broader class of curvilinear coordinate systems, making it suitable for modeling physical configurations with approximate or exact symmetries, such as modeling black hole dynamics.

[ascl:1807.025] NRPy+: Code generator for Numerical Relativity

NRPy+ (Python-based Code generation for Numerical Relativity and Beyond) generates highly-optimized C code from complex tensorial expressions input in Einstein-like notation. NRPy+ uses SymPy as its computer algebra system backend. It is part of the NRPy+/SENR numerical relativity code package for solving Einstein's equations of general relativity to model compact objects at about 1/100 the cost in memory of more traditional, AMR-based numerical relativity codes, thus allowing desktop computers to be used for gravitational wave astrophysics.

[ascl:1807.024] TBI: Three-Body Integration

Three-Body Integration performs numerical n-body simulations for mapping conditions for close approaches for the relevant parameter space of configurations and mass values of two white dwarfs and a third star. Low tertiary masses of 0.1M⊙ can be studied, and the collision probability can be estimated with good confidence for the case of nearly equal mass white dwarfs.

[ascl:1807.023] DAMOCLES: Monte Carlo line radiative transfer code

The Monte Carlo code DAMOCLES models the effects of dust, composed of any combination of species and grain size distributions, on optical and NIR emission lines emitted from the expanding ejecta of a late-time (> 1 yr) supernova. The emissivity and dust distributions follow smooth radial power-law distributions; any arbitrary distribution can be specified by providing the appropriate grid. DAMOCLES treats a variety of clumping structures as specified by a clumped dust mass fraction, volume filling factor, clump size and clump power-law distribution, and the emissivity distribution may also initially be clumped. The code has a large number of variable parameters ranging from 5 dimensions in the simplest models to > 20 in the most complex cases.

[ascl:1807.022] PUMA: Low-frequency radio catalog cross-matching

PUMA (Positional Update and Matching Algorithm) cross-matches low-frequency radio catalogs using a Bayesian positional probability with spectral matching criteria. The code reliably finds the correct spectral indices of sources and recovers ionospheric offsets. PUMA can be used to facilitate all-sky cross-matches with further constraints applied for other science goals.

[ascl:1807.021] POWER: Python Open-source Waveform ExtractoR

POWER (Python Open-source Waveform ExtractoR) monitors the status and progress of numerical relativity simulations and post-processes the data products of these simulations to compute the gravitational wave strain at future null infinity.

[ascl:1807.020] wdmerger: Simulate white dwarf mergers with CASTRO

wdmerger simulates binary white dwarf mergers (and related events) in CASTRO (ascl:1105.010) and provides useful information on the viability of mergers of white dwarfs as a progenitor for Type Ia supernovae.

[ascl:1807.019] GLS: Generalized Lomb-Scargle periodogram

The Lomb-Scargle periodogram is a common tool in the frequency analysis of unequally spaced data equivalent to least-squares fitting of sine waves. GLS is a solution for the generalization to a full sine wave fit, including an offset and weights (χ2 fitting). Compared to the Lomb-Scargle periodogram, GLS is superior as it provides more accurate frequencies, is less susceptible to aliasing, and gives a much better determination of the spectral intensity.

[ascl:1807.018] BARYCORR: Python interface for barycentric RV correction

BARYCORR is a Python interface for ZBARYCORR (ascl:1807.017); it requires the measured redshift and returns the corrected barycentric velocity and time correction.

[ascl:1807.017] ZBARYCORR: Barycentric redshift calculator

ZBARYCORR determines the barycentric redshift (zB) for a given star. It calculates the positions and velocities of solar system objects, applies the rotation, precession, nutation, and polar motion of the Earth, applies the stellar motion using the Markwardt library (ascl:1807.016), Shapiro delay, and light-travel term, and finally calculates the quantity zB—the barycentric correction independent of the measured redshift. A Python wrapper, BARYCORR (ascl:1807.018), is available.

[ascl:1807.016] MIDLL: Markwardt IDL Library

The Markwardt IDL Library contains routines for curve fitting and function minimization, including MPFIT (ascl:1208.019), statistical tests, and non-linear optimization (TNMIN); graphics programs including plotting three-dimensional data as a cube and fixed- or variable-width histograms; adaptive numerical integration (Quadpack), Chebyshev approximation and interpolation, and other mathematical tools; many ephemeris and timing routines; and array and set operations, such as computing the fast product of a large array, efficiently inserting or deleting elements in an array, and performing set operations on numbers and strings; and many other useful and varied routines.

[ascl:1807.015] CAESAR: Compact And Extended Source Automated Recognition

CAESAR extracts and parameterizes both compact and extended sources from astronomical radio interferometric maps. The processing pipeline is a series of stages that can run on multiple cores and processors. After local background and rms map computation, compact sources are extracted with flood-fill and blob finder algorithms, processed (selection + deblending), and fitted using a 2D gaussian mixture model. Extended source search is based on a pre-filtering stage, allowing image denoising, compact source removal and enhancement of diffuse emission, followed by a final segmentation. Different algorithms are available for image filtering and segmentation. The outputs delivered to the user include source fitted and shape parameters, regions and contours. Written in C++, CAESAR is designed to handle the large-scale surveys planned with the Square Kilometer Array (SKA) and its precursors.

[ascl:1807.014] SPEGID: Single-Pulse Event Group IDentification

SPEGID (Single-Pulse Event Group IDentification) identifies astrophysical pulse candidates as trial single-pulse event groups (SPEGs) by first applying Density Based Spatial Clustering of Applications with Noise (DBSCAN) on trial single-pulse events and then merging the clusters that fall within the expected DM (Dispersion Measure) and time span of astrophysical pulses. SPEGID also calculates the peak score for each SPEG in the S/N versus DM space to identify the expected peak-like shape in the signal-to-noise (S/N) ratio versus DM curve of astrophysical pulses. Additionally, SPEGID groups SPEGs that appear at a consistent DM and therefore are likely emitted from the same source. After running SPEGID, periocity.py can be used to find (or verify) the underlying periodicity among a group of SPEGs (i.e., astrophysical pulse candidates).

[ascl:1807.013] CLASSgal: Relativistic cosmological large scale structure code

CLASSgal computes large scale structure observables; it includes all relativistic corrections and computes both the power spectrum Cl(z1,z2) and the corresponding correlation function ξ(θ, z1, z2) of the matter density and the galaxy number fluctuations in linear perturbation theory. These quantities contain the full information encoded in the large scale matter distribution at the level of linear perturbation theory for Gaussian initial perturbations. CLASSgal is a modified version of CLASS (ascl:1106.020).

[ascl:1807.012] AngPow: Fast computation of accurate tomographic power spectra

AngPow computes the auto (z1 = z2) and cross (z1 ≠ z2) angular power spectra between redshift bins (i.e. Cℓ(z1,z2)). The developed algorithm is based on developments on the Chebyshev polynomial basis and on the Clenshaw-Curtis quadrature method. AngPow is flexible and can handle any user-defined power spectra, transfer functions, bias functions, and redshift selection windows. The code is fast enough to be embedded inside programs exploring large cosmological parameter spaces through the Cℓ(z1,z2) comparison with data.

[ascl:1807.011] nfield: Stochastic tool for QFT on inflationary backgrounds

nfield uses a stochastic formalism to compute the IR correlation functions of quantum fields during cosmic inflation in n-field dimensions. This is a necessary 1-loop resummation of the correlation functions to render them finite. The code supports the implementation of n-numbers of coupled test fields (energetically sub-dominant) as well as non-test fields.

[ascl:1807.010] THOR: Global Circulation Model for planetary atmospheres

THOR solves the three-dimensional nonhydrostatic Euler equations. The code implements an icosahedral grid for the poles where converging meridians lead to increasingly smaller time steps; irregularities in the grid are smoothed using spring dynamics. THOR is designed to run on graphics processing units (GPUs) and is part of the open-source Exoclimes Simulation Platform.

[ascl:1807.009] HELIOS: Radiative transfer code for exoplanetary atmospheres

HELIOS, a radiative transfer code, is constructed for studying exoplanetary atmospheres. The model atmospheres of HELIOS are one-dimensional and plane-parallel, and the equation of radiative transfer is solved in the two-stream approximation with non-isotropic scattering. Though HELIOS can be used alone, the opacity calculator HELIOS-K (ascl:1503.004) can be used with it to provide the molecular opacities.

[ascl:1807.008] HII-CHI-mistry_UV: Oxygen abundance and ionizionation parameters for ultraviolet emission lines

HII-CHI-mistry_UV derives oxygen and carbon abundances using the ultraviolet (UV) lines emitted by the gas phase ionized by massive stars. The code first fixes C/O using ratios of appropriate emission lines and, in a second step, calculates O/H and the ionization parameter from carbon lines in the UV. An optical version of this Python code, HII-CHI-mistry (ascl:1807.007), is also available.

[ascl:1807.007] HII-CHI-mistry: Oxygen abundance and ionizionation parameters for optical emission lines

HII-CHI-mistry calculates the oxygen abundance for gaseous nebulae ionized by massive stars using optical collisionally excited emission lines. This code takes the extinction-corrected emission line fluxes and, based on a Χ2 minimization on a photoionization models grid, determines chemical-abundances (O/H, N/O) and ionization parameters. An ultraviolet version of this Python code, HII-CHI-mistry-UV (ascl:1807.008), is also available.

[ascl:1807.006] pyqz: Emission line code

pyqz computes the values of log(Q) [the ionization parameter] and 12+log(O/H) [the oxygen abundance, either total or in the gas phase] for a given set of strong emission lines fluxes from HII regions. The log(Q) and 12+log(O/H) values are interpolated from a finite set of diagnostic line ratio grids computed with the MAPPINGS V code (ascl:1807.005). The grids used by pyqz are chosen to be flat, without wraps, to decouple the influence of log(Q) and 12+log(O/H) on the emission line ratios.

[ascl:1807.005] MAPPINGS V: Astrophysical plasma modeling code

MAPPINGS V is a update of the MAPPINGS code (ascl:1306.008) and provides new cooling function computations for optically thin plasmas based on the greatly expanded atomic data of the CHIANTI 8 database. The number of cooling and recombination lines has been expanded from ~2000 to over 80,000, and temperature-dependent spline-based collisional data have been adopted for the majority of transitions. The expanded atomic data set provides improved modeling of both thermally ionized and photoionized plasmas; the code is now capable of predicting detailed X-ray spectra of nonequilibrium plasmas over the full nonrelativistic temperature range, increasing its utility in cosmological simulations, in modeling cooling flows, and in generating accurate models for the X-ray emission from shocks in supernova remnants.

[ascl:1807.004] ARKCoS: Radial kernel convolution on the sphere

ARKCoS (Accelerated radial kernel convolution on the sphere) efficiently convolves pixelated maps on the sphere with radially symmetric kernels with compact support. It performs the convolution along isolatitude rings in Fourier space and integrates in longitudinal direction in pixel space. The computational costs scale linearly with the kernel support, making the method most beneficial for convolution with compact kernels. Typical applications include CMB beam smoothing, symmetric wavelet analyses, and point-source filtering operations. The software is written in C++/CUDA and provides two independent code paths to do the necessary computation either on conventional hardware (CPUs), or on graphics processing units (GPUs).

[ascl:1807.003] PyAutoLens: Strong lens modeling

PyAutoLens models and analyzes galaxy-scale strong gravitational lenses. This automated module suite simultaneously models the lens galaxy's light and mass while reconstructing the extended source galaxy on an adaptive pixel-grid. Source-plane discretization is amorphous, adapting its clustering and regularization to the intrinsic properties of the lensed source. The lens's light is fitted using a superposition of Sersic functions, allowing PyAutoLens to cleanly deblend its light from the source. Bayesian model comparison is used to automatically chose the complexity of the light and mass models. PyAutoLens provides accurate light, mass, and source profiles inferred for data sets representative of both existing Hubble imaging and future Euclid wide-field observations.

[ascl:1807.002] Warpfield: Winds And Radiation Pressure: Feedback Induced Expansion, colLapse and Dissolution

Warpfield (Winds And Radiation Pressure: Feedback Induced Expansion, colLapse and Dissolution) calculates shell dynamics and shell structure simultaneously for isolated massive clouds (≥105 M). This semi-analytic 1D feedback model scans a large range of physical parameters (gas density, star formation efficiency, and metallicity) to estimate escape fractions of ionizing radiation fesc, I, the minimum star formation efficiency ∊min required to drive an outflow, and recollapse time-scales for clouds that are not destroyed by feedback.

[ascl:1807.001] POLARIS: POLArized RadIation Simulator

POLARIS (POLArized RadIation Simulator) simulates the intensity and polarization of light emerging from analytical astrophysical models as well as complex magneto-hydrodynamic simulations on various grids. This 3D Monte-Carlo continuum radiative transfer code is written in C++ and is capable of performing dust heating, dust grain alignment, line radiative transfer, and synchrotron simulations to calculate synthetic intensity and polarization maps. The code makes use of a full set of physical quantities (density, temperature, velocity, magnetic field distribution, and dust grain properties as well as different sources of radiation) as input.

[ascl:1806.032] pwv_kpno: Modeling atmospheric absorption

pwv_kpno provides models for the atmospheric transmission due to precipitable water vapor (PWV) at user specified sites. Atmospheric transmission in the optical and near-infrared is highly dependent on the PWV column density along the line of sight. The pwv_kpno package uses published SuomiNet data in conjunction with MODTRAN models to determine the modeled, time-dependent atmospheric transmission between 3,000 and 12,000 Å. By default, models are provided for Kitt Peak National Observatory (KPNO). Additional locations can be added by the user for any of the hundreds of SuomiNet locations worldwide.

[ascl:1806.031] ASPIC: Accurate Slow-roll Predictions for Inflationary Cosmology

Aspic, written in modern Fortran, computes various observable quantities used in cosmology from definite single field inflationary models. It provides an efficient, extendable, and accurate way of comparing theoretical inflationary predictions with cosmological data and supports many (~70) models of inflation. The Hubble flow functions, observable quantities up to second order in the slow-roll approximation, are in direct correspondence with the spectral index, the tensor-to-scalar ratio and the running of the primordial power spectrum. The ASPIC library also provides the field potential, its first and second derivatives, the energy density at the end of inflation, the energy density at the end of reheating, and the field value (or e-fold value) at which the pivot scale crossed the Hubble radius during inflation. All these quantities are computed in a way which is consistent with the existence of a reheating phase.

[ascl:1806.030] foxi: Forecast Observations and their eXpected Information

Using information theory and Bayesian inference, the foxi Python package computes a suite of expected utilities given futuristic observations in a flexible and user-friendly way. foxi requires a set of n-dim prior samples for each model and one set of n-dim samples from the current data, and can calculate the expected ln-Bayes factor between models, decisiveness between models and its maximum-likelihood averaged equivalent, the decisivity, and the expected Kullback-Leibler divergence (i.e., the expected information gain of the futuristic dataset). The package offers flexible inputs and is designed for all-in-one script calculation or an initial cluster run then local machine post-processing, which should make large jobs quite manageable subject to resources and includes features such as LaTeX tables and plot-making for post-data analysis visuals and convenience of presentation.

[ascl:1806.029] EXO-NAILER: EXOplanet traNsits and rAdIal veLocity fittER

EXO-NAILER (EXOplanet traNsits and rAdIal veLocity fittER) efficiently fits exoplanet transit lightcurves, radial velocities (RVs) or both. The code handles data taken with different instruments. For RVs, a different center-of-mass velocity can be fitted for each instrument to account for offsets between them; if jitter is included, a different jitter term can also fitted for each instrument. For transits, a different photometric jitter can be fitted to each instrument as can different limb-darkening coefficients and different transit depths. In addition to general options that need to be set, EXO-NAILER also requires that photometry and radial velocity options be defined for each instrument.

[ascl:1806.028] PyMUSE: VLT/MUSE data analyzer

PyMUSE analyzes VLT/MUSE datacubes. The package is optimized to extract 1-D spectra of arbitrary spatial regions within the cube and also for producing images using photometric filters and customized masks. It is intended to provide the user the tools required for a complete analysis of a MUSE data set.

[ascl:1806.027] fcmaker: Creating ESO-compliant finding charts for Observing Blocks on p2

fcmaker creates astronomical finding charts for Observing Blocks (OBs) on the p2 web server from the European Southern Observatory (ESO). It automates the creation of ESO-compliant finding charts for Service Mode and/or Visitor Mode OBs at the Very Large Telescope (VLT). The design of the fcmaker finding charts, based on an intimate knowledge of VLT observing procedures, is fine-tuned to best support night time operations. As an automated tool, fcmaker also allows observers to independently check visually, for the first time, the observing sequence coded inside an OB. This includes, for example, the signs of telescope and position angle offsets.

[ascl:1806.026] BWED: Brane-world extra dimensions

Braneworld-extra-dimensions places constraints on the size of the AdS5 radius of curvature within the Randall-Sundrum brane-world model in light of the near-simultaneous detection of the gravitational wave event GW170817 and its optical counterpart, the short γ-ray burst event GRB170817A. The code requires a (supplied) patch to the Montepython cosmological MCMC sampler (ascl:1805.027) to sample the posterior distribution of the 4-dimensional parameter space in VBV17 and obtain constraints on the parameters.

[ascl:1806.025] BRATS: Broadband Radio Astronomy ToolS

BRATS (Broadband Radio Astronomy ToolS) provides tools for the spectral analysis of broad-bandwidth radio data and legacy support for narrowband telescopes. It can fit models of spectral ageing on small spatial scales, offers automatic selection of regions based on user parameters (e.g. signal to noise), and automatic determination of the best-fitting injection index. It includes statistical testing, including Chi-squared, error maps, confidence levels and binning of model fits, and can map spectral index as a function of position. It also provides the ability to reconstruct sources at any frequency for a given model and parameter set, subtract any two FITS images and output residual maps, easily combine and scale FITS images in the image plane, and resize radio maps.

[ascl:1806.024] RMextract: Ionospheric Faraday Rotation calculator

RMextract calculates Ionospheric Faraday Rotation for a given epoch, location and line of sight. This Python code extracts TEC, vTEC, Earthmagnetic field and Rotation Measures from GPS and WMM data for radio interferometry observations.

[ascl:1806.023] Spheral++: Coupled hydrodynamical and gravitational numerical simulations

Spheral++ provides a steerable parallel environment for performing coupled hydrodynamical and gravitational numerical simulations. Hydrodynamics and gravity are modeled using particle-based methods (SPH and N-Body). It uses an Adaptive Smoothed Particle Hydrodynamics (ASPH) algorithm, provides a total energy conserving compatible hydro mode, and performs fluid and solid material modeling and damage and fracture modeling in solids.

[ascl:1806.022] Keras: The Python Deep Learning library

Keras is a high-level neural networks API written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It focuses on enabling fast experimentation.

[ascl:1806.021] LASR: Linear Algorithm for Significance Reduction

LASR removes stellar variability in the light curves of δ-Scuti and similar stars. It subtracts oscillations from a time series by minimizing their statistical significance in frequency space.

[ascl:1806.020] exoinformatics: Compute the entropy of a planetary system's size-ordering

exoinformatics computes the entropy of a planetary system's size ordering using three different entropy methods: tally-scores, integral path, and change points.

[ascl:1806.019] SYGMA: Modeling stellar yields for galactic modeling

SYGMA (Stellar Yields for Galactic Modeling Applications) follows the ejecta of simple stellar populations as a function of time to model the enrichment and feedback from simple stellar populations. It is the basic building block of the galaxy code One-zone Model for the Evolution of GAlaxies (OMEGA, ascl:1806.018) and is part of the NuGrid Python Chemical Evolution Environment (NuPyCEE, ascl:1610.015). Stellar yields of AGB and massive stars are calculated with the same nuclear physics and are provided by the NuGrid collaboration.

[ascl:1806.018] OMEGA: One-zone Model for the Evolution of GAlaxies

OMEGA (One-zone Model for the Evolution of GAlaxies) calculates the global chemical evolution trends of galaxies. From an input star formation history, it uses SYGMA to create as a function of time multiple simple stellar populations with different masses, ages, and initial compositions. OMEGA offers several prescriptions for modeling the star formation efficiency and the evolution of galactic inflows and outflows. OMEGA is part of the NuGrid (ascl:1610.015) chemical evolution package.

[ascl:1806.017] RadFil: Radial density profile builder for interstellar filaments

RadFil is a radial density profile building and fitting tool for interstellar filaments. The software uses an image array and (in most cases) a boolean mask array that delineates the boundary of the filament to build and fit a radial density profile for the filaments.

[ascl:1806.016] DirectDM-py: Dark matter direct detection

DirectDM, written in Python, takes the Wilson coefficients of relativistic operators that couple DM to the SM quarks, leptons, and gauge bosons and matches them onto a non-relativistic Galilean invariant EFT in order to calculate the direct detection scattering rates. A Mathematica implementation of DirectDM is also available (ascl:1806.015).

[ascl:1806.015] DirectDM-mma: Dark matter direct detection

The Mathematica code DirectDM takes the Wilson coefficients of relativistic operators that couple DM to the SM quarks, leptons, and gauge bosons and matches them onto a non-relativistic Galilean invariant EFT in order to calculate the direct detection scattering rates. A Python implementation of DirectDM is also available (ascl:1806.016).

[ascl:1806.014] pile-up: Monte Carlo simulations of star-disk torques on hot Jupiters

The pile-up gnuplot script generates a Monte Carlo simulation with a selectable number of randomized drawings (1000 by default, ~1min on a modern laptop). For each realization, the script calculates the torque acting on a hot Jupiter around a young, solar-type star as a function of the star-planet distance. The total torque on the planet is composed of the disk torque in the type II migration regime (that is, the planet is assumed to have opened up a gap in the disk) and of the stellar tidal torque. The model has four free parameters, which are drawn from a normal or lognormal distribution: (1) the disk's gas surface density at 1 astronomical unit, (2) the magnitude of tidal dissipation within the star, (3) the disk's alpha viscosity parameter, and (4) and the mean molecular weight of the gas in the disk midplane. For each realization, the total torque is screened for a distance at which it becomes zero. If present, then this distance would represent a tidal migration barrier to the planet. In other words, the planet would stop migrating. This location is added to a histogram on top of the main torque-over-distance panel and the realization is counted as one case that contributes to the overall survival rate of hot Jupiters. Finally, the script generates an output file (PDF by default) and prints the hot Jupiter survival rate for the assumed parameterization of the star-planet-disk system.

[ascl:1806.013] SpS: Single-pulse Searcher

The presence of human-made interference mimicking the behavior of celestial radio pulses is a major challenge when searching for radio pulses emitted on millisecond timescales by celestial radio sources such as pulsars and fast radio bursts due to the highly imbalanced samples. Single-pulse Searcher (SpS) reduces the presence of radio interference when processing standard output from radio single-pulse searches to produce diagnostic plots useful for selecting good candidates. The modular software allows modifications for specific search characteristics. LOTAAS Single-pulse Searcher (L-SpS) is an implementation of different features of the software (such as a machine-learning approach) developed for a particular study: the LOFAR Tied-Array All-Sky Survey (LOTAAS).

[ascl:1806.012] WDEC: White Dwarf Evolution Code

WDEC (White Dwarf Evolution Code), written in Fortran, offers a fast and fairly easy way to produce models of white dwarfs. The code evolves hot (~100,000 K) input models down to a chosen effective temperature by relaxing the models to be solutions of the equations of stellar structure. The code can also be used to obtain g-mode oscillation modes for the models.

[ascl:1806.011] P2DFFT: Parallelized technique for measuring galactic spiral arm pitch angles

P2DFFT is a parallelized version of 2DFFT (ascl:1608.015). It isolates and measures the spiral arm pitch angle of galaxies. The code allows direct input of FITS images, offers the option to output inverse Fourier transform FITS images, and generates idealized logarithmic spiral test images of a specified size that have 1 to 6 arms with pitch angles of -75 degrees to 75 degrees​​. Further, it can output Fourier amplitude versus inner radius and pitch angle versus inner radius for each Fourier component (m = 0 to m = 6), and calculates the Fourier amplitude weighted mean pitch angle across m = 1 to m = 6 versus inner radius.

[ascl:1806.010] SpaghettiLens: Web-based gravitational lens modeling tool

SpaghettiLens allows citizen scientists to model gravitational lenses collaboratively; the software should also be easily adaptable to any other, reasonably similar problem. It lets volunteers execute a computer intensive task that cannot be easily executed client side and relies on citizen scientists collaborating. SpaghettiLens makes survey data available to citizen scientists, manages the model configurations generated by the volunteers, stores the resulting model configuration, and delivers the actual model. A model can be shared and discussed with other volunteers and revised, and new child models can be created, resulting in a branching version tree of models that explore different possibilities. Scientists can choose a collection of models; discussion among volunteers and scientists prune the tree to determine which models will receive further analysis.

[ascl:1806.009] GLASS: Parallel, free-form gravitational lens modeling tool and framework

GLASS models strong gravitational lenses. It produces an ensemble of possible models that fit the observed input data and conform to certain constraints specified by the user. GLASS makes heavy use of the numerical routines provided by the numpy and scipy packages as well as the linear programming package GLPK. This latter package, and its Python interface, is provided with GLASS and installs automatically in the GLASS build directory.

[ascl:1806.008] gsf: galactic structure finder

gsf applies Gaussian Mixture Models in the stellar kinematic space of normalized angular momentum and binding energy on NIHAO high resolution galaxies to separate the stars into multiple components. The gsf analysis package assumes that the simulation snapshot has been pre-processed with a halo finder. It is based on pynbody (ascl:1305.002) and the scikit-learnpython package for Machine Learning; after loading, orienting, and transforming a simulation snapshot to physical units, it runs the clustering algorithm and performs the direct N-body gravity force using all the particles in the given halo.

[ascl:1806.007] PyAMOR: AMmOnia data Reduction

PyAMOR models spectra of low level ammonia transitions (between (J,K)=(1,1) and (5,5)) and derives parameters such as intrinsic linewidth, optical depth, and rotation temperature. For low S/N or low spectral resolution data, the code uses cross-correlation between a model and a regridded spectrum (e.g. 10 times smaller channel width) to find the velocity, then fixes it and runs the minimization process. For high S/N data, PyAMOR runs with the velocity as a free parameter.

[ascl:1806.006] QE: Quantum opEn-Source Package for Research in Electronic Structure, Simulation, and Optimization

Quantum ESPRESSO (opEn-Source Package for Research in Electronic Structure, Simulation, and Optimization) is an integrated suite of codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials. QE performs ground-state calculations such as self-consistent total energies, forces, stresses and Kohn-Sham orbitals, Car-Parrinello and Born-Oppenheimer molecular dynamics, and quantum transport such as ballistic transport, coherent transport from maximally localized Wannier functions, and Kubo-Greenwood electrical conductivity. It can also determine spectroscopic properties and examine time-dependent density functional perturbations and electronic excitations, and has a wide range of other functions.

[ascl:1806.005] Indri: Pulsar population synthesis toolset

Indri models the population of single (not in binary or hierarchical systems) neutron stars. Given a starting distribution of parameters (birth place, velocity, magnetic field, and period), the code moves a set of stars through the time (by evolving spin period and magnetic field) and the space (by propagating through the Galactic potential). Upon completion of the evolution, a set of observables is computed (radio flux, position, dispersion measure) and compared with a radio survey such as the Parkes Multibeam Survey. The models' parameters are optimised by using the Markov Chain Monte Carlo technique.

[ascl:1806.004] WiseView: Visualizing motion and variability of faint WISE sources

WiseView renders image blinks of Wide-field Infrared Survey Explorer (WISE) coadds spanning a multi-year time baseline in a browser. The software allows for easy visual identification of motion and variability for sources far beyond the single-frame detection limit, a key threshold not surmounted by many studies. WiseView transparently gathers small image cutouts drawn from many terabytes of unWISE coadds, facilitating access to this large and unique dataset. Users need only input the coordinates of interest and can interactively tune parameters including the image stretch, colormap and blink rate. WiseView was developed in the context of the Backyard Worlds: Planet 9 citizen science project, and has enabled hundreds of brown dwarf candidate discoveries by citizen scientists and professional astronomers.

[ascl:1806.003] pyZELDA: Python code for Zernike wavefront sensors

pyZELDA analyzes data from Zernike wavefront sensors dedicated to high-contrast imaging applications. This modular software was originally designed to analyze data from the ZELDA wavefront sensor prototype installed in VLT/SPHERE; simple configuration files allow it to be extended to support several other instruments and testbeds. pyZELDA also includes simple simulation tools to measure the theoretical sensitivity of a sensor and to compare it to other sensors.

[ascl:1806.002] BHDD: Primordial black hole binaries code

BHDD (BlackHolesDarkDress) simulates primordial black hole (PBH) binaries that are clothed in dark matter (DM) halos. The software uses N-body simulations and analytical estimates to follow the evolution of PBH binaries formed in the early Universe.

[ascl:1806.001] feets: feATURE eXTRACTOR FOR tIME sERIES

feets characterizes and analyzes light-curves from astronomical photometric databases for modelling, classification, data cleaning, outlier detection and data analysis. It uses machine learning algorithms to determine the numerical descriptors that characterize and distinguish the different variability classes of light-curves; these range from basic statistical measures such as the mean or standard deviation to complex time-series characteristics such as the autocorrelation function. The library is not restricted to the astronomical field and could also be applied to any kind of time series. This project is a derivative work of FATS (ascl:1711.017).

[ascl:1805.032] PyCCF: Python Cross Correlation Function for reverberation mapping studies

PyCCF emulates a Fortran program written by B. Peterson for use with reverberation mapping. The code cross correlates two light curves that are unevenly sampled using linear interpolation and measures the peak and centroid of the cross-correlation function. In addition, it is possible to run Monto Carlo iterations using flux randomization and random subset selection (RSS) to produce cross-correlation centroid distributions to estimate the uncertainties in the cross correlation results.

[ascl:1805.031] CubiCal: Suite for fast radio interferometric calibration

CubiCal implements several accelerated gain solvers which exploit complex optimization for fast radio interferometric gain calibration. The code can be used for both direction-independent and direction-dependent self-calibration. CubiCal is implemented in Python and Cython, and multiprocessing is fully supported.

A successor to CubiCal, QuartiCal (ascl:2305.006), is available.

[ascl:1805.030] PyCBC: Gravitational-wave data analysis toolkit

PyCBC analyzes data from gravitational-wave laser interferometer detectors, finds signals, and studies their parameters. It contains algorithms that can detect coalescing compact binaries and measure the astrophysical parameters of detected sources. PyCBC was used in the first direct detection of gravitational waves by LIGO and is used in the ongoing analysis of LIGO and Virgo data.

[ascl:1805.029] DeepMoon: Convolutional neural network trainer to identify moon craters

DeepMoon trains a convolutional neural net using data derived from a global digital elevation map (DEM) and catalog of craters to recognize craters on the Moon. The TensorFlow-based pipeline code is divided into three parts. The first generates a set images of the Moon randomly cropped from the DEM, with corresponding crater positions and radii. The second trains a convnet using this data, and the third validates the convnet's predictions.

[ascl:1805.028] SP_Ace: Stellar Parameters And Chemical abundances Estimator

SP_Ace (Stellar Parameters And Chemical abundances Estimator) estimates the stellar parameters Teff, log g, [M/H], and elemental abundances. It employs 1D stellar atmosphere models in Local Thermodynamic Equilibrium (LTE). The code is highly automated and suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R = 2000-20 000). A web service for calculating these values with the software is also available.

[ascl:1805.027] MontePython 3: Parameter inference code for cosmology

MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.

[ascl:1805.026] PySE: Python Source Extractor for radio astronomical images

PySE finds and measures sources in radio telescope images. It is run with several options, such as the detection threshold (a multiple of the local noise), grid size, and the forced clean beam fit, followed by a list of input image files in standard FITS or CASA format. From these, PySe provides a list of found sources; information such as the calculated background image, source list in different formats (e.g. text, region files importable in DS9), and other data may be saved. PySe can be integrated into a pipeline; it was originally written as part of the LOFAR Transient Detection Pipeline (TraP, ascl:1412.011).

[ascl:1805.025] GLACiAR: GaLAxy survey Completeness AlgoRithm

GLACiAR (GaLAxy survey Completeness AlgoRithm) estimates the completeness and selection functions in galaxy surveys. Tailored for multiband imaging surveys aimed at searching for high-redshift galaxies through the Lyman Break technique, the code can nevertheless be applied broadly. GLACiAR generates artificial galaxies that follow Sérsic profiles with different indexes and with customizable size, redshift and spectral energy distribution properties, adds them to input images, and measures the recovery rate.

[ascl:1805.024] ASTROPOP: ASTROnomical Polarimetry and Photometry pipeline

AstroPoP reduces almost any CCD photometry and image polarimetry data. For photometry reduction, the code performs source finding, aperture and PSF photometry, astrometry calibration using different automated and non-automated methods and automated source identification and magnitude calibration based on online and local catalogs. For polarimetry, the code resolves linear and circular Stokes parameters produced by image beam splitter or polarizer polarimeters. In addition to the modular functions, ready-to-use pipelines based in configuration files and header keys are also provided with the code. AstroPOP was initially developed to reduce the IAGPOL polarimeter data installed at Observatório Pico dos Dias (Brazil).

[ascl:1805.023] PROM7: 1D modeler of solar filaments or prominences

PROM7 is an update of PROM4 (ascl:1306.004) and computes simple models of solar prominences and filaments using Partial Radiative Distribution (PRD). The models consist of plane-parallel slabs standing vertically above the solar surface. Each model is defined by 5 parameters: temperature, density, geometrical thickness, microturbulent velocity and height above the solar surface. It solves the equations of radiative transfer, statistical equilibrium, ionization and pressure equilibria, and computes electron and hydrogen level population and hydrogen line profiles. Moreover, the code treats calcium atom which is reduced to 3 ionization states (Ca I, Ca II, CA III). Ca II ion has 5 levels which are useful for computing 2 resonance lines (H and K) and infrared triplet (to 8500 A).

[ascl:1805.022] BCcodes: Bolometric Corrections and Synthetic Stellar Photometry

BCcodes computes bolometric corrections and synthetic colors in up to 5 filters for input values of the stellar parameters Teff, log(g), [Fe/H], E(B-V) and [alpha/Fe].

[ascl:1805.021] PampelMuse: Crowded-field 3D spectroscopy

PampelMuse analyzes integral-field spectroscopic observations of crowded stellar fields and provides several subroutines to perform the individual steps of the data analysis. All analysis steps assume that the IFS data has been properly reduced and that all the instrumental artifacts have been removed. PampelMuse is designed to correctly handle IFS data regardless of which instrument was used to observe the data. In addition to the actual data, the software also requires an estimate of the variances for the analysis; optionally, it can use a bad pixel mask. The analysis relies on the presence of a reference catalogue, containing coordinates and magnitudes of the stars in and around the observed field.

[ascl:1805.020] SWIFT: SPH With Inter-dependent Fine-grained Tasking

SWIFT runs cosmological simulations on peta-scale machines for solving gravity and SPH. It uses the Fast Multipole Method (FMM) to calculate gravitational forces between nearby particles, combining these with long-range forces provided by a mesh that captures both the periodic nature of the calculation and the expansion of the simulated universe. SWIFT currently uses a single fixed but time-variable softening length for all the particles. Many useful external potentials are also available, such as galaxy haloes or stratified boxes that are used in idealised problems. SWIFT implements a standard LCDM cosmology background expansion and solves the equations in a comoving frame; equations of state of dark-energy evolve with scale-factor. The structure of the code allows implementation for modified-gravity solvers or self-interacting dark matter schemes to be implemented. Many hydrodynamics schemes are implemented in SWIFT and the software allows users to add their own.

[ascl:1805.019] HENDRICS: High ENergy Data Reduction Interface from the Command Shell

HENDRICS, a rewrite and update to MaLTPyNT (ascl:1502.021), contains command-line scripts based on Stingray (ascl:1608.001) to perform a quick-look (spectral-)timing analysis of X-ray data, treating the gaps in the data due, e.g., to occultation from the Earth or passages through the SAA, properly. Despite its original main focus on NuSTAR, HENDRICS can perform standard aperiodic timing analysis on X-ray data from, in principle, any other satellite, and its features include power density and cross spectra, time lags, pulsar searches with the Epoch folding and the Z_n^2 statistics, color-color and color-intensity diagrams. The periodograms produced by HENDRICS (such as a power density spectrum or a cospectrum) can be saved in a format compatible with XSPEC (ascl:9910.005) or ISIS (ascl:1302.002).

[ascl:1805.018] CUBE: Information-optimized parallel cosmological N-body simulation code

CUBE, written in Coarray Fortran, is a particle-mesh based parallel cosmological N-body simulation code. The memory usage of CUBE can approach as low as 6 bytes per particle. Particle pairwise (PP) force, cosmological neutrinos, spherical overdensity (SO) halofinder are included.

[ascl:1805.017] SNSEDextend: SuperNova Spectral Energy Distributions extrapolation toolkit

SNSEDextend extrapolates core-collapse and Type Ia Spectral Energy Distributions (SEDs) into the UV and IR for use in simulations and photometric classifications. The user provides a library of existing SED templates (such as those in the authors' SN SED Repository) along with new photometric constraints in the UV and/or NIR wavelength ranges. The software then extends the existing template SEDs so their colors match the input data at all phases. SNSEDextend can also extend the SALT2 spectral time-series model for Type Ia SN for a "first-order" extrapolation of the SALT2 model components, suitable for use in survey simulations and photometric classification tools; as the code does not do a rigorous re-training of the SALT2 model, the results should not be relied on for precision applications such as light curve fitting for cosmology.

[ascl:1805.016] xspec_emcee: XSPEC-friendly interface for the emcee package

XSPEC_EMCEE is an XSPEC-friendly interface for emcee (ascl:1303.002). It carries out MCMC analyses of X-ray spectra in the X-ray spectral fitting program XSPEC (ascl:9910.005). It can run multiple xspec processes simultaneously, speeding up the analysis, and can switch to parameterizing norm
parameters in log space.

[ascl:1805.015] BinMag: Widget for comparing stellar observed with theoretical spectra

BinMag examines theoretical stellar spectra computed with Synth/SynthMag/Synmast/Synth3/SME spectrum synthesis codes and compare them to observations. An IDL widget program, BinMag applies radial velocity shift and broadening to the theoretical spectra to account for the effects of stellar rotation, radial-tangential macroturbulence, and instrumental smearing. The code can also simulate spectra of spectroscopic binary stars by appropriate coaddition of two synthetic spectra. Additionally, BinMag can be used to measure equivalent width, fit line profile shapes with analytical functions, and to automatically determine radial velocity and broadening parameters. BinMag interfaces with the Synth3 (ascl:1212.010) and SME (ascl:1202.013) codes, allowing the user to determine chemical abundances and stellar atmospheric parameters from the observed spectra.

[ascl:1805.014] OSS: OSSOS Survey Simulator

Comparing properties of discovered trans-Neptunian Objects (TNOs) with dynamical models is impossible due to the observational biases that exist in surveys. The OSSOS Survey Simulator takes an intrinsic orbital model (from, for example, the output of a dynamical Kuiper belt emplacement simulation) and applies the survey biases, so the biased simulated objects can be directly compared with real discoveries.

[ascl:1805.012] Arcmancer: Geodesics and polarized radiative transfer library

Arcmancer computes geodesics and performs polarized radiative transfer in user-specified spacetimes. The library supports Riemannian and semi-Riemannian spaces of any dimension and metric; it also supports multiple simultaneous coordinate charts, embedded geometric shapes, local coordinate systems, and automatic parallel propagation. Arcmancer can be used to solve various problems in numerical geometry, such as solving the curve equation of motion using adaptive integration with configurable tolerances and differential equations along precomputed curves. It also provides support for curves with an arbitrary acceleration term and generic tools for generating ray initial conditions and performing parallel computation over the image, among other tools.

[ascl:1805.011] PoMiN: A Post-Minkowskian N-Body Solver

PoMiN is a lightweight N-body code based on the Post-Minkowskian N-body Hamiltonian of Ledvinka, Schafer, and Bicak, which includes General Relativistic effects up to first order in Newton's constant G, and all orders in the speed of light c. PoMiN is a single file written in C and uses a fourth-order Runge-Kutta integration scheme. PoMiN has also been written to handle an arbitrary number of particles (both massive and massless) with a computational complexity that scales as O(N^2).

[ascl:1805.010] StarSmasher: Smoothed Particle Hydrodynamics code for smashing stars and planets

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian particle method that approximates a continuous fluid as discrete nodes, each carrying various parameters such as mass, position, velocity, pressure, and temperature. In an SPH simulation the resolution scales with the particle density; StarSmasher is able to handle both equal-mass and equal number-density particle models. StarSmasher solves for hydro forces by calculating the pressure for each particle as a function of the particle's properties - density, internal energy, and internal properties (e.g. temperature and mean molecular weight). The code implements variational equations of motion and libraries to calculate the gravitational forces between particles using direct summation on NVIDIA graphics cards. Using a direct summation instead of a tree-based algorithm for gravity increases the accuracy of the gravity calculations at the cost of speed. The code uses a cubic spline for the smoothing kernel and an artificial viscosity prescription coupled with a Balsara Switch to prevent unphysical interparticle penetration. The code also implements an artificial relaxation force to the equations of motion to add a drag term to the calculated accelerations during relaxation integrations. Initially called StarCrash, StarSmasher was developed originally by Rasio.

[ascl:1805.009] STARBLADE: STar and Artefact Removal with a Bayesian Lightweight Algorithm from Diffuse Emission

STARBLADE (STar and Artefact Removal with a Bayesian Lightweight Algorithm from Diffuse Emission) separates superimposed point-like sources from a diffuse background by imposing physically motivated models as prior knowledge. The algorithm can also be used on noisy and convolved data, though performing a proper reconstruction including a deconvolution prior to the application of the algorithm is advised; the algorithm could also be used within a denoising imaging method. STARBLADE learns the correlation structure of the diffuse emission and takes it into account to determine the occurrence and strength of a superimposed point source.

[ascl:1805.008] AGAMA: Action-based galaxy modeling framework

The AGAMA library is a collection of tools for constructing and analyzing models of galaxies. It computes gravitational potential and forces, performs orbit integration and analysis, and can convert between position/velocity and action/angle coordinates. It offers a framework for finding best-fit parameters of a model from data and self-consistent multi-component galaxy models, and contains useful auxiliary utilities such as various mathematical routines. The core of the library is written in C++, and there are Python and Fortran interfaces. AGAMA may be used as a plugin for the stellar-dynamical software packages galpy (ascl:1411.008), AMUSE (ascl:1107.007), and NEMO (ascl:1010.051).

[ascl:1805.007] exocartographer: Constraining surface maps orbital parameters of exoplanets

exocartographer solves the exo-cartography inverse problem. This flexible forward-modeling framework, written in Python, retrieves the albedo map and spin geometry of a planet based on time-resolved photometry; it uses a Markov chain Monte Carlo method to extract albedo maps and planet spin and their uncertainties. Gaussian Processes use the data to fit for the characteristic length scale of the map and enforce smooth maps.

[ascl:1805.006] StePS: Stereographically Projected Cosmological Simulations

StePS (Stereographically Projected Cosmological Simulations) compactifies the infinite spatial extent of the Universe into a finite sphere with isotropic boundary conditions to simulate the evolution of the large-scale structure. This eliminates the need for periodic boundary conditions, which are a numerical convenience unsupported by observation and which modifies the law of force on large scales in an unrealistic fashion. StePS uses stereographic projection for space compactification and naive O(N2) force calculation; this arrives at a correlation function of the same quality more quickly than standard (tree or P3M) algorithms with similar spatial and mass resolution. The N2 force calculation is easy to adapt to modern graphics cards, hence StePS can function as a high-speed prediction tool for modern large-scale surveys.

[ascl:1805.005] 3DCORE: Forward modeling of solar storm magnetic flux ropes for space weather prediction

3DCORE forward models solar storm magnetic flux ropes called 3-Dimensional Coronal Rope Ejection (3DCORE). The code is able to produce synthetic in situ observations of the magnetic cores of solar coronal mass ejections sweeping over planets and spacecraft. Near Earth, these data are taken currently by the Wind, ACE and DSCOVR spacecraft. Other suitable spacecraft making these kind of observations carrying magnetometers in the solar wind were MESSENGER, Venus Express, MAVEN, and even Helios.

[ascl:1805.004] EARL: Exoplanet Analytic Reflected Lightcurves package

EARL (Exoplanet Analytic Reflected Lightcurves) computes the analytic form of a reflected lightcurve, given a spherical harmonic decomposition of the planet albedo map and the viewing and orbital geometries. The EARL Mathematica notebook allows rapid computation of reflected lightcurves, thus making lightcurve numerical experiments accessible.

[ascl:1805.003] lcps: Light curve pre-selection

lcps searches for transit-like features (i.e., dips) in photometric data. Its main purpose is to restrict large sets of light curves to a number of files that show interesting behavior, such as drops in flux. While lcps is adaptable to any format of time series, its I/O module is designed specifically for photometry of the Kepler spacecraft. It extracts the pre-conditioned PDCSAP data from light curves files created by the standard Kepler pipeline. It can also handle csv-formatted ascii files. lcps uses a sliding window technique to compare a section of flux time series with its surroundings. A dip is detected if the flux within the window is lower than a threshold fraction of the surrounding fluxes.

[ascl:1805.002] dftools: Distribution function fitting

dftools, written in R, finds the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a mass function (D=1), a mass-size distribution (D=2) or the mass-spin-morphology distribution (D=3). Unlike most common fitting approaches, this method accurately accounts for measurement in uncertainties and complex selection functions.

[ascl:1805.001] powerbox: Arbitrarily structured, arbitrary-dimension boxes and log-normal mocks

powerbox creates density grids (or boxes) with an arbitrary two-point distribution (i.e. power spectrum). The software works in any number of dimensions, creates Gaussian or Log-Normal fields, and measures power spectra of output fields to ensure consistency. The primary motivation for creating the code was the simple creation of log-normal mock galaxy distributions, but the methodology can be used for other applications.

[submitted] pydftools: Distribution function fitting in Python

pydftools is a pure-python port of the dftools R package (ascl:1805.002), which finds the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a MF (P=1), a mass-size distribution (P=2) or the mass-spin-morphology distribution (P=3). Unlike most common fitting approaches, this method accurately accounts for measurement in uncertainties and complex selection functions. Though this package imitates the dftools package quite closely while being as Pythonic as possible, it has not implemented 2D+ nor non-parametric.

[ascl:1804.026] KSTAT: KD-tree Statistics Package

KSTAT calculates the 2 and 3-point correlation functions in discreet point data. These include the two-point correlation function in 2 and 3-dimensions, the anisotripic 2PCF decomposed in either sigma-pi or Kazin's dist. mu projection. The 3-point correlation function can also work in anisotropic coordinates. The code is based on kd-tree structures and is parallelized using a mixture of MPI and OpenMP.

[ascl:1804.025] FastChem: An ultra-fast equilibrium chemistry

FastChem is an equilibrium chemistry code that calculates the chemical composition of the gas phase for given temperatures and pressures. Written in C++, it is based on a semi-analytic approach and is optimized for extremely fast and accurate calculations.

[ascl:1804.024] LFlGRB: Luminosity function of long gamma-ray bursts

LFlGRB models the luminosity function (LF) of long Gamma Ray Bursts (lGRBs) by using a sample of Swift and Fermi lGRBs to re-derive the parameters of the Yonetoku correlation and self-consistently estimate pseudo-redshifts of all the bursts with unknown redshifts. The GRB formation rate is modeled as the product of the cosmic star formation rate and a GRB formation efficiency for a given stellar mass.

[ascl:1804.023] LFsGRB: Binary neutron star merger rate via the luminosity function of short gamma-ray bursts

LFsGRB models the luminosity function (LF) of short Gamma Ray Bursts (sGRBs) by using the available catalog data of all short GRBs (sGRBs) detected till 2017 October, estimating the luminosities via pseudo-redshifts obtained from the Yonetoku correlation, and then assuming a standard delay distribution between the cosmic star formation rate and the production rate of their progenitors. The data are fit well both by exponential cutoff powerlaw and broken powerlaw models. Using the derived parameters of these models along with conservative values in the jet opening angles seen from afterglow observations, the true rate of short GRBs is derived. Assuming a short GRB is produced from each binary neutron star merger (BNSM), the rate of gravitational wave (GW) detections from these mergers are derived for the past, present and future configurations of the GW detector networks.

[ascl:1804.022] UniDAM: Unified tool to estimate Distances, Ages, and Masses

UniDAM obtains a homogenized set of stellar parameters from spectrophotometric data of different surveys. Parallax and extinction data can be incorporated into the isochrone fitting method used in UniDAM to reduce distance and age estimate uncertainties for TGAS stars for distances up to 1 kpc and decrease distance Gaia end-of-mission parallax uncertainties by about a factor of 20 and age uncertainties by a factor of two for stars up to 10 kpc away from the Sun.

[ascl:1804.021] allantools: Allan deviation calculation

allantools calculates Allan deviation and related time & frequency statistics. The library is written in Python and has a GPL v3+ license. It takes input data that is either evenly spaced observations of either fractional frequency, or phase in seconds. Deviations are calculated for given tau values in seconds. Several noise generators for creating synthetic datasets are also included.

[ascl:1804.020] Agatha: Disentangling period signals from correlated noise in a periodogram framework

Agatha is a framework of periodograms to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. These periodograms are calculated by applying likelihood maximization and marginalization and combined in a self-consistent way. Agatha can be used to select the optimal noise model and to test the consistency of signals in time and can be applied to time series analyses in other astronomical and scientific disciplines. An interactive web implementation of the software is also available at http://agatha.herts.ac.uk/.

[ascl:1804.019] ViSBARD: Visual System for Browsing, Analysis and Retrieval of Data

ViSBARD interactively visualizes and analyzes space physics data. It provides an interactive integrated 3-D and 2-D environment to determine correlations between measurements across many spacecraft. It supports a variety of spacecraft data products and MHD models and is easily extensible to others. ViSBARD provides a way of visualizing multiple vector and scalar quantities as measured by many spacecraft at once. The data are displayed three-dimesionally along the orbits which may be displayed either as connected lines or as points. The data display allows the rapid determination of vector configurations, correlations between many measurements at multiple points, and global relationships. With the addition of magnetohydrodynamic (MHD) model data, this environment can also be used to validate simulation results with observed data, use simulated data to provide a global context for sparse observed data, and apply feature detection techniques to the simulated data.

[ascl:1804.018] 3DView: Space physics data visualizer

3DView creates visualizations of space physics data in their original 3D context. Time series, vectors, dynamic spectra, celestial body maps, magnetic field or flow lines, and 2D cuts in simulation cubes are among the variety of data representation enabled by 3DView. It offers direct connections to several large databases and uses VO standards; it also allows the user to upload data. 3DView's versatility covers a wide range of space physics contexts.

[ascl:1804.017] APPHi: Automated Photometry Pipeline for High Cadence Large Volume Data

APPHi (Automated Photometry Pipeline) carries out aperture and differential photometry of TAOS-II project data. It is computationally efficient and can be used also with other astronomical wide-field image data. APPHi works with large volumes of data and handles both FITS and HDF5 formats. Due the large number of stars that the software has to handle in an enormous number of frames, it is optimized to automatically find the best value for parameters to carry out the photometry, such as mask size for aperture, size of window for extraction of a single star, and the number of counts for the threshold for detecting a faint star. Although intended to work with TAOS-II data, APPHi can analyze any set of astronomical images and is a robust and versatile tool to performing stellar aperture and differential photometry.

[ascl:1804.016] surrkick: Black-hole kicks from numerical-relativity surrogate models

surrkick quickly and reliably extract recoils imparted to generic, precessing, black hole binaries. It uses a numerical-relativity surrogate model to obtain the gravitational waveform given a set of binary parameters, and from this waveform directly integrates the gravitational-wave linear momentum flux. This entirely bypasses the need of fitting formulae which are typically used to model black-hole recoils in astrophysical contexts.

[ascl:1804.015] NR-code: Nonlinear reconstruction code

NR-code applies nonlinear reconstruction to the dark matter density field in redshift space and solves for the nonlinear mapping from the initial Lagrangian positions to the final redshift space positions; this reverses the large-scale bulk flows and improves the precision measurement of the baryon acoustic oscillations (BAO) scale.

[ascl:1804.014] IMNN: Information Maximizing Neural Networks

This software trains artificial neural networks to find non-linear functionals of data that maximize Fisher information: information maximizing neural networks (IMNNs). As compressing large data sets vastly simplifies both frequentist and Bayesian inference, important information may be inadvertently missed. Likelihood-free inference based on automatically derived IMNN summaries produces summaries that are good approximations to sufficient statistics. IMNNs are robustly capable of automatically finding optimal, non-linear summaries of the data even in cases where linear compression fails: inferring the variance of Gaussian signal in the presence of noise, inferring cosmological parameters from mock simulations of the Lyman-α forest in quasar spectra, and inferring frequency-domain parameters from LISA-like detections of gravitational waveforms. In this final case, the IMNN summary outperforms linear data compression by avoiding the introduction of spurious likelihood maxima.

[ascl:1804.013] CAT-PUMA: CME Arrival Time Prediction Using Machine learning Algorithms

CAT-PUMA (CME Arrival Time Prediction Using Machine learning Algorithms) quickly and accurately predicts the arrival of Coronal Mass Ejections (CMEs) of CME arrival time. The software was trained via detailed analysis of CME features and solar wind parameters using 182 previously observed geo-effective partial-/full-halo CMEs and uses algorithms of the Support Vector Machine (SVM) to make its predictions, which can be made within minutes of providing the necessary input parameters of a CME.

[ascl:1804.012] Lenstronomy: Multi-purpose gravitational lens modeling software package

Lenstronomy is a multi-purpose open-source gravitational lens modeling python package. Lenstronomy reconstructs the lens mass and surface brightness distributions of strong lensing systems using forward modelling and supports a wide range of analytic lens and light models in arbitrary combination. The software is also able to reconstruct complex extended sources as well as point sources. Lenstronomy is flexible and numerically accurate, with a clear user interface that could be deployed across different platforms. Lenstronomy has been used to derive constraints on dark matter properties in strong lenses, measure the expansion history of the universe with time-delay cosmography, measure cosmic shear with Einstein rings, and decompose quasar and host galaxy light.

[ascl:1804.011] DESCQA: Synthetic Sky Catalog Validation Framework

The DESCQA framework provides rigorous validation protocols for assessing the quality of high-quality simulated sky catalogs in a straightforward and comprehensive way. DESCQA enables the inspection, validation, and comparison of an inhomogeneous set of synthetic catalogs via the provision of a common interface within an automated framework. An interactive web interface is also available at https://portal.nersc.gov/projecta/lsst/descqa/v2/.

[ascl:1804.010] SMERFS: Stochastic Markov Evaluation of Random Fields on the Sphere

SMERFS (Stochastic Markov Evaluation of Random Fields on the Sphere) creates large realizations of random fields on the sphere. It uses a fast algorithm based on Markov properties and fast Fourier Transforms in 1d that generates samples on an n X n grid in O(n2 log n) and efficiently derives the necessary conditional covariance matrices.

[ascl:1804.009] orbit-estimation: Fast orbital parameters estimator

orbit-estimation tests and evaluates the Stäckel approximation method for estimating orbit parameters in galactic potentials. It relies on the approximation of the Galactic potential as a Stäckel potential, in a prolate confocal coordinate system, under which the vertical and horizontal motions decouple. By solving the Hamilton Jacobi equations at the turning points of the horizontal and vertical motions, it is possible to determine the spatial boundary of the orbit, and hence calculate the desired orbit parameters.

[ascl:1804.008] EGG: Empirical Galaxy Generator

The Empirical Galaxy Generator (EGG) generates fake galaxy catalogs and images with realistic positions, morphologies and fluxes from the far-ultraviolet to the far-infrared. The catalogs are generated by egg-gencat and stored in binary FITS tables (column oriented). Another program, egg-2skymaker, is used to convert the generated catalog into ASCII tables suitable for ingestion by SkyMaker (ascl:1010.066) to produce realistic high resolution images (e.g., Hubble-like), while egg-gennoise and egg-genmap can be used to generate the low resolution images (e.g., Herschel-like). These tools can be used to test source extraction codes, or to evaluate the reliability of any map-based science (stacking, dropout identification, etc.).

[ascl:1804.007] chroma: Chromatic effects for LSST weak lensing

Chroma investigates biases originating from two chromatic effects in the atmosphere: differential chromatic refraction (DCR), and wavelength dependence of seeing. These biases arise when using the point spread function (PSF) measured with stars to estimate the shapes of galaxies with different spectral energy distributions (SEDs) than the stars.

[ascl:1804.006] ProFound: Source Extraction and Application to Modern Survey Data

ProFound detects sources in noisy images, generates segmentation maps identifying the pixels belonging to each source, and measures statistics like flux, size, and ellipticity. These inputs are key requirements of ProFit (ascl:1612.004), our galaxy profiling package; these two packages used in unison semi-automatically profile large samples of galaxies. The key novel feature introduced in ProFound is that all photometry is executed on dilated segmentation maps that fully contain the identifiable flux, rather than using more traditional circular or ellipse-based photometry. Also, to be less sensitive to pathological segmentation issues, the de-blending is made across saddle points in flux. ProFound offers good initial parameter estimation for ProFit, and also segmentation maps that follow the sometimes complex geometry of resolved sources, whilst capturing nearly all of the flux. A number of bulge-disc decomposition projects are already making use of the ProFound and ProFit pipeline.

[ascl:1804.005] DaCHS: Data Center Helper Suite

DaCHS, the Data Center Helper Suite, is an integrated package for publishing astronomical data sets to the Virtual Observatory. Network-facing, it speaks the major VO protocols (SCS, SIAP, SSAP, TAP, Datalink, etc). Operator-facing, many input formats, including FITS/WCS, ASCII files, and VOTable, can be processed to publication-ready data. DaCHS puts particular emphasis on integrated metadata handling, which facilitates a tight integration with the VO's Registry

[ascl:1804.004] AstroCV: Astronomy computer vision library

AstroCV processes and analyzes big astronomical datasets, and is intended to provide a community repository of high performance Python and C++ algorithms used for image processing and computer vision. The library offers methods for object recognition, segmentation and classification, with emphasis in the automatic detection and classification of galaxies.

[ascl:1804.003] DPPP: Default Pre-Processing Pipeline

DPPP (Default Pre-Processing Pipeline, also referred to as NDPPP) reads and writes radio-interferometric data in the form of Measurement Sets, mainly those that are created by the LOFAR telescope. It goes through visibilities in time order and contains standard operations like averaging, phase-shifting and flagging bad stations. Between the steps in a pipeline, the data is not written to disk, making this tool suitable for operations where I/O dominates. More advanced procedures such as gain calibration are also included. Other computing steps can be provided by loading a shared library; currently supported external steps are the AOFlagger (ascl:1010.017) and a bridge that enables loading python steps.

[ascl:1804.002] ipole: Semianalytic scheme for relativistic polarized radiative transport

ipole is a ray-tracing code for covariant, polarized radiative transport particularly useful for modeling Event Horizon Telescope sources, though may also be used for other relativistic transport problems. The code extends the ibothros scheme for covariant, unpolarized transport using two representations of the polarized radiation field: in the coordinate frame, it parallel transports the coherency tensor, and in the frame of the plasma, it evolves the Stokes parameters under emission, absorption, and Faraday conversion. The transport step is as spacetime- and coordinate- independent as possible; the emission, absorption, and Faraday conversion step is implemented using an analytic solution to the polarized transport equation with constant coefficients. As a result, ipole is stable, efficient, and produces a physically reasonable solution even for a step with high optical depth and Faraday depth.

[ascl:1804.001] ASERA: A Spectrum Eye Recognition Assistant

ASERA, ASpectrum Eye Recognition Assistant, aids in quasar spectral recognition and redshift measurement and can also be used to recognize various types of spectra of stars, galaxies and AGNs (Active Galactic Nucleus). This interactive software allows users to visualize observed spectra, superimpose template spectra from the Sloan Digital Sky Survey (SDSS), and interactively access related spectral line information. ASERA is an efficient and user-friendly semi-automated toolkit for the accurate classification of spectra observed by LAMOST (the Large Sky Area Multi-object Fiber Spectroscopic Telescope) and is available as a standalone Java application and as a Java applet. The software offers several functions, including wavelength and flux scale settings, zoom in and out, redshift estimation, and spectral line identification.

[ascl:1803.015] RAPTOR: Imaging code for relativistic plasmas in strong gravity

RAPTOR produces accurate images, animations, and spectra of relativistic plasmas in strong gravity by numerically integrating the equations of motion of light rays and performing time-dependent radiative transfer calculations along the rays. The code is compatible with any analytical or numerical spacetime, is hardware-agnostic and may be compiled and run on both GPUs and CPUs. RAPTOR is useful for studying accretion models of supermassive black holes, performing time-dependent radiative transfer through general relativistic magneto-hydrodynamical (GRMHD) simulations and investigating the expected observational differences between the so-called fastlight and slow-light paradigms.

[ascl:1803.014] ExoCross: Spectra from molecular line lists

ExoCross generates spectra and thermodynamic properties from molecular line lists in ExoMol, HITRAN, or several other formats. The code is parallelized and also shows a high degree of vectorization; it works with line profiles such as Doppler, Lorentzian and Voigt and supports several broadening schemes. ExoCross is also capable of working with the recently proposed method of super-lines. It supports calculations of lifetimes, cooling functions, specific heats and other properties. ExoCross converts between different formats, such as HITRAN, ExoMol and Phoenix, and simulates non-LTE spectra using a simple two-temperature approach. Different electronic, vibronic or vibrational bands can be simulated separately using an efficient filtering scheme based on the quantum numbers.

[ascl:1803.013] optBINS: Optimal Binning for histograms

optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.

[ascl:1803.012] LWPC: Long Wavelength Propagation Capability

Long Wavelength Propagation Capability (LWPC), written as a collection of separate programs that perform unique actions, generates geographical maps of signal availability for coverage analysis. The program makes it easy to set up these displays by automating most of the required steps. The user specifies the transmitter location and frequency, the orientation of the transmitting and receiving antennae, and the boundaries of the operating area. The program automatically selects paths along geographic bearing angles to ensure that the operating area is fully covered. The diurnal conditions and other relevant geophysical parameters are then determined along each path. After the mode parameters along each path are determined, the signal strength along each path is computed. The signal strength along the paths is then interpolated onto a grid overlying the operating area. The final grid of signal strength values is used to display the signal-strength in a geographic display. The LWPC uses character strings to control programs and to specify options. The control strings have the same meaning and use among all the programs.

[ascl:1803.011] ExtLaw_H18: Extinction law code

ExtLaw_H18 generates the extinction law between 0.8 - 2.2 microns. The law is derived using the Westerlund 1 (Wd1) main sequence (A_Ks ~ 0.6 mag) and Arches cluster field Red Clump at the Galactic Center (A_Ks ~ 2.7 mag). To derive the law a Wd1 cluster age of 5 Myr is assumed, though changing the cluster age between 4 Myr -- 7 Myr has no effect on the law. This extinction law can be applied to highly reddened stellar populations that have similar foreground material as Wd1 and the Arches RC, namely dust from the spiral arms of the Milky Way in the Galactic Plane.

[ascl:1803.010] 3D-PDR: Three-dimensional photodissociation region code

3D-PDR is a three-dimensional photodissociation region code written in Fortran. It uses the Sundials package (written in C) to solve the set of ordinary differential equations and it is the successor of the one-dimensional PDR code UCL_PDR (ascl:1303.004). Using the HEALpix ray-tracing scheme (ascl:1107.018), 3D-PDR solves a three-dimensional escape probability routine and evaluates the attenuation of the far-ultraviolet radiation in the PDR and the propagation of FIR/submm emission lines out of the PDR. The code is parallelized (OpenMP) and can be applied to 1D and 3D problems.

[ascl:1803.009] SETI-EC: SETI Encryption Code

The SETI Encryption code, written in Python, creates a message for use in testing the decryptability of a simulated incoming interstellar message. The code uses images in a portable bit map (PBM) format, then writes the corresponding bits into the message, and finally returns both a PBM image and a text (TXT) file of the entire message. The natural constants (c, G, h) and the wavelength of the message are defined in the first few lines of the code, followed by the reading of the input files and their conversion into 757 strings of 359 bits to give one page. Each header of a page, i.e., the little-endian binary code translation of the tempo-spatial yardstick, is calculated and written on-the-fly for each page.

[ascl:1803.008] FAST: Fitting and Assessment of Synthetic Templates

FAST (Fitting and Assessment of Synthetic Templates) fits stellar population synthesis templates to broadband photometry and/or spectra. FAST is compatible with the photometric redshift code EAzY (ascl:1010.052) when fitting broadband photometry; it uses the photometric redshifts derived by EAzY, and the input files (for examply, photometric catalog and master filter file) are the same. FAST fits spectra in combination with broadband photometric data points or simultaneously fits two components, allowing for an AGN contribution in addition to the host galaxy light. Depending on the input parameters, FAST outputs the best-fit redshift, age, dust content, star formation timescale, metallicity, stellar mass, star formation rate (SFR), and their confidence intervals. Though some of FAST's functions overlap with those of HYPERZ (ascl:1108.010), it differs by fitting fluxes instead of magnitudes, allows the user to completely define the grid of input stellar population parameters and easily input photometric redshifts and their confidence intervals, and calculates calibrated confidence intervals for all parameters. Note that FAST is not a photometric redshift code, though it can be used as one.

[ascl:1803.007] IMAGINE: Interstellar MAGnetic field INference Engine

IMAGINE (Interstellar MAGnetic field INference Engine) performs inference on generic parametric models of the Galaxy. The modular open source framework uses highly optimized tools and technology such as the MultiNest sampler (ascl:1109.006) and the information field theory framework NIFTy (ascl:1302.013) to create an instance of the Milky Way based on a set of parameters for physical observables, using Bayesian statistics to judge the mismatch between measured data and model prediction. The flexibility of the IMAGINE framework allows for simple refitting for newly available data sets and makes state-of-the-art Bayesian methods easily accessible particularly for random components of the Galactic magnetic field.

[ascl:1803.006] MulensModel: Microlensing light curves modeling

MulensModel calculates light curves of microlensing events. Both single and binary lens events are modeled and various higher-order effects can be included: extended source (with limb-darkening), annual microlensing parallax, and satellite microlensing parallax. The code is object-oriented and written in Python3, and requires AstroPy (ascl:1304.002).

[ascl:1803.005] Kadenza: Kepler/K2 Raw Cadence Data Reader

Kadenza enables time-critical data analyses to be carried out using NASA's Kepler Space Telescope. It enables users to convert Kepler's raw data files into user-friendly Target Pixel Files upon downlink from the spacecraft. The primary motivation for this tool is to enable the microlensing, supernova, and exoplanet communities to create quicklook lightcurves for transient events which require rapid follow-up.

[ascl:1803.004] nanopipe: Calibration and data reduction pipeline for pulsar timing

nanopipe is a data reduction pipeline for calibration, RFI removal, and pulse time-of-arrival measurement from radio pulsar data. It was developed primarily for use by the NANOGrav project. nanopipe is written in Python, and depends on the PSRCHIVE (ascl:1105.014) library.

[ascl:1803.003] scarlet: Source separation in multi-band images by Constrained Matrix Factorization

SCARLET performs source separation (aka "deblending") on multi-band images. It is geared towards optical astronomy, where scenes are composed of stars and galaxies, but it is straightforward to apply it to other imaging data. Separation is achieved through a constrained matrix factorization, which models each source with a Spectral Energy Distribution (SED) and a non-parametric morphology, or multiple such components per source. The code performs forced photometry (with PSF matching if needed) using an optimal weight function given by the signal-to-noise weighted morphology across bands. The approach works well if the sources in the scene have different colors and can be further strengthened by imposing various additional constraints/priors on each source. Because of its generic utility, this package provides a stand-alone implementation that contains the core components of the source separation algorithm. However, the development of this package is part of the LSST Science Pipeline; the meas_deblender package contains a wrapper to implement the algorithms here for the LSST stack.

[ascl:1803.002] CIFOG: Cosmological Ionization Fields frOm Galaxies

CIFOG is a versatile MPI-parallelised semi-numerical tool to perform simulations of the Epoch of Reionization. From a set of evolving cosmological gas density and ionizing emissivity fields, it computes the time and spatially dependent ionization of neutral hydrogen (HI), neutral (HeI) and singly ionized helium (HeII) in the intergalactic medium (IGM). The code accounts for HII, HeII, HeIII recombinations, and provides different descriptions for the photoionization rate that are used to calculate the residual HI fraction in ionized regions. This tool has been designed to be coupled to semi-analytic galaxy formation models or hydrodynamical simulations. The modular fashion of the code allows the user to easily introduce new descriptions for recombinations and the photoionization rate.

[ascl:1803.001] DaMaSCUS-CRUST: Dark Matter Simulation Code for Underground Scatterings - Crust Edition

DaMaSCUS-CRUST determines the critical cross-section for strongly interacting DM for various direct detection experiments systematically and precisely using Monte Carlo simulations of DM trajectories inside the Earth's crust, atmosphere, or any kind of shielding. Above a critical dark matter-nucleus scattering cross section, any terrestrial direct detection experiment loses sensitivity to dark matter, since the Earth crust, atmosphere, and potential shielding layers start to block off the dark matter particles. This critical cross section is commonly determined by describing the average energy loss of the dark matter particles analytically. However, this treatment overestimates the stopping power of the Earth crust; therefore, the obtained bounds should be considered as conservative. DaMaSCUS-CRUST is a modified version of DaMaSCUS (ascl:1706.003) that accounts for shielding effects and returns a precise exclusion band.

[ascl:1802.016] eqpair: Electron energy distribution calculator

eqpair computes the electron energy distribution resulting from a balance between heating and direct acceleration of particles, and cooling processes. Electron-positron pair balance, bremstrahlung, and Compton cooling, including external soft photon input, are among the processes considered, and the final electron distribution can be hybrid, thermal, or non-thermal.

[ascl:1802.015] mrpy: Renormalized generalized gamma distribution for HMF and galaxy ensemble properties comparisons

mrpy calculates the MRP parameterization of the Halo Mass Function. It calculates basic statistics of the truncated generalized gamma distribution (TGGD) with the TGGD class, including mean, mode, variance, skewness, pdf, and cdf. It generates MRP quantities with the MRP class, such as differential number counts and cumulative number counts, and offers various methods for generating normalizations. It can generate the MRP-based halo mass function as a function of physical parameters via the mrp_b13 function, and fit MRP parameters to data in the form of arbitrary curves and in the form of a sample of variates with the SimFit class. mrpy also calculates analytic hessians and jacobians at any point, and allows the user to alternate parameterizations of the same form via the reparameterize module.

[ascl:1802.014] collapse: Spherical-collapse model code

collapse calculates the spherical−collapse for standard cosmological models as well as for dark energy models when the dark energy can be taken to be spatially homogeneous. The calculation is valid on sub−horizon scales and takes a top−hat perturbation to exist in an otherwise featureless cosmos and follows its evolution into the non−linear regime where it reaches a maximum size and then recollapses. collapse provides the user with the linear−collapse threshold (delta_c) and the virial overdensity (Delta_v) for the collapsed halo over a range of cosmic scale factors.

[ascl:1802.013] BHMcalc: Binary Habitability Mechanism Calculator

BHMcalc provides renditions of the instantaneous circumbinary habital zone (CHZ) and also calculates BHM properties of the system including those related to the rotational evolution of the stellar components and the combined XUV and SW fluxes as measured at different distances from the binary. Moreover, it provides numerical results that can be further manipulated and used to calculate other properties.

[ascl:1802.012] PyOSE: Orbital sampling effect (OSE) simulator

PyOSE is a fully numerical orbital sampling effect (OSE) simulator that can model arbitrary inclinations of the transiting moon orbit. It can be used to search for exomoons in long-term stellar light curves such as those by Kepler and the upcoming PLATO mission.

[ascl:1802.011] runDM: Running couplings of Dark Matter to the Standard Model

runDM calculates the running of the couplings of Dark Matter (DM) to the Standard Model (SM) in simplified models with vector mediators. By specifying the mass of the mediator and the couplings of the mediator to SM fields at high energy, the code can calculate the couplings at low energy, taking into account the mixing of all dimension-6 operators. runDM can also extract the operator coefficients relevant for direct detection, namely low energy couplings to up, down and strange quarks and to protons and neutrons.

[ascl:1802.010] Glimpse: Sparsity based weak lensing mass-mapping tool

Glimpse, also known as Glimpse2D, is a weak lensing mass-mapping tool that relies on a robust sparsity-based regularization scheme to recover high resolution convergence from either gravitational shear alone or from a combination of shear and flexion. Including flexion allows the supplementation of the shear on small scales in order to increase the sensitivity to substructures and the overall resolution of the convergence map. To preserve all available small scale information, Glimpse avoids any binning of the irregularly sampled input shear and flexion fields and treats the mass-mapping problem as a general ill-posed inverse problem, regularized using a multi-scale wavelet sparsity prior. The resulting algorithm incorporates redshift, reduced shear, and reduced flexion measurements for individual galaxies and is made highly efficient by the use of fast Fourier estimators.

[ascl:1802.009] astroplan: Observation planning package for astronomers

astroplan is a flexible toolbox for observation planning and scheduling. It is powered by Astropy (ascl:1304.002); it works for Python beginners and new observers, and is powerful enough for observatories preparing nightly and long-term schedules as well. It calculates rise/set/meridian transit times, alt/az positions for targets at observatories anywhere on Earth, and offers built-in plotting convenience functions for standard observation planning plots (airmass, parallactic angle, sky maps). It can also determine the observability of sets of targets given an arbitrary set of constraints (i.e., altitude, airmass, moon separation/illumination, etc.).

[ascl:1802.008] AntiparticleDM: Discriminating between Majorana and Dirac Dark Matter

AntiparticleDM calculates the prospects of future direct detection experiments to discriminate between Majorana and Dirac Dark Matter (i.e., to determine whether Dark Matter is its own antiparticle). Direct detection event rates and mock data generation are dealt with by a variation of the WIMpy code.

[ascl:1802.007] HiGal_SED_Fitter: SED fitting tools for Herschel Hi-Gal data

HiGal SED Fitter fits modified blackbody SEDs to Herschel data, specifically targeted at Herschel Hi-Gal data.

[ascl:1802.006] VISIBLE: VISIbility Based Line Extraction

VISIBLE applies approximated matched filters to interferometric data, allowing line detection directly in visibility space. The filter can be created from a FITS image or RADMC3D output image, and the weak line data can be a CASA MS or uvfits file. The filter response spectrum can be output either to a .npy file or returned back to the user for scripting.

[ascl:1802.005] Verne: Earth-stopping effect for heavy dark matter

Verne calculates the Earth-stopping effect for super-heavy Dark Matter (DM). The code allows you to calculate the speed distribution (and DM signal rate) at an arbitrary detector location on the Earth. The calculation takes into account the full anisotropic DM velocity distribution and the full velocity dependence of the DM-nucleus cross section. Results can be obtained for any DM mass and cross section, though the results are most reliable for very heavy DM particles.

[submitted] Opik Collision Probability

The Opik method gives the mean probability of collision of a small body with a given planet. It is a statistical value valid for an orbit with given (a,e,i) and undefined argument of perihelion. In some cases, the planet can eject the small body from the solar system; in these cases, the program estimates the mean time for the ejection. The Opik method does not take into account other perturbers than the planet considered, so it only provides an idea of the timescales involved.

[ascl:1802.004] ARTIP: Automated Radio Telescope Image Processing Pipeline

The Automated Radio Telescope Image Processing Pipeline (ARTIP) automates the entire process of flagging, calibrating, and imaging for radio-interferometric data. ARTIP starts with raw data, i.e. a measurement set and goes through multiple stages, such as flux calibration, bandpass calibration, phase calibration, and imaging to generate continuum and spectral line images. Each stage can also be run independently. The pipeline provides continuous feedback to the user through various messages, charts and logs. It is written using standard python libraries and the CASA package. The pipeline can deal with datasets with multiple spectral windows and also multiple target sources which may have arbitrary combinations of flux/bandpass/phase calibrators.

[ascl:1802.003] CMacIonize: Monte Carlo photoionisation and moving-mesh radiation hydrodynamics

CMacIonize simulates the self-consistent evolution of HII regions surrounding young O and B stars, or other sources of ionizing radiation. The code combines a Monte Carlo photoionization algorithm that uses a complex mix of hydrogen, helium and several coolants in order to self-consistently solve for the ionization and temperature balance at any given time, with a standard first order hydrodynamics scheme. The code can be run as a post-processing tool to get the line emission from an existing simulation snapshot, but can also be used to run full radiation hydrodynamical simulations. Both the radiation transfer and the hydrodynamics are implemented in a general way that is independent of the grid structure that is used to discretize the system, allowing it to be run both as a standard fixed grid code and also as a moving-mesh code.

[ascl:1802.002] venice: Mask utility

venice reads a mask file (DS9 or fits type) and a catalogue of objects (ascii or fits type) to create a pixelized mask, find objects inside/outside a mask, or generate a random catalogue of objects inside/outside a mask. The program reads the mask file and checks if a point, giving its coordinates, is inside or outside the mask, i.e. inside or outside at least one polygon of the mask.

[ascl:1802.001] FAC: Flexible Atomic Code

FAC calculates various atomic radiative and collisional processes, including radiative transition rates, collisional excitation and ionization by electron impact, energy levels, photoionization, and autoionization, and their inverse processes radiative recombination and dielectronic capture. The package also includes a collisional radiative model to construct synthetic spectra for plasmas under different physical conditions.

[ascl:1801.012] RadVel: General toolkit for modeling Radial Velocities

RadVel models Keplerian orbits in radial velocity (RV) time series. The code is written in Python with a fast Kepler's equation solver written in C. It provides a framework for fitting RVs using maximum a posteriori optimization and computing robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel can perform Bayesian model comparison and produces publication quality plots and LaTeX tables.

[ascl:1801.011] GABE: Grid And Bubble Evolver

GABE (Grid And Bubble Evolver) evolves scalar fields (as well as other purposes) on an expanding background for non-canonical and non-linear classical field theory. GABE is based on the Runge-Kutta method.

[ascl:1801.010] DICE/ColDICE: 6D collisionless phase space hydrodynamics using a lagrangian tesselation

DICE is a C++ template library designed to solve collisionless fluid dynamics in 6D phase space using massively parallel supercomputers via an hybrid OpenMP/MPI parallelization. ColDICE, based on DICE, implements a cosmological and physical VLASOV-POISSON solver for cold systems such as dark matter (CDM) dynamics.

[ascl:1801.009] Gnuastro: GNU Astronomy Utilities

Gnuastro (GNU Astronomy Utilities) manipulates and analyzes astronomical data. It is an official GNU package of a large collection of programs and C/C++ library functions. Command-line programs perform arithmetic operations on images, convert FITS images to common types like JPG or PDF, convolve an image with a given kernel or matching of kernels, perform cosmological calculations, crop parts of large images (possibly in multiple files), manipulate FITS extensions and keywords, and perform statistical operations. In addition, it contains programs to make catalogs from detection maps, add noise, make mock profiles with a variety of radial functions using monte-carlo integration for their centers, match catalogs, and detect objects in an image among many other operations. The command-line programs share the same basic command-line user interface for the comfort of both the users and developers. Gnuastro is written to comply fully with the GNU coding standards and integrates well with all Unix-like operating systems. This enables astronomers to expect a fully familiar experience in the source code, building, installing and command-line user interaction that they have seen in all the other GNU software that they use. Gnuastro's extensive library is included for users who want to build their own unique programs.

[ascl:1801.008] BOND: Bayesian Oxygen and Nitrogen abundance Determinations

BOND determines oxygen and nitrogen abundances in giant H II regions by comparison with a large grid of photoionization models. The grid spans a wide range in O/H, N/O and ionization parameter U, and covers different starburst ages and nebular geometries. Unlike other statistical methods, BOND relies on the [Ar III]/[Ne III] emission line ratio to break the oxygen abundance bimodality. By doing so, it can measure oxygen and nitrogen abundances without assuming any a priori relation between N/O and O/H. BOND takes into account changes in the hardness of the ionizing radiation field, which can come about due to the ageing of H II regions or the stochastically sampling of the IMF. The emission line ratio He I/Hβ, in addition to commonly used strong lines, constrains the hardness of the ionizing radiation field. BOND relies on the emission line ratios [O III]/Hβ, [O II]/Hβ and [N II]/Hβ, [Ar III]/Hβ, [Ne III]/Hβ, He I/Hβ as its input parameters, while its output values are the measurements and uncertainties for O/H and N/O.

[ascl:1801.007] cambmag: Magnetic Fields in CAMB

cambmag is a modification to CAMB (ascl:1102.026) that calculates the compensated magnetic mode in the scalar, vector and tensor case. Previously CAMB included code only for the vectors. It also corrects for tight-coupling issues and adds in the ability to include massive neutrinos when calculating vector modes.

[ascl:1801.006] DecouplingModes: Passive modes amplitudes

DecouplingModes calculates the amplitude of the passive modes, which requires solving the Einstein equations on superhorizon scales sourced by the anisotropic stress from the magnetic fields (prior to neutrino decoupling), and the magnetic and neutrino stress (after decoupling). The code is available as a Mathematica notebook.

[ascl:1801.005] InitialConditions: Initial series solutions for perturbations in our Universe

InitialConditions finds the initial series solutions for perturbations in our Universe. This includes all scalar (1 adiabatic, 4 isocurvature and 2 magnetic modes), vector (1 vorticity mode, 1 magnetic mode), and tensor (1 gravitational wave mode and 1 magnetic mode) perturbations including terms up to second order in the neutrino mass. It can handle the standard species (cdm, baryons, photons), and two neutrino mass eigenstates (1 light, 1 heavy).

[ascl:1801.004] hh0: Hierarchical Hubble Constant Inference

hh0 is a Bayesian hierarchical model (BHM) that describes the full distance ladder, from nearby geometric-distance anchors through Cepheids to SNe in the Hubble flow. It does not rely on any of the underlying distributions being Gaussian, allowing outliers to be modeled and obviating the need for any arbitrary data cuts.

[ascl:1801.003] Stan: Statistical inference

Stan facilitates statistical inference at the frontiers of applied statistics and provides both a modeling language for specifying complex statistical models and a library of statistical algorithms for computing inferences with those models. These components are exposed through interfaces in environments such as R, Python, and the command line.

[ascl:1801.002] iWander: Dynamics of interstellar wanderers

iWander assesses the origin of interstellar small bodies such as asteroids and comets. It includes a series of databases and tools that can be used in general for studying the dynamics of an interstellar vagabond object (small−body, interstellar spaceship and even stars).

[ascl:1801.001] BANYAN_Sigma: Bayesian classifier for members of young stellar associations

BANYAN_Sigma calculates the membership probability that a given astrophysical object belongs to one of the currently known 27 young associations within 150 pc of the Sun, using Bayesian inference. This tool uses the sky position and proper motion measurements of an object, with optional radial velocity (RV) and distance (D) measurements, to derive a Bayesian membership probability. By default, the priors are adjusted such that a probability threshold of 90% will recover 50%, 68%, 82% or 90% of true association members depending on what observables are input (only sky position and proper motion, with RV, with D, with both RV and D, respectively). The algorithm is implemented in a Python package, in IDL, and is also implemented as an interactive web page.

[submitted] A Neural Network for the Identification of Dangerous Planetesimals (Including scripts for data generation)

Two neural networks were designed to identify hazardous planetesimals that were trained on object trajectories calculated in a cloud computing environment. The first neural network was fully-connected and was trained on the orbital elements (OEs) of real/simulated planetesimals, while the second was a 1-dimensional convolutional neural network that was trained on the position Cartesian coordinates of real/simulated planetesimals. Ultimately, the network trained on OEs had a better performance by identifying one-third of known potentially hazardous objects including the 3 asteroids with the highest chance of impact with Earth (2009 FD, 1999 RQ36, 1950 DA) as established by NASA's Monte Carlo based Sentry system.

[submitted] loci: Smooth Cubic Multivariate Local Interpolations

loci is a shared library for interpolations in up to 4 dimensions. It is written in C and can be used with C/C++, Python and others. In order to calculate the coefficients of the cubic polynom, only local values are used: The data itself and all combinations of first-order derivatives, i.e. in 2D f_x, f_y and f_xy. This is in contrast to splines, where the coefficients are not calculated using derivatives, but non-local data, which can lead to over-smoothing the result.

[ascl:1712.016] LgrbWorldModel: Long-duration Gamma-Ray Burst World Model

LgrbWorldModel is written in Fortran 90 and attempts to model the population distribution of the Long-duration class of Gamma-Ray Bursts (LGRBs) as detected by the NASA's now-defunct Burst And Transient Source Experiment (BATSE) onboard the Compton Gamma Ray Observatory (CGRO). It is assumed that the population distribution of LGRBs is well fit by a multivariate log-normal distribution. The best-fit parameters of the distribution are then found by maximizing the likelihood of the observed data by BATSE detectors via a native built-in Adaptive Metropolis-Hastings Markov-Chain Monte Carlo (AMH-MCMC) Sampler.

[ascl:1712.015] SgrbWorldModel: Short-duration Gamma-Ray Burst World Model

SgrbWorldModel, written in Fortran 90, presents an attempt at modeling the population distribution of the Short-duration class of Gamma-Ray Bursts (SGRBs) as detected by the NASA's now-defunct Burst And Transient Source Experiment (BATSE) onboard the Compton Gamma Ray Observatory (CGRO). It is assumed that the population distribution of SGRBs is well fit by a multivariate log-normal distribution, whose differential cosmological rate of occurrence follows the Star-Formation-Rate (SFR) convolved with a log-normal binary-merger delay-time distribution. The best-fit parameters of the model are then found by maximizing the likelihood of the observed data by the BATSE detectors via a native built-in Adaptive Metropolis-Hastings Markov-Chain Monte Carlo (AMH-MCMC)Sampler that is part of the code. A model for the detection algorithm of the BATSE detectors is also provided.

[ascl:1712.014] QATS: Quasiperiodic Automated Transit Search

QATS detects transiting extrasolar planets in time-series photometry. It relaxes the usual assumption of strictly periodic transits by permitting a variable, but bounded, interval between successive transits.

[ascl:1712.013] photodynam: Photodynamical code for fitting the light curves of multiple body systems

Photodynam facilitates so-called "photometric-dynamical" modeling. This model is quite simple and this is reflected in the code base. A N-body code provides coordinates and the photometric code produces light curves based on coordinates.

[ascl:1712.012] MadDM: Computation of dark matter relic abundance

MadDM computes dark matter relic abundance and dark matter nucleus scattering rates in a generic model. The code is based on the existing MadGraph 5 architecture and as such is easily integrable into any MadGraph collider study. A simple Python interface offers a level of user-friendliness characteristic of MadGraph 5 without sacrificing functionality. MadDM is able to calculate the dark matter relic abundance in models which include a multi-component dark sector, resonance annihilation channels and co-annihilations. The direct detection module of MadDM calculates spin independent / spin dependent dark matter-nucleon cross sections and differential recoil rates as a function of recoil energy, angle and time. The code provides a simplified simulation of detector effects for a wide range of target materials and volumes.

[ascl:1712.011] FBEYE: Analyzing Kepler light curves and validating flares

FBEYE, the "Flares By-Eye" detection suite, is written in IDL and analyzes Kepler light curves and validates flares. It works on any 3-column light curve that contains time, flux, and error. The success of flare identification is highly dependent on the smoothing routine, which may not be suitable for all sources.

[ascl:1712.010] Flux Tube: Solar model

Flux Tube is a nonlinear, two-dimensional, numerical simulation of magneto-acoustic wave propagation in the photosphere and chromosphere of small-scale flux tubes with internal structure. Waves with realistic periods of three to five minutes are studied, after horizontal and vertical oscillatory perturbations are applied to the equilibrium model. Spurious reflections of shock waves from the upper boundary are minimized by a special boundary condition.

[ascl:1712.009] RODRIGUES: RATT Online Deconvolved Radio Image Generation Using Esoteric Software

RODRIGUES (RATT Online Deconvolved Radio Image Generation Using Esoteric Software) is a web-based radio telescope simulation and reduction tool. From a technical perspective it is a web based parameterized docker container scheduler with a result set viewer.

[ascl:1712.008] CosApps: Simulate gravitational lensing through ray tracing and shear calculation

Cosmology Applications (CosApps) provides tools to simulate gravitational lensing using two different techniques, ray tracing and shear calculation. The tool ray_trace_ellipse calculates deflection angles on a grid for light passing a deflecting mass distribution. Using MPI, ray_trace_ellipse may calculate deflection in parallel across network connected computers, such as cluster. The program physcalc calculates the gravitational lensing shear using the relationship of convergence and shear, described by a set of coupled partial differential equations.

[ascl:1712.007] SFoF: Friends-of-friends galaxy cluster detection algorithm

SFoF is a friends-of-friends galaxy cluster detection algorithm that operates in either spectroscopic or photometric redshift space. The linking parameters, both transverse and along the line-of-sight, change as a function of redshift to account for selection effects.

[ascl:1712.006] Nyx: Adaptive mesh, massively-parallel, cosmological simulation code

Nyx code solves equations of compressible hydrodynamics on an adaptive grid hierarchy coupled with an N-body treatment of dark matter. The gas dynamics in Nyx use a finite volume methodology on an adaptive set of 3-D Eulerian grids; dark matter is represented as discrete particles moving under the influence of gravity. Particles are evolved via a particle-mesh method, using Cloud-in-Cell deposition/interpolation scheme. Both baryonic and dark matter contribute to the gravitational field. In addition, Nyx includes physics for accurately modeling the intergalactic medium; in optically thin limits and assuming ionization equilibrium, the code calculates heating and cooling processes of the primordial-composition gas in an ionizing ultraviolet background radiation field.

[ascl:1712.005] draco: Analysis and simulation of drift scan radio data

draco analyzes transit radio data with the m-mode formalism. It is telescope agnostic, and is used as part of the analysis and simulation pipeline for the CHIME (Canadian Hydrogen Intensity Mapping Experiment) telescope. It can simulate time stream data from maps of the sky (using the m-mode formalism) and add gain fluctuations and correctly correlated instrumental noise (i.e. Wishart distributed). Further, it can perform various cuts on the data and make maps of the sky from data using the m-mode formalism.

[ascl:1712.004] Bitshuffle: Filter for improving compression of typed binary data

Bitshuffle rearranges typed, binary data for improving compression; the algorithm is implemented in a python/C package within the Numpy framework. The library can be used alongside HDF5 to compress and decompress datasets and is integrated through the dynamically loaded filters framework. Algorithmically, Bitshuffle is closely related to HDF5's Shuffle filter except it operates at the bit level instead of the byte level. Arranging a typed data array in to a matrix with the elements as the rows and the bits within the elements as the columns, Bitshuffle "transposes" the matrix, such that all the least-significant-bits are in a row, etc. This transposition is performed within blocks of data roughly 8kB long; this does not in itself compress data, but rearranges it for more efficient compression. A compression library is necessary to perform the actual compression. This scheme has been used for compression of radio data in high performance computing.

[ascl:1712.003] Py-SPHViewer: Cosmological simulations using Smoothed Particle Hydrodynamics

Py-SPHViewer visualizes and explores N-body + Hydrodynamics simulations. The code interpolates the underlying density field (or any other property) traced by a set of particles, using the Smoothed Particle Hydrodynamics (SPH) interpolation scheme, thus producing not only beautiful but also useful scientific images. Py-SPHViewer enables the user to explore simulated volumes using different projections. Py-SPHViewer also provides a natural way to visualize (in a self-consistent fashion) gas dynamical simulations, which use the same technique to compute the interactions between particles.

[ascl:1712.002] MPI_XSTAR: MPI-based parallelization of XSTAR program

MPI_XSTAR parallelizes execution of multiple XSTAR runs using Message Passing Interface (MPI). XSTAR (ascl:9910.008), part of the HEASARC's HEAsoft (ascl:1408.004) package, calculates the physical conditions and emission spectra of ionized gases. MPI_XSTAR invokes XSTINITABLE from HEASoft to generate a job list of XSTAR commands for given physical parameters. The job list is used to make directories in ascending order, where each individual XSTAR is spawned on each processor and outputs are saved. HEASoft's XSTAR2TABLE program is invoked upon the contents of each directory in order to produce table model FITS files for spectroscopy analysis tools.

[ascl:1712.001] KDUtils: Kinematic Distance Utilities

The Kinematic Distance utilities (KDUtils) calculate kinematic distances and kinematic distance uncertainties. The package includes methods to calculate "traditional" kinematic distances as well as a Monte Carlo method to calculate kinematic distances and uncertainties.

[ascl:1711.024] NOD3: Single dish reduction software

NOD3 processes and analyzes maps from single-dish observations affected by scanning effects from clouds, receiver instabilities, or radio-frequency interference. Its “basket-weaving” tool combines orthogonally scanned maps into a final map that is almost free of scanning effects. A restoration tool for dual-beam observations reduces the noise by a factor of about two compared to the NOD2 version. Combining single-dish with interferometer data in the map plane ensures the full recovery of the total flux density.

[ascl:1711.023] HBT+: Subhalo finder and merger tree builder

HBT+ is a hybrid subhalo finder and merger tree builder for cosmological simulations. It comes as an MPI edition that can be run on distributed clusters or shared memory machines and is MPI/OpenMP parallelized, and also as an OpenMP edition that can be run on shared memory machines and is only OpenMP parallelized. This version is more memory efficient than the MPI branch on shared memory machines, and is more suitable for analyzing zoomed-in simulations that are difficult to balance on distributed clusters. Both editions support hydro simulations with gas/stars.

[ascl:1711.022] HBT: Hierarchical Bound-Tracing

HBT is a Hierarchical Bound-Tracing subhalo finder and merger tree builder, for numerical simulations in cosmology. It tracks haloes from birth and continues to track them after mergers, finding self-bound structures as subhaloes and recording their merger histories as merger trees.

[ascl:1711.021] Bifrost: Stream processing framework for high-throughput applications

Bifrost is a stream processing framework that eases the development of high-throughput processing CPU/GPU pipelines. It is designed for digital signal processing (DSP) applications within radio astronomy. Bifrost uses a flexible ring buffer implementation that allows different signal processing blocks to be connected to form a pipeline. Each block may be assigned to a CPU core, and the ring buffers are used to transport data to and from blocks. Processing blocks may be run on either the CPU or GPU, and the ring buffer will take care of memory copies between the CPU and GPU spaces.

[ascl:1711.020] MARXS: Multi-Architecture Raytrace Xray mission Simulator

MARXS (Multi-Architecture-Raytrace-Xraymission-Simulator) simulates X-ray observatories. Primarily designed to simulate X-ray instruments on astronomical X-ray satellites and sounding rocket payloads, it can also be used to ray-trace experiments in the laboratory. MARXS performs polarization Monte-Carlo ray-trace simulations from a source (astronomical or lab) through a collection of optical elements such as mirrors, baffles, and gratings to a detector.

[ascl:1711.019] SPIDERMAN: Fast code to simulate secondary transits and phase curves

SPIDERMAN calculates exoplanet phase curves and secondary eclipses with arbitrary surface brightness distributions in two dimensions. The code uses a geometrical algorithm to solve exactly the area of sections of the disc of the planet that are occulted by the star. Approximately 1000 models can be generated per second in typical use, which makes making Markov Chain Monte Carlo analyses practicable. The code is modular and allows comparison of the effect of multiple different brightness distributions for a dataset.

[ascl:1711.018] LExTeS: Link Extraction and Testing Suite

LExTeS (Link Extraction and Testing Suite) extracts hyperlinks from PDF documents, tests the extracted links to see which are broken, and tabulates the results. Though written to support a particular set of PDF documents, the dataset and scripts can be edited for use on other documents.

[ascl:1711.017] FATS: Feature Analysis for Time Series

FATS facilitates and standardizes feature extraction for time series data; it quickly and efficiently calculates a compilation of many existing light curve features. Users can characterize or analyze an astronomical photometric database, though this library is not necessarily restricted to the astronomical domain and can also be applied to any kind of time series data.

[ascl:1711.016] Thindisk: Protoplanetary disk model

Thindisk computes the line emission from a geometrically thin protoplanetary disk. It creates a datacube in FITS format that can be processed with a data reduction package (such as GILDAS, ascl:1305.010) to produce synthetic images and visibilities. These synthetic data can be compared with observations to determine the properties (e.g. central mass or inclination) of an observed disk. The disk is assumed to be in Keplerian rotation at a radius lower than the centrifugal radius (which can be set to a large value, for a purely Keplerian disk), and in infall with rotation beyond the centrifugal radius.

[ascl:1711.015] rac-2d: Thermo-chemical for modeling water vapor formation in protoplanetary disks

rec-2d models the distribution of water vapor in protoplanetary disks. Given a distribution of gas and dust, rac-2d first solves the dust temperature distribution with a Monte Carlo method and then solves the gas temperature distribution and chemical composition. Although the geometry is symmetric with respect to rotation around the central axis and reflection about the midplane, the photon propagation is done in full three dimensions. After establishing the dust temperature distribution, the disk chemistry is evolved for 1 Myr; the heating and cooling processes are coupled with chemistry, allowing the gas temperature to be evolved in tandem with chemistry based on the heating and cooling rates.

[ascl:1711.014] Gammapy: Python toolbox for gamma-ray astronomy

Gammapy analyzes gamma-ray data and creates sky images, spectra and lightcurves, from event lists and instrument response information; it can also determine the position, morphology and spectra of gamma-ray sources. It is used to analyze data from H.E.S.S., Fermi-LAT, and the Cherenkov Telescope Array (CTA).

[ascl:1711.013] HO-CHUNK: Radiation Transfer code

HO-CHUNK calculates radiative equilibrium temperature solution, thermal and PAH/vsg emission, scattering and polarization in protostellar geometries. It is useful for computing spectral energy distributions (SEDs), polarization spectra, and images.

[ascl:1711.012] megaman: Manifold Learning for Millions of Points

megaman is a scalable manifold learning package implemented in python. It has a front-end API designed to be familiar to scikit-learn but harnesses the C++ Fast Library for Approximate Nearest Neighbors (FLANN) and the Sparse Symmetric Positive Definite (SSPD) solver Locally Optimal Block Precodition Gradient (LOBPCG) method to scale manifold learning algorithms to large data sets. It is designed for researchers and as such caches intermediary steps and indices to allow for fast re-computation with new parameters.

[ascl:1711.011] galkin: Milky Way rotation curve data handler

galkin is a compilation of kinematic measurements tracing the rotation curve of our Galaxy, together with a tool to treat the data. The compilation is optimized to Galactocentric radii between 3 and 20 kpc and includes the kinematics of gas, stars and masers in a total of 2780 measurements collected from almost four decades of literature. The user-friendly software provided selects, treats and retrieves the data of all source references considered. This tool is especially designed to facilitate the use of kinematic data in dynamical studies of the Milky Way with various applications ranging from dark matter constraints to tests of modified gravity.

[ascl:1711.010] galstreams: Milky Way streams footprint library and toolkit

galstreams provides a compilation of spatial information for known stellar streams and overdensities in the Milky Way and includes Python tools for visualizing them. ASCII tables are also provided for quick viewing of the stream's footprints using TOPCAT (ascl:1101.010). As of 2022, the library provides celestial, distance, proper motion and radial velocity tracks for each stream (pm/vrad when available) stored as AstroPy (ascl:1304.002) SkyCoord objects and a stream's (heliocentric) coordinate frame is realized as an AstroPy reference frame. The code offers polygon footprints and pole (at mid point) and pole tracks in the heliocentric and Galactocentric (GSR) frames. It also offers angular momentum tracks in a heliocentric reference frame at rest with respect to the Galactic center, and provides uniformly reported stream length, end points and mid-point, heliocentric and Galactocentric mid-pole, track and discovery references and information flag denoting which of the 6D attributes (sky, distance, proper motions and radial velocity) are available in the track object.

[ascl:1711.009] Lightning: SED Fitting Package

Lightning is a spectral energy distribution (SED) fitting procedure that quickly and reliably recovers star formation history (SFH) and extinction parameters. The SFH is modeled as discrete steps in time. The code consists of a fully vectorized inversion algorithm to determine SFH step intensities and combines this with a grid-based approach to determine three extinction parameters.

[ascl:1711.008] clustep: Initial conditions for galaxy cluster halo simulations

clustep generates a snapshot in GADGET-2 (ascl:0003.001) format containing a galaxy cluster halo in equilibrium; this snapshot can also be read in RAMSES (ascl:1011.007) using the DICE patch. The halo is made of a dark matter component and a gas component, with the latter representing the ICM. Each of these components follows a Dehnen density profile, with gamma=0 or gamma=1. If gamma=1, then the profile corresponds to a Hernquist profile.

[ascl:1711.007] galstep: Initial conditions for spiral galaxy simulations

galstep generates initial conditions for disk galaxy simulations with GADGET-2 (ascl:0003.001), RAMSES (ascl:1011.007) and GIZMO (ascl:1410.003), including a stellar disk, a gaseous disk, a dark matter halo and a stellar bulge. The first two components follow an exponential density profile, and the last two a Dehnen density profile with gamma=1 by default, corresponding to a Hernquist profile.

[ascl:1711.006] RGW: Goodman-Weare Affine-Invariant Sampling

RGW is a lightweight R-language implementation of the affine-invariant Markov Chain Monte Carlo sampling method of Goodman & Weare (2010). The implementation is based on the description of the python package emcee (ascl:1303.002).

[ascl:1711.005] correlcalc: Two-point correlation function from redshift surveys

correlcalc calculates two-point correlation function (2pCF) of galaxies/quasars using redshift surveys. It can be used for any assumed geometry or Cosmology model. Using BallTree algorithms to reduce the computational effort for large datasets, it is a parallelised code suitable for running on clusters as well as personal computers. It takes redshift (z), Right Ascension (RA) and Declination (DEC) data of galaxies and random catalogs as inputs in form of ascii or fits files. If random catalog is not provided, it generates one of desired size based on the input redshift distribution and mangle polygon file (in .ply format) describing the survey geometry. It also calculates different realisations of (3D) anisotropic 2pCF. Optionally it makes healpix maps of the survey providing visualization.

[ascl:1711.004] BayesVP: Full Bayesian Voigt profile fitting

BayesVP offers a Bayesian approach for modeling Voigt profiles in absorption spectroscopy. The code fits the absorption line profiles within specified wavelength ranges and generates posterior distributions for the column density, Doppler parameter, and redshifts of the corresponding absorbers. The code uses publicly available efficient parallel sampling packages to sample posterior and thus can be run on parallel platforms. BayesVP supports simultaneous fitting for multiple absorption components in high-dimensional parameter space. The package includes additional utilities such as explicit specification of priors of model parameters, continuum model, Bayesian model comparison criteria, and posterior sampling convergence check.

[ascl:1711.003] FTbg: Background removal using Fourier Transform

FTbg performs Fourier transforms on FITS images and separates low- and high-spatial frequency components by a user-specified cut. Both components are then inverse Fourier transformed back to image domain. FTbg can remove large-scale background/foreground emission in many astrophysical applications. FTbg has been designed to identify and remove Galactic background emission in Herschel/Hi-GAL continuum images, but it is applicable to any other (e.g., Planck) images when background/foreground emission is a concern.

[ascl:1711.002] inhomog: Biscale kinematical backreaction analytical evolution

The inhomog library provides Raychaudhuri integration of cosmological domain-wise average scale factor evolution using an analytical formula for kinematical backreaction Q_D evolution. The inhomog main program illustrates biscale examples. The library routine lib/Omega_D_precalc.c is callable by RAMSES (ascl:1011.007) using the RAMSES extension ramses-scalav.

[ascl:1711.001] SpcAudace: Spectroscopic processing and analysis package of Audela software

SpcAudace processes long slit spectra with automated pipelines and performs astrophysical analysis of the latter data. These powerful pipelines do all the required steps in one pass: standard preprocessing, masking of bad pixels, geometric corrections, registration, optimized spectrum extraction, wavelength calibration and instrumental response computation and correction. Both high and low resolution long slit spectra are managed for stellar and non-stellar targets. Many types of publication-quality figures can be easily produced: pdf and png plots or annotated time series plots. Astrophysical quantities can be derived from individual or large amount of spectra with advanced functions: from line profile characteristics to equivalent width and periodogram. More than 300 documented functions are available and can be used into TCL scripts for automation. SpcAudace is based on Audela open source software.

[ascl:1710.024] pred_loggs: Predicting individual galaxy G/S probability distributions

pred_loggs models the entire PGF probability density field, enabling iterative statistical modeling of upper limits and prediction of full G/S probability distributions for individual galaxies.

[ascl:1710.023] LIMEPY: Lowered Isothermal Model Explorer in PYthon

LIMEPY solves distribution function (DF) based lowered isothermal models. It solves Poisson's equation used on input parameters and offers fast solutions for isotropic/anisotropic, single/multi-mass models, normalized DF values, density and velocity moments, projected properties, and generates discrete samples.

[ascl:1710.022] galario: Gpu Accelerated Library for Analyzing Radio Interferometer Observations

The galario library exploits the computing power of modern graphic cards (GPUs) to accelerate the comparison of model predictions to radio interferometer observations. It speeds up the computation of the synthetic visibilities given a model image (or an axisymmetric brightness profile) and their comparison to the observations.

[ascl:1710.021] OSIRIS Toolbox: OH-Suppressing InfraRed Imaging Spectrograph pipeline

OSIRIS Toolbox reduces data for the Keck OSIRIS instrument, an integral field spectrograph that works with the Keck Adaptive Optics System. It offers real-time reduction of raw frames into cubes for display and basic analysis. In this real-time mode, it takes about one minute for a preliminary data cube to appear in the “quicklook” display package. The reduction system also includes a growing set of final reduction steps including correction of telluric absorption and mosaicing of multiple cubes.

[ascl:1710.020] PSPLINE: Princeton Spline and Hermite cubic interpolation routines

PSPLINE is a collection of Spline and Hermite interpolation tools for 1D, 2D, and 3D datasets on rectilinear grids. Spline routines give full control over boundary conditions, including periodic, 1st or 2nd derivative match, or divided difference-based boundary conditions on either end of each grid dimension. Hermite routines take the function value and derivatives at each grid point as input, giving back a representation of the function between grid points. Routines are provided for creating Hermite datasets, with appropriate boundary conditions applied. The 1D spline and Hermite routines are based on standard methods; the 2D and 3D spline or Hermite interpolation functions are constructed from 1D spline or Hermite interpolation functions in a straightforward manner. Spline and Hermite interpolation functions are often much faster to evaluate than other representations using e.g. Fourier series or otherwise involving transcendental functions.

[ascl:1710.019] GASOLINE: Smoothed Particle Hydrodynamics (SPH) code

Gasoline solves the equations of gravity and hydrodynamics in astrophysical problems, including simulations of planets, stars, and galaxies. It uses an SPH method that features correct mixing behavior in multiphase fluids and minimal artificial viscosity. This method is identical to the SPH method used in the ChaNGa code (ascl:1105.005), allowing users to extend results to problems requiring >100,000 cores. Gasoline uses a fast, memory-efficient O(N log N) KD-Tree to solve Poisson's Equation for gravity and avoids artificial viscosity in non-shocking compressive flows.

[ascl:1710.018] FITSFH: Star Formation Histories

FITSFH derives star formation histories from photometry of resolved stellar populations by populating theoretical isochrones according to a chosen stellar initial mass function (IMF) and searching for the linear combination of isochrones with different ages and metallicities that best matches the data. In comparing the synthetic and real data, observational errors and incompleteness are taken into account, and a rudimentary treatment of the effect of unresolved binaries is also implemented. The code also allows for an age-dependent range of extinction values to be included in the modelling.

[ascl:1710.017] ATLAS9: Model atmosphere program with opacity distribution functions

ATLAS9 computes model atmospheres using a fixed set of pretabulated opacities, allowing one to work on huge numbers of stars and interpolate in large grids of models to determine parameters quickly. The code works with two different sets of opacity distribution functions (ODFs), one with “big” wavelength intervals covering the whole spectrum and the other with 1221 “little” wavelength intervals covering the whole spectrum. The ODFs use a 12-step representation; the radiation field is computed starting with the highest step and working down. If a lower step does not matter because the line opacity is small relative to the continuum at all depths, all the lower steps are lumped together and not computed to save time.

[ascl:1710.016] LGMCA: Local-Generalized Morphological Component Analysis

LGMCA (Local-Generalized Morphological Component Analysis) is an extension to GMCA (ascl:1710.015). Similarly to GMCA, it is a Blind Source Separation method which enforces sparsity. The novel aspect of LGMCA, however, is that the mixing matrix changes across pixels allowing LGMCA to deal with emissions sources which vary spatially. These IDL scripts compute the CMB map from WMAP and Planck data; running LGMCA on the WMAP9 temperature products requires the main script and a selection of mandatory files, algorithm parameters and map parameters.

[ascl:1710.015] GMCALab: Generalized Morphological Component Analysis

GMCALab solves Blind Source Separation (BSS) problems from multichannel/multispectral/hyperspectral data. In essence, multichannel data provide different observations of the same physical phenomena (e.g. multiple wavelengths), which are modeled as a linear combination of unknown elementary components or sources. Written as a set of Matlab toolboxes, it provides a generic framework that can be extended to tackle different matrix factorization problems.

[ascl:1710.014] GBART: Determination of the orbital elements of spectroscopic binaries

GBART is an improved version of the code for determining the orbital elements for spectroscopic binaries originally written by Bertiau & Grobben (1968).

[ascl:1710.013] Ramses-GPU: Second order MUSCL-Handcock finite volume fluid solver

RamsesGPU is a reimplementation of RAMSES (ascl:1011.007) which drops the adaptive mesh refinement (AMR) features to optimize 3D uniform grid algorithms for modern graphics processor units (GPU) to provide an efficient software package for astrophysics applications that do not need AMR features but do require a very large number of integration time steps. RamsesGPU provides an very efficient C++/CUDA/MPI software implementation of a second order MUSCL-Handcock finite volume fluid solver for compressible hydrodynamics as a magnetohydrodynamics solver based on the constraint transport technique. Other useful modules includes static gravity, dissipative terms (viscosity, resistivity), and forcing source term for turbulence studies, and special care was taken to enhance parallel input/output performance by using state-of-the-art libraries such as HDF5 and parallel-netcdf.

[ascl:1710.012] FSFE: Fake Spectra Flux Extractor

The fake spectra flux extractor generates simulated quasar absorption spectra from a particle or adaptive mesh-based hydrodynamic simulation. It is implemented as a python module. It can produce both hydrogen and metal line spectra, if the simulation includes metals. The cloudy table for metal ionization fractions is included. Unlike earlier spectral generation codes, it produces absorption from each particle close to the sight-line individually, rather than first producing an average density in each spectral pixel, thus substantially preserving more of the small-scale velocity structure of the gas. The code supports both Gadget (ascl:0003.001) and AREPO (ascl:1909.010).

[ascl:1710.011] mTransport: Two-point-correlation function calculator

mTransport computes the 2-point-correlation function of the curvature and tensor perturbations in multifield models of inflation in the presence of a curved field space. It is a Mathematica implementation of the transport method which encompasses scenarios with violations of slow-roll conditions and turns of the trajectory in field space. It can be used for an arbitrary mass spectrum, including massive modes, particle production and models with quasi-single-field dynamics.

[ascl:1710.010] PyTransport: Calculate inflationary correlation functions

PyTransport calculates the 2-point and 3-point function of inflationary perturbations produced during multi-field inflation. The core of PyTransport is C++ code which is automatically edited and compiled into a Python module once an inflationary potential is specified. This module can then be called to solve the background inflationary cosmology as well as the evolution of correlations of inflationary perturbations. PyTransport includes two additional modules written in Python, one to perform the editing and compilation, and one containing a suite of functions for common tasks such as looping over the core module to construct spectra and bispectra.

[ascl:1710.009] CppTransport: Two- and three-point function transport framework for inflationary cosmology

CppTransport solves the 2- and 3-point functions of the perturbations produced during an inflationary epoch in the very early universe. It is implemented for models with canonical kinetic terms, although the underlying method is quite general and could be scaled to handle models with a non-trivial field-space metric or an even more general non-canonical Lagrangian.

[ascl:1710.008] Binary: Accretion disk evolution

Binary computes the evolution of an accretion disc interacting with a binary system. It has been developed and used to study the coupled evolution of supermassive BH binaries and gaseous accretion discs.

[ascl:1710.007] FLAG: Exact Fourier-Laguerre transform on the ball

FLAG is a fast implementation of the Fourier-Laguerre Transform, a novel 3D transform exploiting an exact quadrature rule of the ball to construct an exact harmonic transform in 3D spherical coordinates. The angular part of the Fourier-Laguerre transform uses the MW sampling theorem and the exact spherical harmonic transform implemented in the SSHT code (ascl:2207.034). The radial sampling scheme arises from an exact quadrature of the radial half-line using damped Laguerre polynomials. The radial transform can in fact be used to compute the spherical Bessel transform exactly, and the Fourier-Laguerre transform is thus closely related to the Fourier-Bessel transform.

[ascl:1710.006] MOSFiT: Modular Open-Source Fitter for Transients

MOSFiT (Modular Open-Source Fitter for Transients) downloads transient datasets from open online catalogs (e.g., the Open Supernova Catalog), generates Monte Carlo ensembles of semi-analytical light curve fits to those datasets and their associated Bayesian parameter posteriors, and optionally delivers the fitting results back to those same catalogs to make them available to the rest of the community. MOSFiT helps bridge the gap between observations and theory in time-domain astronomy; in addition to making the application of existing models and creation of new models as simple as possible, MOSFiT yields statistically robust predictions for transient characteristics, with a standard output format that includes all the setup information necessary to reproduce a given result.

[ascl:1710.005] SkyNet: Modular nuclear reaction network library

The general-purpose nuclear reaction network SkyNet evolves the abundances of nuclear species under the influence of nuclear reactions. SkyNet can be used to compute the nucleosynthesis evolution in all astrophysical scenarios where nucleosynthesis occurs. Any list of isotopes can be evolved and SkyNet supports various different types of nuclear reactions. SkyNet is modular, permitting new or existing physics, such as nuclear reactions or equations of state, to be easily added or modified.

[ascl:1710.004] SPIPS: Spectro-Photo-Interferometry of Pulsating Stars

SPIPS (Spectro-Photo-Interferometry of Pulsating Stars) combines radial velocimetry, interferometry, and photometry to estimate physical parameters of pulsating stars, including presence of infrared excess, color excess, Teff, and ratio distance/p-factor. The global model-based parallax-of-pulsation method is implemented in Python. Derived parameters have a high level of confidence; statistical precision is improved (compared to other methods) due to the large number of data taken into account, accuracy is improved by using consistent physical modeling and reliability of the derived parameters is strengthened by redundancy in the data.

[ascl:1710.003] EXOFASTv2: Generalized publication-quality exoplanet modeling code

EXOFASTv2 improves upon EXOFAST (ascl:1207.001) for exoplanet modeling. It uses a differential evolution Markov Chain Monte Carlo code to fit an arbitrary number of transits (each with their own error scaling, normalization, TTV, and/or detrending parameters), an arbitrary number of RV sources (each with their own zero point and jitter), and an arbitrary number of planets, changing nothing but command line arguments and configuration files. The global model includes integrated isochrone and SED models to constrain the stellar properties and can accept priors on any fitted or derived quantities (e.g., parallax from Gaia). It is easily extensible to add additional effects or parameters.

[ascl:1710.002] rfpipe: Radio interferometric transient search pipeline

rfpipe supports Python-based analysis of radio interferometric data (especially from the Very Large Array) and searches for fast radio transients. This extends on the rtpipe library (ascl:1706.002) with new approaches to parallelization, acceleration, and more portable data products. rfpipe can run in standalone mode or be in a cluster environment.

[ascl:1710.001] vysmaw: Fast visibility stream muncher

The vysmaw client library facilitates the development of code for processes to tap into the fast visibility stream on the National Radio Astronomy Observatory's Very Large Array correlator back-end InfiniBand network. This uses the vys protocol to allow loose coupling to clients that need to remotely access memory over an Infiniband network.

[ascl:1709.011] FLaapLUC: Fermi-LAT automatic aperture photometry light curve

Most high energy sources detected with Fermi-LAT are blazars, which are highly variable sources. High cadence long-term monitoring simultaneously at different wavelengths being prohibitive, the study of their transient activities can help shed light on our understanding of these objects. The early detection of such potentially fast transient events is the key for triggering follow-up observations at other wavelengths. FLaapLUC (Fermi-LAT automatic aperture photometry Light C↔Urve) uses the simple aperture photometry approach to effectively detect relative flux variations in a set of predefined sources and alert potential users. Such alerts can then be used to trigger observations of these sources with other facilities. The FLaapLUC pipeline is built on top of the Science Tools provided by the Fermi-LAT collaboration and quickly generates short- or long-term Fermi-LAT light curves.

[ascl:1709.010] MagIC: Fluid dynamics in a spherical shell simulator

MagIC simulates fluid dynamics in a spherical shell. It solves for the Navier-Stokes equation including Coriolis force, optionally coupled with an induction equation for Magneto-Hydro Dynamics (MHD), a temperature (or entropy) equation and an equation for chemical composition under both the anelastic and the Boussinesq approximations. MagIC uses either Chebyshev polynomials or finite differences in the radial direction and spherical harmonic decomposition in the azimuthal and latitudinal directions. The time-stepping scheme relies on a semi-implicit Crank-Nicolson for the linear terms of the MHD equations and a Adams-Bashforth scheme for the non-linear terms and the Coriolis force.

[ascl:1709.009] bmcmc: MCMC package for Bayesian data analysis

bmcmc is a general purpose Markov Chain Monte Carlo package for Bayesian data analysis. It uses an adaptive scheme for automatic tuning of proposal distributions. It can also handle Bayesian hierarchical models by making use of the Metropolis-Within-Gibbs scheme.

[ascl:1709.008] celerite: Scalable 1D Gaussian Processes in C++, Python, and Julia

celerite provides fast and scalable Gaussian Process (GP) Regression in one dimension and is implemented in C++, Python, and Julia. The celerite API is designed to be familiar to users of george and, like george, celerite is designed to efficiently evaluate the marginalized likelihood of a dataset under a GP model. This is then be used alongside a non-linear optimization or posterior inference library for the best results.

celerite has been superceded by celerite2 (ascl:2310.001).

[ascl:1709.007] MSSC: Multi-Source Self-Calibration

Multi-Source Self-Calibration (MSSC) provides direction-dependent calibration to standard phase referencing. The code combines multiple faint sources detected within the primary beam to derive phase corrections. Each source has its CLEAN model divided into the visibilities which results in multiple point sources that are stacked in the uv plane to increase the S/N, thus permitting self-calibration. This process applies only to wide-field VLBI data sets that detect and image multiple sources within one epoch.

[ascl:1709.006] DCMDN: Deep Convolutional Mixture Density Network

Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

[ascl:1709.005] DanIDL: IDL solutions for science and astronomy

DanIDL provides IDL functions and routines for many standard astronomy needs, such as searching for matching points between two coordinate lists of two-dimensional points where each list corresponds to a different coordinate space, estimating the full-width half-maximum (FWHM) and ellipticity of the PSF of an image, calculating pixel variances for a set of calibrated image data, and fitting a 3-parameter plane model to image data. The library also supplies astrometry, general image processing, and general scientific applications.

[ascl:1709.004] DOOp: DAOSPEC Output Optimizer pipeline

The DAOSPEC Output Optimizer pipeline (DOOp) runs efficient and convenient equivalent widths measurements in batches of hundreds of spectra. It uses a series of BASH scripts to work as a wrapper for the FORTRAN code DAOSPEC (ascl:1011.002) and uses IRAF (ascl:9911.002) to automatically fix some of the parameters that are usually set by hand when using DAOSPEC. This allows batch-processing of quantities of spectra that would be impossible to deal with by hand. DOOp was originally built for the large quantity of UVES and GIRAFFE spectra produced by the Gaia-ESO Survey, but just like DAOSPEC, it can be used on any high resolution and high signal-to-noise ratio spectrum binned on a linear wavelength scale.

[ascl:1709.003] MeshLab: 3D triangular meshes processing and editing

MeshLab processes and edits 3D triangular meshes. It includes tools for editing, cleaning, healing, inspecting, rendering, texturing and converting meshes, and offers features for processing raw data produced by 3D digitization tools and devices and for preparing models for 3D printing.

[ascl:1709.002] PHANTOM: Smoothed particle hydrodynamics and magnetohydrodynamics code

Phantom is a smoothed particle hydrodynamics and magnetohydrodynamics code focused on stellar, galactic, planetary, and high energy astrophysics. It is modular, and handles sink particles, self-gravity, two fluid and one fluid dust, ISM chemistry and cooling, physical viscosity, non-ideal MHD, and more. Its modular structure makes it easy to add new physics to the code.

[ascl:1709.001] SPHYNX: SPH hydrocode for subsonic hydrodynamical instabilities and strong shocks

SPHYNX addresses subsonic hydrodynamical instabilities and strong shocks; it is Newtonian, grounded on the Euler-Lagrange formulation of the smoothed-particle hydrodynamics technique, and density based. SPHYNX uses an integral approach for estimating gradients, a flexible family of interpolators to suppress pairing instability, and incorporates volume elements to provides better partition of the unity.

[ascl:1708.030] GAMBIT: Global And Modular BSM Inference Tool

GAMBIT (Global And Modular BSM Inference Tool) performs statistical global fits of generic physics models using a wide range of particle physics and astrophysics data. Modules provide native simulations of collider and astrophysics experiments, a flexible system for interfacing external codes (the backend system), a fully featured statistical and parameter scanning framework, and additional tools for implementing and using hierarchical models.

[ascl:1708.029] iSEDfit: Bayesian spectral energy distribution modeling of galaxies

iSEDfit uses Bayesian inference to extract the physical properties of galaxies from their observed broadband photometric spectral energy distribution (SED). In its default mode, the inputs to iSEDfit are the measured photometry (fluxes and corresponding inverse variances) and a measurement of the galaxy redshift. Alternatively, iSEDfit can be used to estimate photometric redshifts from the input photometry alone.

After the priors have been specified, iSEDfit calculates the marginalized posterior probability distributions for the physical parameters of interest, including the stellar mass, star-formation rate, dust content, star formation history, and stellar metallicity. iSEDfit also optionally computes K-corrections and produces multiple "quality assurance" (QA) plots at each stage of the modeling procedure to aid in the interpretation of the prior parameter choices and subsequent fitting results. The software is distributed as part of the impro IDL suite.

[ascl:1708.028] ANA: Astrophysical Neutrino Anisotropy

ANA calculates the likelihood function for a model comprised of two components to the astrophysical neutrino flux detected by IceCube. The first component is extragalactic. Since point sources have not been found and there is increasing evidence that one source catalog cannot describe the entire data set, ANA models the extragalactic flux as isotropic. The second component is galactic. A variety of catalogs of interest are also provided. ANA takes the galactic contribution to be proportional to the matter density of the universe. The likelihood function has one free parameter fgal that is the fraction of the astrophysical flux that is galactic. ANA finds the best fit value of fgal and scans over 0<fgal<1.

[ascl:1708.027] empiriciSN: Supernova parameter generator

empiriciSN generates realistic supernova parameters given photometric observations of a potential host galaxy, based entirely on empirical correlations measured from supernova datasets. It is intended to be used to improve supernova simulation for DES and LSST. It is extendable such that additional datasets may be added in the future to improve the fitting algorithm or so that additional light curve parameters or supernova types may be fit.

[ascl:1708.026] XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

[ascl:1708.025] extinction-distances: Estimating distances to dark clouds

Extinction-distances uses the number of foreground stars and a Galactic model of the stellar distribution to estimate the distance to dark clouds. It exploits the relatively narrow range of intrinsic near-infrared colors of stars to separate foreground from background stars. An advantage of this method is that the distribution of stellar colors in the Galactic model need not be precisely correct, only the number density as a function of distance from the Sun.

[ascl:1708.024] ComEst: Completeness Estimator

ComEst calculates the completeness of CCD images conducted in astronomical observations saved in the FITS format. It estimates the completeness of the source finder SExtractor (ascl:1010.064) on the optical and near-infrared (NIR) imaging of point sources or galaxies as a function of flux (or magnitude) directly from the image itself. It uses PyFITS (ascl:1207.009) and GalSim (ascl:1402.009) to perform the end-to-end estimation of the completeness and can also estimate the purity of the source detection.

[ascl:1708.023] ExoSOFT: Exoplanet Simple Orbit Fitting Toolbox

ExoSOFT provides orbital analysis of exoplanets and binary star systems. It fits any combination of astrometric and radial velocity data, and offers four parameter space exploration techniques, including MCMC. It is packaged with an automated set of post-processing and plotting routines to summarize results, and is suitable for performing orbital analysis during surveys with new radial velocity and direct imaging instruments.

[ascl:1708.022] Naima: Derivation of non-thermal particle distributions through MCMC spectral fitting

Naima computes non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee (ascl:1303.002), an affine-invariant ensemble sampler for Markov Chain Monte Carlo. Naima is an Astropy (ascl:1304.002) affiliated package.

[ascl:1708.020] 4DAO: DAOSPEC interface

4DAO launches DAOSPEC (ascl:1011.002) for a large sample of spectra. Written in Fortran, the software allows one to easily manage the input and output files of DAOSPEC, optimize the main DAOSPEC parameters, and mask specific spectral regions. It also provides suitable graphical tools to evaluate the quality of the solution and provides final, normalized, zero radial velocity spectra.

[ascl:1708.019] SINFONI Pipeline: Data reduction pipeline for the Very Large Telescope SINFONI spectrograph

The SINFONI pipeline reduces data from the Very Large Telescope's SINFONI (Spectrograph for INtegral Field Observations in the Near Infrared) instrument. It can evaluate the detector linearity and generate a corresponding non linear pixel map, create a master dark and a hot-pixel map, a master flat and a map of pixels which have intensities greater than a given threshold. It can also compute the optical distortions and slitlets distances, and perform wavelength calibration, PSF, telluric standard and other science data reduction, and can coadd bad pixel maps, collapse a cube to an image over a given wavelength range, perform cube arithmetics, among other useful tasks.

[ascl:1708.018] CUTEX: CUrvature Thresholding EXtractor

CuTEx analyzes images in the infrared bands and extracts sources from complex backgrounds, particularly star-forming regions that offer the challenges of crowding, having a highly spatially variable background, and having no-psf profiles such as protostars in their accreting phase. The code is composed of two main algorithms, the first an algorithm for source detection, and the second for flux extraction. The code is originally written in IDL language and it was exported in the license free GDL language. CuTEx could be used in other bands or in scientific cases different from the native case.

This software is also available as an on-line tool from the Multi-Mission Interactive Archive web pages dedicated to the Herschel Observatory.

[ascl:1708.017] LCC: Light Curves Classifier

Light Curves Classifier uses data mining and machine learning to obtain and classify desired objects. This task can be accomplished by attributes of light curves or any time series, including shapes, histograms, or variograms, or by other available information about the inspected objects, such as color indices, temperatures, and abundances. After specifying features which describe the objects to be searched, the software trains on a given training sample, and can then be used for unsupervised clustering for visualizing the natural separation of the sample. The package can be also used for automatic tuning parameters of used methods (for example, number of hidden neurons or binning ratio).

Trained classifiers can be used for filtering outputs from astronomical databases or data stored locally. The Light Curve Classifier can also be used for simple downloading of light curves and all available information of queried stars. It natively can connect to OgleII, OgleIII, ASAS, CoRoT, Kepler, Catalina and MACHO, and new connectors or descriptors can be implemented. In addition to direct usage of the package and command line UI, the program can be used through a web interface. Users can create jobs for ”training” methods on given objects, querying databases and filtering outputs by trained filters. Preimplemented descriptors, classifier and connectors can be picked by simple clicks and their parameters can be tuned by giving ranges of these values. All combinations are then calculated and the best one is used for creating the filter. Natural separation of the data can be visualized by unsupervised clustering.

[ascl:1708.016] pyLCSIM: X-ray lightcurves simulator

pyLCSIM simulates X-ray lightcurves from coherent signals and power spectrum models. Coherent signals can be specified as a sum of one or more sinusoids, each with its frequency, pulsed fraction and phase shift; or as a series of harmonics of a fundamental frequency (each with its pulsed fraction and phase shift). Power spectra can be simulated from a model of the power spectrum density (PSD) using as a template one or more of the built-in library functions. The user can also define his/her custom models. Models are additive.

[ascl:1708.021] KERTAP: Strong lensing effects of Kerr black holes

KERTAP computes the strong lensing effects of Kerr black holes, including the effects on polarization. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles.

[ascl:1708.015] TWO-POP-PY: Two-population dust evolution model

TWO-POP-PY runs a two-population dust evolution model that follows the upper end of the dust size distribution and the evolution of the dust surface density profile and treats dust surface density, maximum particle size, small and large grain velocity, and fragmentation. It derives profiles that describe the dust-to-gas ratios and the dust surface density profiles well in protoplanetary disks, in addition to the radial flux by solid material rain out.

[ascl:1708.014] PACSman: IDL Suite for Herschel/PACS spectrometer data

PACSman provides an alternative for several reduction and analysis steps performed in HIPE (ascl:1111.001) on PACS spectroscopic data; it is written in IDL. Among the operations possible with it are transient correction, line fitting, map projection, and map analysis, and unchopped scan, chop/nod, and the decommissioned wavelength switching observation modes are supported.

[ascl:1708.013] GMM: Gaussian Mixture Modeling

GMM (Gaussian Mixture Modeling) tests the existence of bimodality in globular cluster color distributions. GMM uses three indicators to distinguish unimodal and bimodal distributions: the kurtosis of the distribution, the separation of the peaks, and the probability of obtaining the same χ2 from a unimodal distribution.

[ascl:1708.012] GANDALF: Gas AND Absorption Line Fitting

GANDALF (Gas AND Absorption Line Fitting) accurately separates the stellar and emission-line contributions to observed spectra. The IDL code includes reddening by interstellar dust and also returns formal errors on the position, width, amplitude and flux of the emission lines. Example wrappers that make use of pPXF (ascl:1210.002) to derive the stellar kinematics are included.

[ascl:1708.011] RM-CLEAN: RM spectra cleaner

RM-CLEAN reads in dirty Q and U cubes, generates rmtf based on the frequencies given in an ASCII file, and cleans the RM spectra following the algorithm given by Brentjens (2007). The output cubes contain the clean model components and the CLEANed RM spectra. The input cubes must be reordered with mode=312, and the output cubes will have the same ordering and thus must be reordered after being written to disk. RM-CLEAN runs as a MIRIAD (ascl:1106.007) task and a Python wrapper is included with the code.

[ascl:1708.010] BAGEMASS: Bayesian age and mass estimates for transiting planet host stars

BAGEMASS calculates the posterior probability distribution for the mass and age of a star from its observed mean density and other observable quantities using a grid of stellar models that densely samples the relevant parameter space. It is written in Fortran and requires FITSIO (ascl:1010.001).

[ascl:1708.009] FIEStool: Automated data reduction for FIber-fed Echelle Spectrograph (FIES)

FIEStool automatically reduces data obtained with the FIber-fed Echelle Spectrograph (FIES) at the Nordic Optical Telescope, a high-resolution spectrograph available on a stand-by basis, while also allowing the basic properties of the reduction to be controlled in real time by the user. It provides a Graphical User Interface and offers bias subtraction, flat-fielding, scattered-light subtraction, and specialized reduction tasks from the external packages IRAF (ascl:9911.002) and NumArray. The core of FIEStool is instrument-independent; the software, written in Python, could with minor modifications also be used for automatic reduction of data from other instruments.

[ascl:1708.008] ALCHEMIC: Advanced time-dependent chemical kinetics

ALCHEMIC solves chemical kinetics problems, including gas-grain interactions, surface reactions, deuterium fractionization, and transport phenomena and can model the time-dependent chemical evolution of molecular clouds, hot cores, corinos, and protoplanetary disks.

[ascl:1708.007] PBMC: Pre-conditioned Backward Monte Carlo code for radiative transport in planetary atmospheres

PBMC (Pre-Conditioned Backward Monte Carlo) solves the vector Radiative Transport Equation (vRTE) and can be applied to planetary atmospheres irradiated from above. The code builds the solution by simulating the photon trajectories from the detector towards the radiation source, i.e. in the reverse order of the actual photon displacements. In accounting for the polarization in the sampling of photon propagation directions and pre-conditioning the scattering matrix with information from the scattering matrices of prior (in the BMC integration order) photon collisions, PBMC avoids the unstable and biased solutions of classical BMC algorithms for conservative, optically-thick, strongly-polarizing media such as Rayleigh atmospheres.

[ascl:1708.006] DISORT: DIScrete Ordinate Radiative Transfer

DISORT (DIScrete Ordinate Radiative Transfer) solves the problem of 1D scalar radiative transfer in a single optical medium, such as a planetary atmosphere. The code correctly accounts for multiple scattering by an isotropic or plane-parallel beam source, internal Planck sources, and reflection from a lower boundary. Provided that polarization effects can be neglected, DISORT efficiently calculates accurate fluxes and intensities at any user-specified angle and location within the user-specified medium.

[ascl:1708.005] STools: IDL Tools for Spectroscopic Analysis

STools contains a variety of simple tools for spectroscopy, such as reading an IRAF-formatted (multispec) echelle spectrum in FITS, measuring the wavelength of the center of a line, Gaussian convolution, deriving synthetic photometry from an input spectrum, and extracting and interpolating a MARCS model atmosphere (standard composition).

[ascl:1708.003] CRISPRED: CRISP imaging spectropolarimeter data reduction pipeline

CRISPRED reduces data from the CRISP imaging spectropolarimeter at the Swedish 1 m Solar Telescope (SST). It performs fitting routines, corrects optical aberrations from atmospheric turbulence as well as from the optics, and compensates for inter-camera misalignments, field-dependent and time-varying instrumental polarization, and spatial variation in the detector gain and in the zero level offset (bias). It has an object-oriented IDL structure with computationally demanding routines performed in C subprograms called as dynamically loadable modules (DLMs).

[ascl:1708.002] CINE: Comet INfrared Excitation

CINE calculates infrared pumping efficiencies that can be applied to the most common molecules found in cometary comae such as water, hydrogen cyanide or methanol. One of the main mechanisms for molecular excitation in comets is the fluorescence by the solar radiation followed by radiative decay to the ground vibrational state. This command-line tool calculates the effective pumping rates for rotational levels in the ground vibrational state scaled by the heliocentric distance of the comet. Fluorescence coefficients are useful for modeling rotational emission lines observed in cometary spectra at sub-millimeter wavelengths. Combined with computational methods to solve the radiative transfer equations based, e.g., on the Monte Carlo algorithm, this model can retrieve production rates and rotational temperatures from the observed emission spectrum.

[ascl:1708.001] ATOOLS: A command line interface to the AST library

The ATOOLS package of applications provides an interface to the AST library (ascl:1404.016), allowing quick experiments to be performed from the shell. It manipulates descriptions of coordinate frames and mappings in the form of AST objects and performs other functions, with each application within the package corresponding closely to one of the functions in the AST library.

[ascl:1707.007] swot: Super W Of Theta

SWOT (Super W Of Theta) computes two-point statistics for very large data sets, based on “divide and conquer” algorithms, mainly, but not limited to data storage in binary trees, approximation at large scale, parellelization (open MPI), and bootstrap and jackknife resampling methods “on the fly”. It currently supports projected and 3D galaxy auto and cross correlations, galaxy-galaxy lensing, and weighted histograms.

[ascl:1707.006] Gala: Galactic astronomy and gravitational dynamics

Gala is a Python package (and Astropy affiliated package) for Galactic astronomy and gravitational dynamics. The bulk of the package centers around implementations of gravitational potentials, numerical integration, nonlinear dynamics, and astronomical velocity transformations (i.e. proper motions). Gala uses the Astropy units and coordinates subpackages extensively to provide a clean, pythonic interface to these features but does any heavy-lifting in C and Cython for speed.
20221218 aa: Updated ADS links to new ADS format; updated site links from http: to https:

[ascl:1707.005] PyMOC: Multi-Order Coverage map module for Python

PyMOC manipulates Multi-Order Coverage (MOC) maps. It supports reading and writing the three encodings mentioned in the IVOA MOC recommendation: FITS, JSON and ASCII.

[ascl:1707.004] CCFpams: Atmospheric stellar parameters from cross-correlation functions

CCFpams allows the measurement of stellar temperature, metallicity and gravity within a few seconds and in a completely automated fashion. Rather than performing comparisons with spectral libraries, the technique is based on the determination of several cross-correlation functions (CCFs) obtained by including spectral features with different sensitivity to the photospheric parameters. Literature stellar parameters of high signal-to-noise (SNR) and high-resolution HARPS spectra of FGK Main Sequence stars are used to calibrate the stellar parameters as a function of CCF areas.

[ascl:1707.003] pyaneti: Multi-planet radial velocity and transit fitting

Pyaneti is a multi-planet radial velocity and transit fit software. The code uses Markov chain Monte Carlo (MCMC) methods with a Bayesian approach and a parallelized ensemble sampler algorithm in Fortran which makes the code fast. It creates posteriors, correlations, and ready-to-publish plots automatically, and handles circular and eccentric orbits. It is capable of multi-planet fitting and handles stellar limb darkening, systemic velocities for multiple instruments, and short and long cadence data, and offers additional capabilities.

[ascl:1707.002] SASRST: Semi-Analytic Solutions for 1-D Radiative Shock Tubes

SASRST, a small collection of Python scripts, attempts to reproduce the semi-analytical one-dimensional equilibrium and non-equilibrium radiative shock tube solutions of Lowrie & Rauenzahn (2007) and Lowrie & Edwards (2008), respectively. The included code calculates the solution for a given set of input parameters and also plots the results using Matplotlib. This software was written to provide validation for numerical radiative shock tube solutions produced by a radiation hydrodynamics code.

[ascl:1707.001] HRM: HII Region Models

HII Region Models fits HII region models to observed radio recombination line and radio continuum data. The algorithm includes the calculations of departure coefficients to correct for non-LTE effects. HII Region Models has been used to model star formation in the nucleus of IC 342.

[ascl:1706.012] KeplerSolver: Kepler equation solver

KeplerSolver solves Kepler's equation for arbitrary epoch and eccentricity, using continued fractions. It is written in C and its speed is nearly the same as the SWIFT routines, while achieving machine precision. It comes with a test program to demonstrate usage.

[ascl:1706.011] PyPulse: PSRFITS handler

PyPulse handles PSRFITS files and performs subsequent analyses on pulse profiles.

[ascl:1706.010] EXOSIMS: Exoplanet Open-Source Imaging Mission Simulator

EXOSIMS generates and analyzes end-to-end simulations of space-based exoplanet imaging missions. The software is built up of interconnecting modules describing different aspects of the mission, including the observatory, optical system, and scheduler (encoding mission rules) as well as the physical universe, including the assumed distribution of exoplanets and their physical and orbital properties. Each module has a prototype implementation that is inherited by specific implementations for different missions concepts, allowing for the simulation of widely variable missions.

[submitted] Kliko - The Scientific Compute Container Format

We present Kliko, a Docker based container specification for running one or multiple related compute jobs. The key concepts of Kliko is the encapsulation of data processing software into a container and the formalisation of the input, output and task parameters. Formalisation is realised by bundling a container with a Kliko file, which describes the IO and task parameters. This Kliko container can then be opened and run by a Kliko runner. The Kliko runner will parse the Kliko definition and gather the values for these parameters, for example by requesting user input or pre defined values in a script. Parameters can be various primitive types, for example float, int or the path to a file. This paper will also discuss the implementation of a support library named Kliko which can be used to create Kliko containers, parse Kliko definitions, chain Kliko containers in workflows using, for example, Luigi a workflow manager. The Kliko library can be used inside the container interact with the Kliko runner. Finally this paper will discuss two reference implementations based on Kliko: RODRIGUES, a web based Kliko container schedular and output visualiser specifically for astronomical data, and VerMeerKAT, a multi container workflow data reduction pipeline which is being used as a prototype pipeline for the commisioning of the MeerKAT radio telescope.

[ascl:1706.009] sick: Spectroscopic inference crank

sick infers astrophysical parameters from noisy observed spectra. Phenomena that can alter the data (e.g., redshift, continuum, instrumental broadening, outlier pixels) are modeled and simultaneously inferred with the astrophysical parameters of interest. This package relies on emcee (ascl:1303.002); it is best suited for situations where a grid of model spectra already exists, and one would like to infer model parameters given some data.

[ascl:1706.008] the-wizz: Clustering redshift estimation code

the-wizz clusters redshift estimates for any photometric unknown sample in a survey. The software is composed of two main parts: a pair finder and a pdf maker. The pair finder finds spatial pairs and stores the indices of all closer pairs around target reference objects in an output HDF5 data file. Users then query this data file using the indices of their unknown sample to produce an output clustering-z.

[ascl:1706.007] encube: Large-scale comparative visualization and analysis of sets of multidimensional data

Encube is a qualitative, quantitative and comparative visualization and analysis framework, with application to high-resolution, immersive three-dimensional environments and desktop displays, providing a capable visual analytics experience across the display ecology. Encube includes mechanisms for the support of: 1) interactive visual analytics of sufficiently large subsets of data; 2) synchronous and asynchronous collaboration; and 3) documentation of the discovery workflow. The framework is modular, allowing additional functionalities to be included as required.

[ascl:1706.006] GenPK: Power spectrum generator

GenPK generates the 3D matter power spectra for each particle species from a Gadget snapshot. Written in C++, it requires both FFTW3 and GadgetReader.

[ascl:1706.005] LMC: Logarithmantic Monte Carlo

LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).

[ascl:1706.004] Dark Sage: Semi-analytic model of galaxy evolution

DARK SAGE is a semi-analytic model of galaxy formation that focuses on detailing the structure and evolution of galaxies' discs. The code-base, written in C, is an extension of SAGE (ascl:1601.006) and maintains the modularity of SAGE. DARK SAGE runs on any N-body simulation with trees organized in a supported format and containing a minimum set of basic halo properties.

[ascl:1706.003] DaMaSCUS: Dark Matter Simulation Code for Underground Scatterings

DaMaSCUS calculates the density and velocity distribution of dark matter (DM) at any detector of given depth and latitude to provide dark matter particle trajectories inside the Earth. Provided a strong enough DM-matter interaction, the particles scatter on terrestrial atoms and get decelerated and deflected. The resulting local modifications of the DM velocity distribution and number density can have important consequences for direct detection experiments, especially for light DM, and lead to signatures such as diurnal modulations depending on the experiment's location on Earth. The code involves both the Monte Carlo simulation of particle trajectories and generation of data as well as the data analysis consisting of non-parametric density estimation of the local velocity distribution functions and computation of direct detection event rates.

[ascl:1706.002] rtpipe: Searching for Fast Radio Transients in Interferometric Data

rtpipe (real-time pipeline) analyzes radio interferometric data with an emphasis on searching for transient or variable astrophysical sources. The package combines single-dish concepts such as dedispersion and filters with interferometric concepts, including images and the uv-plane. In contrast to time-domain data recorded with large single-dish telescopes, visibilities from interferometers can precisely localize sources anywhere in the entire field of view. rtpipe opens interferometers to the study of fast transient sky, including sources like pulsars, stellar flares, rotating radio transients, and fast radio bursts. Key portions of the search pipeline, such as image generation and dedispersion, have been accelerated. That, in combination with its multi-threaded, multi-node design, makes rtpipe capable of searching millisecond timescale data in real time on small compute clusters.

[ascl:1706.001] Exotrending: Fast and easy-to-use light curve detrending software for exoplanets

The simple, straightforward Exotrending code detrends exoplanet transit light curves given a light curve (flux versus time) and good ephemeris (epoch of first transit and orbital period). The code has been tested with Kepler and K2 light curves and should work with any other light curve.

[ascl:1705.017] supernovae: Photometric classification of supernovae

Supernovae classifies supernovae using their light curves directly as inputs to a deep recurrent neural network, which learns information from the sequence of observations. Observational time and filter fluxes are used as inputs; since the inputs are agnostic, additional data such as host galaxy information can also be included.

[ascl:1705.016] astroABC: Approximate Bayesian Computation Sequential Monte Carlo sampler

astroABC is a Python implementation of an Approximate Bayesian Computation Sequential Monte Carlo (ABC SMC) sampler for parameter estimation. astroABC allows for massive parallelization using MPI, a framework that handles spawning of processes across multiple nodes. It has the ability to create MPI groups with different communicators, one for the sampler and several others for the forward model simulation, which speeds up sampling time considerably. For smaller jobs the Python multiprocessing option is also available.

[ascl:1705.015] WeirdestGalaxies: Outlier Detection Algorithm on Galaxy Spectra

WeirdestGalaxies finds the weirdest galaxies in the Sloan Digital Sky Survey (SDSS) by using a basic outlier detection algorithm. It uses an unsupervised Random Forest (RF) algorithm to assign a similarity measure (or distance) between every pair of galaxy spectra in the SDSS. It then uses the distance matrix to find the galaxies that have the largest distance, on average, from the rest of the galaxies in the sample, and defined them as outliers.

[ascl:1705.014] NPTFit: Non-Poissonian Template Fitting

NPTFit is a specialized Python/Cython package that implements Non-Poissonian Template Fitting (NPTF), originally developed for characterizing populations of unresolved point sources. It offers fast evaluation of likelihoods for NPTF analyses and has an easy-to-use interface for performing non-Poissonian (as well as standard Poissonian) template fits using MultiNest (ascl:1109.006) or other inference tools. It allows inclusion of an arbitrary number of point source templates, with an arbitrary number of degrees of freedom in the modeled flux distribution, and has modules for analyzing and plotting the results of an NPTF.

[ascl:1705.013] PSOAP: Precision Spectroscopic Orbits A-Parametrically

PSOAP (Precision Spectroscopic Orbits A-Parametrically) uses Gaussian processes to infer component spectra of single-lined and double-lined spectroscopic binaries, while simultaneously exploring the posteriors of the orbital parameters and the spectra themselves. PSOAP accounts for the natural λ-covariances in each spectrum, thus providing a natural "de-noising" of the spectra typically offered by Fourier techniques.

[ascl:1705.012] fd3: Spectral disentangling of double-lined spectroscopic binary stars

The spectral disentangling technique can be applied on a time series of observed spectra of a spectroscopic double-lined binary star (SB2) to determine the parameters of orbit and reconstruct the spectra of component stars, without the use of template spectra. fd3 disentangles the spectra of SB2 stars, capable also of resolving the possible third companion. It performs the separation of spectra in the Fourier space which is faster, but in several respects less versatile than the wavelength-space separation. (Wavelength-space separation is implemented in the twin code CRES.) fd3 is written in C and is designed as a command-line utility for a Unix-like operating system. fd3 is a new version of FDBinary (ascl:1705.011), which is now deprecated.

[ascl:1705.011] FDBinary: A tool for spectral disentangling of double-lined spectroscopic binary stars

FDBinary disentangles spectra of SB2 stars. The spectral disentangling technique can be applied on a time series of observed spectra of an SB2 to determine the parameters of orbit and reconstruct the spectra of component stars, without the use of template spectra. The code is written in C and is designed as a command-line utility for a Unix-like operating system. FDBinary uses the Fourier-space approach in separation of composite spectra. This code has been replaced with the newer fd3 (ascl:1705.012).

[ascl:1705.010] PROFILER: 1D galaxy light profile decomposition

Written in Python, PROFILER analyzes the radial surface brightness profiles of galaxies. It accurately models a wide range of galaxies and galaxy components, such as elliptical galaxies, the bulges of spiral and lenticular galaxies, nuclear sources, discs, bars, rings, and spiral arms with a variety of parametric functions routinely employed in the field (Sérsic, core-Sérsic, exponential, Gaussian, Moffat and Ferrers). In addition, Profiler can employ the broken exponential model (relevant for disc truncations or antitruncations) and two special cases of the edge-on disc model: namely along the major axis (in the disc plane) and along the minor axis (perpendicular to the disc plane).

[ascl:1705.009] LensPop: Galaxy-galaxy strong lensing population simulation

LensPop simulates observations of the galaxy-galaxy strong lensing population in the Dark Energy Survey (DES), the Large Synoptic Survey Telescope (LSST), and Euclid surveys.

[ascl:1705.008] MBProj2: Multi-Band x-ray surface brightness PROJector 2

MBProj2 obtains thermodynamic profiles of galaxy clusters. It forward-models cluster X-ray surface brightness profiles in multiple bands, optionally assuming hydrostatic equilibrium. The code is a set of Python classes the user can use or extend. When modelling a cluster assuming hydrostatic equilibrium, the user chooses a form for the density profile (e.g. binning or a beta model), the metallicity profile, and the dark matter profile (e.g. NFW). If hydrostatic equilibrium is not assumed, a temperature profile model is used instead of the dark matter profile. The code uses the emcee Markov Chain Monte Carlo code (ascl:1303.002) to sample the model parameters, using these to produce chains of thermodynamic profiles.

[submitted] HHTpywrapper: Python Wrapper for Hilbert–Huang Transform MATLAB Package

HHTpywrapper is a python interface to call the Hilbert–Huang Transform (HHT) MATLAB package. HHT is a time-frequency analysis method to adaptively decompose a signal, that could be generated by non-stationary and/or nonlinear processes, into basis components at different timescales, and then Hilbert transform these components into instantaneous phases, frequencies and amplitudes as functions of time. HHT has been successfully applied to analyzing X-ray quasi-periodic oscillations (QPOs) from the active galactic nucleus RE J1034+396 (Hu et al. 2014) and two black hole X-ray binaries, XTE J1550–564 (Su et al. 2015) and GX 339-4 (Su et al. 2017). HHTpywrapper provides examples of reproducing HHT analysis results in Su et al. (2015) and Su et al. (2017). This project is originated from the Astro Hack Week 2015.

[ascl:1705.007] getimages: Background derivation and image flattening method

getimages performs background derivation and image flattening for high-resolution images obtained with space observatories. It is based on median filtering with sliding windows corresponding to a range of spatial scales from the observational beam size up to a maximum structure width X. The latter is a single free parameter of getimages that can be evaluated manually from the observed image. The median filtering algorithm provides a background image for structures of all widths below X. The same median filtering procedure applied to an image of standard deviations derived from a background-subtracted image results in a flattening image. Finally, a flattened image is computed by dividing the background-subtracted by the flattening image. Standard deviations in the flattened image are now uniform outside sources and filaments. Detecting structures in such radically simplified images results in much cleaner extractions that are more complete and reliable. getimages also reduces various observational and map-making artifacts and equalizes noise levels between independent tiles of mosaicked images. The code (a Bash script) uses FORTRAN utilities from getsources (ascl:1507.014), which must be installed.

[ascl:1705.006] f3: Full Frame Fotometry for Kepler Full Frame Images

Light curves from the Kepler telescope rely on "postage stamp" cutouts of a few pixels near each of 200,000 target stars. These light curves are optimized for the detection of short-term signals like planet transits but induce systematics that overwhelm long-term variations in stellar flux. Longer-term effects can be recovered through analysis of the Full Frame Images, a set of calibration data obtained monthly during the Kepler mission. The Python package f3 analyzes the Full Frame Images to infer long-term astrophysical variations in the brightness of Kepler targets, such as magnetic activity or sunspots on slowly rotating stars.

[ascl:1705.005] SPTCLASS: SPecTral CLASSificator code

SPTCLASS assigns semi-automatic spectral types to a sample of stars. The main code includes three spectral classification schemes: the first one is optimized to classify stars in the mass range of TTS (K5 or later, hereafter LATE-type scheme); the second one is optimized to classify stars in the mass range of IMTTS (F late to K early, hereafter Gtype scheme), and the third one is optimized to classify stars in the mass range of HAeBe (F5 or earlier, hereafter HAeBe scheme). SPTCLASS has an interactive module that allows the user to select the best result from the three schemes and analyze the input spectra.

[ascl:1705.004] PCAT: Probabilistic Cataloger

PCAT (Probabilistic Cataloger) samples from the posterior distribution of a metamodel, i.e., union of models with different dimensionality, to compare the models. This is achieved via transdimensional proposals such as births, deaths, splits and merges in addition to the within-model proposals. This method avoids noisy estimates of the Bayesian evidence that may not reliably distinguish models when sampling from the posterior probability distribution of each model.

The code has been applied in two different subfields of astronomy: high energy photometry, where transdimensional elements are gamma-ray point sources; and strong lensing, where light-deflecting dark matter subhalos take the role of transdimensional elements.

[ascl:1705.003] demc2: Differential evolution Markov chain Monte Carlo parameter estimator

demc2, also abbreviated as DE-MCMC, is a differential evolution Markov Chain parameter estimation library written in R for adaptive MCMC on real parameter spaces.

[ascl:1705.002] DMATIS: Dark Matter ATtenuation Importance Sampling

DMATIS (Dark Matter ATtenuation Importance Sampling) calculates the trajectories of DM particles that propagate in the Earth's crust and the lead shield to reach the DAMIC detector using an importance sampling Monte-Carlo simulation. A detailed Monte-Carlo simulation avoids the deficiencies of the SGED/KS method that uses a mean energy loss description to calculate the lower bound on the DM-proton cross section. The code implementing the importance sampling technique makes the brute-force Monte-Carlo simulation of moderately strongly interacting DM with nucleons computationally feasible. DMATIS is written in Python 3 and MATHEMATICA.

[ascl:1705.001] COSMOS: Carnegie Observatories System for MultiObject Spectroscopy

COSMOS (Carnegie Observatories System for MultiObject Spectroscopy) reduces multislit spectra obtained with the IMACS and LDSS3 spectrographs on the Magellan Telescopes. It can be used for the quick-look analysis of data at the telescope as well as for pipeline reduction of large data sets. COSMOS is based on a precise optical model of the spectrographs, which allows (after alignment and calibration) an accurate prediction of the location of spectra features. This eliminates the line search procedure which is fundamental to many spectral reduction programs, and allows a robust data pipeline to be run in an almost fully automatic mode, allowing large amounts of data to be reduced with minimal intervention.

[ascl:1704.014] Multipoles: Potential gain for binary lens estimation

Multipoles, written in Python, calculates the quadrupole and hexadecapole approximations of the finite-source magnification: quadrupole (Wk,rho,Gamma) and hexadecapole (Wk,rho,Gamma). The code is efficient and faster than previously available methods, and could be generalized for use on large portions of the light curves.

[ascl:1704.013] Difference-smoothing: Measuring time delay from light curves

The Difference-smoothing MATLAB code measures the time delay from the light curves of images of a gravitationally lendsed quasar. It uses a smoothing timescale free parameter, generates more realistic synthetic light curves to estimate the time delay uncertainty, and uses X2 plot to assess the reliability of a time delay measurement as well as to identify instances of catastrophic failure of the time delay estimator. A systematic bias in the measurement of time delays for some light curves can be eliminated by applying a correction to each measured time delay.

[ascl:1704.012] XID+: Next generation XID development

XID+ is a prior-based source extraction tool which carries out photometry in the Herschel SPIRE (Spectral and Photometric Imaging Receiver) maps at the positions of known sources. It uses a probabilistic Bayesian framework that provides a natural framework in which to include prior information, and uses the Bayesian inference tool Stan to obtain the full posterior probability distribution on flux estimates.

[ascl:1704.011] VULCAN: Chemical Kinetics For Exoplanetary Atmospheres

VULCAN describes gaseous chemistry from 500 to 2500 K using a reduced C-H-O chemical network with about 300 reactions. It uses eddy diffusion to mimic atmospheric dynamics and excludes photochemistry, and can be used to examine the theoretical trends produced when the temperature-pressure profile and carbon-to-oxygen ratio are varied.

[ascl:1704.010] A-Track: Detecting Moving Objects in FITS images

A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

[ascl:1704.009] Photo-z-SQL: Photometric redshift estimation framework

Photo-z-SQL is a flexible template-based photometric redshift estimation framework that can be seamlessly integrated into a SQL database (or DB) server and executed on demand in SQL. The DB integration eliminates the need to move large photometric datasets outside a database for redshift estimation, and uses the computational capabilities of DB hardware. Photo-z-SQL performs both maximum likelihood and Bayesian estimation and handles inputs of variable photometric filter sets and corresponding broad-band magnitudes.

[ascl:1704.008] Transit: Radiative-transfer code for planetary atmospheres

Transit calculates the transmission or emission spectrum of a planetary atmosphere with application to extrasolar-planet transit and eclipse observations, respectively. It computes the spectra by solving the one-dimensional line-by-line radiative-transfer equation for an atmospheric model.

[ascl:1704.007] PySM: Python Sky Model

PySM generates full-sky simulations of Galactic foregrounds in intensity and polarization relevant for CMB experiments. The components simulated are thermal dust, synchrotron, AME, free-free, and CMB at a given Nside, with an option to integrate over a top hat bandpass, to add white instrument noise, and to smooth with a given beam. PySM is based on the large-scale Galactic part of Planck Sky Model code and uses some of its inputs.

[ascl:1704.006] Quickclump: Identify clumps within a 3D FITS datacube

Quickclump finds clumps in a 3D FITS datacube. It is a fast, accurate, and automated tool written in Python. Though Quickclump is primarily intended for decomposing observations of interstellar clouds into individual clumps, it can also be used for finding clumps in any 3D rectangular data.

[ascl:1704.005] VaST: Variability Search Toolkit

VaST (Variability Search Toolkit) finds variable objects on a series of astronomical images in FITS format. The software performs object detection and aperture photometry using SExtractor (ascl:1010.064) on each image, cross-matches lists of detected stars, performs magnitude calibration with respect to the first (reference) image and constructs a lightcurve for each object. The sigma-magnitude, Stetson's L variability index, Robust Median Statistic (RoMS) and other plots may be used to visually identify variable star candidates. The two distinguishing features of VaST are its ability to perform accurate aperture photometry of images obtained with non-linear detectors and to handle complex image distortions. VaST can be used in cases of unstable PSF (e.g., bad guiding or with digitized wide-field photographic images), and has been successfully applied to images obtained with telescopes ranging from 0.08 to 2.5m in diameter equipped with a variety of detectors including CCD, CMOS, MIC and photographic plates.

[ascl:1704.004] STATCONT: Statistical continuum level determination method for line-rich sources

STATCONT determines the continuum emission level in line-rich spectral data by inspecting the intensity distribution of a given spectrum by using different statistical approaches. The sigma-clipping algorithm provides the most accurate continuum level determination, together with information on the uncertainty in its determination; this uncertainty is used to correct the final continuum emission level. In general, STATCONT obtains accuracies of < 10 % in the continuum determination, and < 5 % in most cases. The main products of the software are the continuum emission level, together with its uncertainty, and data cubes containing only spectral line emission, i.e. continuum-subtracted data cubes. STATCONT also includes the option to estimate the spectral index or variation of the continuum emission with frequency.

[ascl:1704.003] Shwirl: Meaningful coloring of spectral cube data with volume rendering

Shwirl visualizes spectral data cubes with meaningful coloring methods. The program has been developed to investigate transfer functions, which combines volumetric elements (or voxels) to set the color, and graphics shaders, functions used to compute several properties of the final image such as color, depth, and/or transparency, as enablers for scientific visualization of astronomical data. The program uses Astropy (ascl:1304.002) to handle FITS files and World Coordinate System, Qt (and PyQt) for the user interface, and VisPy, an object-oriented Python visualization library binding onto OpenGL.

[ascl:1704.002] UDAT: A multi-purpose data analysis tool

UDAT is a pattern recognition tool for mass analysis of various types of data, including image and audio. Based on its WND-CHARM (ascl:1312.002) prototype, UDAT computed a large set of numerical content descriptors from each file it analyzes, and selects the most informative features using statistical analysis. The tool can perform automatic classification of galaxy images by training with annotated galaxy images. It also has unsupervised learning capabilities, such as query-by-example of galaxies based on morphology. That is, given an input galaxy image of interest, the tool can search through a large database of images to retrieve the galaxies that are the most similar to the query image. The downside of the tool is its computational complexity, which in most cases will require a small or medium cluster.

[ascl:1704.001] pwkit: Astronomical utilities in Python

pwkit is a collection of miscellaneous astronomical utilities in Python, with an emphasis on radio astronomy, reading and writing various data formats, and convenient command-line utilities. Utilities include basic astronomical calculations, data visualization tools such as mapping arbitrary data to color scales and tracing contours, and data input and output utilities such as streaming output from other programs.

[ascl:1703.015] Charm: Cosmic history agnostic reconstruction method

Charm (cosmic history agnostic reconstruction method) reconstructs the cosmic expansion history in the framework of Information Field Theory. The reconstruction is performed via the iterative Wiener filter from an agnostic or from an informative prior. The charm code allows one to test the compatibility of several different data sets with the LambdaCDM model in a non-parametric way.

[ascl:1703.014] MC-SPAM: Monte-Carlo Synthetic-Photometry/Atmosphere-Model

MC-SPAM (Monte-Carlo Synthetic-Photometry/Atmosphere-Model) generates limb-darkening coefficients from models that are comparable to transit photometry; it extends the original SPAM algorithm by Howarth (2011) by taking in consideration the uncertainty on the stellar and transit parameters of the system under analysis.

[ascl:1703.013] Atmospheric Athena: 3D Atmospheric escape model with ionizing radiative transfer

Atmospheric Athena simulates hydrodynamic escape from close-in giant planets in 3D. It uses the Athena hydrodynamics code (ascl:1010.014) with a new ionizing radiative transfer implementation to self-consistently model photoionization driven winds from the planet. The code is fully compatible with static mesh refinement and MPI parallelization and can handle arbitrary planet potentials and stellar initial conditions.

[ascl:1703.012] ICICLE: Initial Conditions for Isolated CoLlisionless systEms

ICICLE (Initial Conditions for Isolated CoLlisionless systEms) generates stable initial conditions for isolated collisionless systems that can then be used in NBody simulations. It supports the Navarro-Frenk-White, Hernquist, King and Einasto density profiles.

[ascl:1703.011] QtClassify: IFS data emission line candidates classifier

QtClassify is a GUI that helps classify emission lines found in integral field spectroscopic data. Input needed is a datacube as well as a catalog with emission lines and a signal-to-noise cube, such at that created by LSDCat (ascl:1612.002). The main idea is to take each detected line and guess what line it could be (and thus the redshift of the object). You would expect to see other lines that might not have been detected but are visible in the cube if you know where to look, which is why parts of the spectrum are shown where other lines are expected. In addition, monochromatic layers of the datacube are displayed, making it easy to spot additional emission lines.

[ascl:1703.010] TransitSOM: Self-Organizing Map for Kepler and K2 transits

A self-organizing map (SOM) can be used to identify planetary candidates from Kepler and K2 datasets with accuracies near 90% in distinguishing known Kepler planets from false positives. TransitSOM classifies a Kepler or K2 lightcurve using a self-organizing map (SOM) created and pre-trained using PyMVPA (ascl:1703.009). It includes functions for users to create their own SOMs.

[ascl:1703.009] PyMVPA: MultiVariate Pattern Analysis in Python

PyMVPA eases statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. It is designed to integrate well with related software packages, such as scikit-learn, shogun, and MDP.

[ascl:1703.008] exorings: Exoring Transit Properties

Exorings is suitable for surveying entire catalogs of transiting planet candidates for exoring candidates, providing a subset of objects worthy of more detailed light curve analysis. Moreover, it is highly suited for uncovering evidence of a population of ringed planets by comparing the radius anomaly and PR-effects in ensemble studies.

[ascl:1703.007] sidm-nbody: Monte Carlo N-body Simulation for Self-Interacting Dark Matter

Self-Interacting Dark Matter (SIDM) is a hypothetical model for cold dark matter in the Universe. A strong interaction between dark matter particles introduce a different physics inside dark-matter haloes, making the density profile cored, reduce the number of subhaloes, and trigger gravothermal collapse. sidm-nbody is an N-body simulation code with Direct Simulation Monte Carlo scattering for self interaction, and some codes to analyse gravothermal collapse of isolated haloes. The N-body simulation is based on GADGET 1.1.

[ascl:1703.006] SNRPy: Supernova remnant evolution modeling

SNRPy (Super Nova Remnant Python) models supernova remnant (SNR) evolution and is useful for understanding SNR evolution and to model observations of SNR for obtaining good estimates of SNR properties. It includes all phases for the standard path of evolution for spherically symmetric SNRs and includes alternate evolutionary models, including evolution in a cloudy ISM, the fractional energy loss model, and evolution in a hot low-density ISM. The graphical interface takes in various parameters and produces outputs such as shock radius and velocity vs. time, SNR surface brightness profile and spectrum.

[ascl:1703.005] starsense_algorithms: Performance evaluation of various star sensors

The Matlab starsense_algorithms package evaluates the performance of various star sensors through the implementation of centroiding, geometric voting and QUEST algorithms. The physical parameters of a star sensor are parametrized and by changing these parameters, performance estimators such as sky coverage, memory requirement, and timing requirements can be estimated for the selected star sensor.

[ascl:1703.004] PHOTOMETRYPIPELINE: Automated photometry pipeline

PHOTOMETRYPIPELINE (PP) provides calibrated photometry from imaging data obtained with small to medium-sized observatories. PP uses Source Extractor (ascl:1010.064) and SCAMP (ascl:1010.063) to register the image data and perform aperture photometry. Calibration is obtained through matching of field stars with reliable photometric catalogs. PP has been specifically designed for the measurement of asteroid photometry, but can also be used to obtain photometry of fixed sources.

[ascl:1703.003] Corrfunc: Blazing fast correlation functions on the CPU

Corrfunc is a suite of high-performance clustering routines. The code can compute a variety of spatial correlation functions on Cartesian geometry as well Landy-Szalay calculations for spatial and angular correlation functions on a spherical geometry and is useful for, for example, exploring the galaxy-halo connection. The code is written in C and can be used on the command-line, through the supplied python extensions, or the C API.

[ascl:1703.002] COCOA: Simulating Observations of Star Cluster Simulations

COCOA (Cluster simulatiOn Comparison with ObservAtions) creates idealized mock photometric observations using results from numerical simulations of star cluster evolution. COCOA is able to present the output of realistic numerical simulations of star clusters carried out using Monte Carlo or N-body codes in a way that is useful for direct comparison with photometric observations. The code can simulate optical observations from simulation snapshots in which positions and magnitudes of objects are known. The parameters for simulating the observations can be adjusted to mimic telescopes of various sizes. COCOA also has a photometry pipeline that can use standalone versions of DAOPHOT (ascl:1104.011) and ALLSTAR to produce photometric catalogs for all observed stars.

[ascl:1703.001] Larch: X-ray Analysis for Synchrotron Applications using Python

Larch is an open-source library and toolkit written in Python for processing and analyzing X-ray spectroscopic data. The primary emphasis is on X-ray spectroscopic and scattering data collected at modern synchrotron sources. Larch provides a wide selection of general-purpose processing, analysis, and visualization tools for processing X-ray data; its related target application areas include X-ray absorption fine structure (XAFS), micro-X-ray fluorescence (XRF) maps, quantitative X-ray fluorescence, X-ray absorption near edge spectroscopy (XANES), and X-ray standing waves and surface scattering. Larch provides a complete set of XAFS Analysis tools and has support for visualizing and analyzing XRF maps and spectra, and additional tools for X-ray spectral analysis, data handling, and general-purpose data modeling.

[ascl:1702.012] GRIM: General Relativistic Implicit Magnetohydrodynamics

GRIM (General Relativistic Implicit Magnetohydrodynamics) evolves a covariant extended magnetohydrodynamics model derived by treating non-ideal effects as a perturbation of ideal magnetohydrodynamics. Non-ideal effects are modeled through heat conduction along magnetic field lines and a difference between the pressure parallel and perpendicular to the field lines. The model relies on an effective collisionality in the disc from wave-particle scattering and velocity-space (mirror and firehose) instabilities. GRIM, which runs on CPUs as well as on GPUs, combines time evolution and primitive variable inversion needed for conservative schemes into a single step using only the residuals of the governing equations as inputs. This enables the code to be physics agnostic as well as flexible regarding time-stepping schemes.

[ascl:1702.011] Chempy: A flexible chemical evolution model for abundance fitting

Chempy models Galactic chemical evolution (GCE); it is a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of 5-10 parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: e.g. the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF) and the incidence of supernova of type Ia (SN Ia). Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets, performing essentially as a chemical evolution fitting tool. Chempy can be used to confront predictions from stellar nucleosynthesis with complex abundance data sets and to refine the physical processes governing the chemical evolution of stellar systems.

ChempyMulti (ascl:1909.006) is available as an update to the ChempyScoring package.

[ascl:1702.010] streamgap-pepper: Effects of peppering streams with many small impacts

streamgap-pepper computes the effect of subhalo fly-bys on cold tidal streams based on the action-angle representation of streams. A line-of-parallel-angle approach is used to calculate the perturbed distribution function of a given stream segment by undoing the effect of all impacts. This approach allows one to compute the perturbed stream density and track in any coordinate system in minutes for realizations of the subhalo distribution down to 10^5 Msun, accounting for the stream's internal dispersion and overlapping impacts. This code uses galpy (ascl:1411.008) and the streampepperdf.py galpy extension, which implements the fast calculation of the perturbed stream structure.

[ascl:1702.009] stream-stream: Stellar and dark-matter streams interactions

Stream-stream analyzes the interaction between a stellar stream and a disrupting dark-matter halo. It requires galpy (ascl:1411.008), NEMO (ascl:1010.051), and the usual common scientific Python packages.

[ascl:1702.008] HOURS: Simulation and analysis software for the KM3NeT

The Hellenic Open University Reconstruction & Simulation (HOURS) software package contains a realistic simulation package of the detector response of very large (km3-scale) underwater neutrino telescopes, including an accurate description of all the relevant physical processes, the production of signal and background as well as several analysis strategies for triggering and pattern recognition, event reconstruction, tracking and energy estimation. HOURS also provides tools for simulating calibration techniques and other studies for estimating the detector sensitivity to several neutrino sources.

[ascl:1702.007] KEPLER: General purpose 1D multizone hydrodynamics code

KEPLER is a general purpose stellar evolution/explosion code that incorporates implicit hydrodynamics and a detailed treatment of nuclear burning processes. It has been used to study the complete evolution of massive and supermassive stars, all major classes of supernovae, hydrostatic and explosive nucleosynthesis, and x- and gamma-ray bursts on neutron stars and white dwarfs.

[ascl:1702.006] GalaxyGAN: Generative Adversarial Networks for recovery of galaxy features

GalaxyGAN uses Generative Adversarial Networks to reliably recover features in images of galaxies. The package uses machine learning to train on higher quality data and learns to recover detailed features such as galaxy morphology by effectively building priors. This method opens up the possibility of recovering more information from existing and future imaging data.

[ascl:1702.005] JetCurry: Modeling 3D geometry of AGN jets from 2D images

Written in Python, JetCurry models the 3D geometry of jets from 2-D images. JetCurry requires NumPy and SciPy and incorporates emcee (ascl:1303.002) and AstroPy (ascl:1304.002), and optionally uses VPython. From a defined initial part of the jet that serves as a reference point, JetCurry finds the position of highest flux within a bin of data in the image matrix and fits along the x axis for the general location of the bends in the jet. A spline fitting is used to smooth out the resulted jet stream.

[ascl:1702.004] Validation: Codes to compare simulation data to various observations

Validation provides codes to compare several observations to simulated data with stellar mass and star formation rate, simulated data stellar mass function with observed stellar mass function from PRIMUS or SDSS-GALEX in several redshift bins from 0.01-1.0, and simulated data B band luminosity function with observed stellar mass function, and to create plots for various attributes, including stellar mass functions, and stellar mass to halo mass. These codes can model predictions (in some cases alongside observational data) to test other mock catalogs.

[ascl:1702.003] juwvid: Julia code for time-frequency analysis

Juwvid performs time-frequency analysis. Written in Julia, it uses a modified version of the Wigner distribution, the pseudo Wigner distribution, and the short-time Fourier transform from MATLAB GPL programs, tftb-0.2. The modification includes the zero-padding FFT, the non-uniform FFT, the adaptive algorithm by Stankovic, Dakovic, Thayaparan 2013, the S-method, the L-Wigner distribution, and the polynomial Wigner-Ville distribution.

[ascl:1702.002] corner.py: Corner plots

corner.py uses matplotlib to visualize multidimensional samples using a scatterplot matrix. In these visualizations, each one- and two-dimensional projection of the sample is plotted to reveal covariances. corner.py was originally conceived to display the results of Markov Chain Monte Carlo simulations and the defaults are chosen with this application in mind but it can be used for displaying many qualitatively different samples. An earlier version of corner.py was known as triangle.py.

[ascl:1702.001] ORBE: Orbital integrator for educational purposes

ORBE performs numerical integration of an arbitrary planetary system composed by a central star and up to 100 planets and minor bodies. ORBE calculates the orbital evolution of a system of bodies by means of the computation of the time evolution of their orbital elements. It is easy to use and is suitable for educational use by undergraduate students in the classroom as a first approach to orbital integrators.

[ascl:1701.012] SONG: Second Order Non-Gaussianity

SONG computes the non-linear evolution of the Universe in order to predict cosmological observables such as the bispectrum of the Cosmic Microwave Background (CMB). More precisely, it is a second-order Boltzmann code, as it solves the Einstein and Boltzmann equations up to second order in the cosmological perturbations.

[ascl:1701.011] GWFrames: Manipulate gravitational waveforms

GWFrames eliminates all rotational behavior, thus simplifying the waveform as much as possible and allowing direct generalizations of methods for analyzing nonprecessing systems. In the process, the angular velocity of a waveform is introduced, which also has important uses, such as supplying a partial solution to an important inverse problem.

[ascl:1701.010] kcorrect: Calculate K-corrections between observed and desired bandpasses

kcorrect fits very restricted spectral energy distribution models to galaxy photometry or spectra in the restframe UV, optical and near-infrared. The main purpose of the fits are for calculating K-corrections. The templates used for the fits may also be interpreted physically, since they are based on the Bruzual-Charlot stellar evolution synthesis codes. Thus, for each fit galaxy kcorrect can provide an estimate of the stellar mass-to-light ratio.

[ascl:1701.009] ChromaStarServer (formerly GrayStarServer): Stellar atmospheric modeling and spectrum synthesis

ChromaStarServer (formerly GrayStarServer) is a stellar atmospheric modeling and spectrum synthesis code of pedagogical accuracy that is accessible in any web browser on commonplace computational devices and that runs on a timescale of a few seconds.

[ascl:1701.008] ChromaStar (formerly GrayStar): Web-based pedagogical stellar modeling

ChromaStar (formerly GrayStar) is a web-based pedagogical stellar model. It approximates stellar atmospheric and spectral line modeling in JavaScript with visualization in HTML. It is suitable for a wide range of education and public outreach levels depending on which optional plots and print-outs are turned on. All plots and renderings are pure basic HTML and the plotting module contains original HTML procedures for automatically scaling and graduating x- and y-axes.

[ascl:1701.007] Forecaster: Mass and radii of planets predictor

Forecaster predicts the mass (or radius) from the radius (or mass) for objects covering nine orders-of-magnitude in mass. It is an unbiased forecasting model built upon a probabilistic mass-radius relation conditioned on a sample of 316 well-constrained objects. It accounts for observational errors, hyper-parameter uncertainties and the intrinsic dispersions observed in the calibration sample.

[ascl:1701.006] MSWAVEF: Momentum-Space Wavefunctions

MSWAVEF calculates hydrogenic and non-hydrogenic momentum-space electronic wavefunctions. Such wavefunctions are often required to calculate various collision processes, such as excitation and line broadening cross sections. The hydrogenic functions are calculated using the standard analytical expressions. The non-hydrogenic functions are calculated within quantum defect theory according to the method of Hoang Binh and van Regemorter (1997). Required Hankel transforms have been determined analytically for angular momentum quantum numbers ranging from zero to 13 using Mathematica. Calculations for higher angular momentum quantum numbers are possible, but slow (since calculated numerically). The code is written in IDL.

[ascl:1701.005] KAULAKYS: Inelastic collisions between hydrogen atoms and Rydberg atoms

KAULAKYS calculates cross sections and rate coefficients for inelastic collisions between Rydberg atoms and hydrogen atoms according to the free electron model of Kaulakys (1986, 1991). It is written in IDL and requires the code MSWAVEF (ascl:1701.006) to calculate momentum-space wavefunctions. KAULAKYS can be easily adapted to collisions with perturbers other than hydrogen atoms by providing the appropriate scattering amplitudes.

[ascl:1701.004] CosmoSlik: Cosmology sampler of likelihoods

CosmoSlik quickly puts together, runs, and analyzes an MCMC chain for analysis of cosmological data. It is highly modular and comes with plugins for CAMB (ascl:1102.026), CLASS (ascl:1106.020), the Planck likelihood, the South Pole Telescope likelihood, other cosmological likelihoods, emcee (ascl:1303.002), and more. It offers ease-of-use, flexibility, and modularity.

[ascl:1701.003] Spectra: Time series power spectrum calculator

Spectra calculates the power spectrum of a time series equally spaced or not based on the Spectral Correlation Coefficient (Ferraz-Mello 1981, Astron. Journal 86 (4), 619). It is very efficient for detection of low frequencies.

[ascl:1701.002] Vizic: Jupyter-based interactive visualization tool for astronomical catalogs

Vizic is a Python visualization library that builds the connection between images and catalogs through an interactive map of the sky region. The software visualizes catalog data over a custom background canvas using the shape, size and orientation of each object in the catalog and displays interactive and customizable objects in the map. Property values such as redshift and magnitude can be used to filter or apply colormaps, and objects can be selected for further analysis through standard Python functions from inside a Jupyter notebook.

Vizic allows custom overlays to be appended dynamically on top of the sky map; included are Voronoi, Delaunay, Minimum Spanning Tree and HEALPix layers, which are helpful for visualizing large-scale structure. Overlays can be generated, added or removed dynamically with one line of code. Catalog data is kept in a non-relational database. The Jupyter Notebook allows the user to create scripts to analyze and plot the data selected/displayed in the interactive map, making Vizic a powerful and flexible interactive analysis tool. Vizic be used for data inspection, clustering analysis, galaxy alignment studies, outlier identification or simply large-scale visualizations.

[ascl:1701.001] The Joker: A custom Monte Carlo sampler for binary-star and exoplanet radial velocity data

Given sparse or low-quality radial-velocity measurements of a star, there are often many qualitatively different stellar or exoplanet companion orbit models that are consistent with the data. The consequent multimodality of the likelihood function leads to extremely challenging search, optimization, and MCMC posterior sampling over the orbital parameters. The Joker is a custom-built Monte Carlo sampler that can produce a posterior sampling for orbital parameters given sparse or noisy radial-velocity measurements, even when the likelihood function is poorly behaved. The method produces correct samplings in orbital parameters for data that include as few as three epochs. The Joker can therefore be used to produce proper samplings of multimodal pdfs, which are still highly informative and can be used in hierarchical (population) modeling.

[ascl:1612.022] REPS: REscaled Power Spectra for initial conditions with massive neutrinos

REPS (REscaled Power Spectra) provides accurate, one-percent level, numerical simulations of the initial conditions for massive neutrino cosmologies, rescaling the late-time linear power spectra to the simulation initial redshift.

[ascl:1612.021] BaTMAn: Bayesian Technique for Multi-image Analysis

Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.

[ascl:1612.020] Grackle: Chemistry and radiative cooling library for astrophysical simulations

The chemistry and radiative cooling library Grackle provides options for primordial chemistry and cooling, photo-heating and photo-ionization from UV backgrounds, and support for user-provided arrays of volumetric and specific heating rates for astrophysical simulations and models. The library provides functions to update chemistry species; solve radiative cooling and update internal energy; and calculate cooling time, temperature, pressure, and ratio of specific heats (gamma), and has interfaces for C, C++, Fortran, and Python codes.

[ascl:1612.019] Trident: Synthetic spectrum generator

Trident creates synthetic absorption-line spectra from astrophysical hydrodynamics simulations. It uses the yt package (ascl:1011.022) to read in simulation datasets and extends it to provide realistic synthetic observations appropriate for studies of the interstellar, circumgalactic, and intergalactic media.

[ascl:1612.018] pylightcurve: Exoplanet lightcurve model

pylightcurve is a model for light-curves of transiting planets. It uses the four coefficients law for the stellar limb darkening and returns the relative flux, F(t), as a function of the limb darkening coefficients, an, the Rp/R* ratio and all the orbital parameters based on the nonlinear limb darkening model (Claret 2000).

[ascl:1612.017] GAMER: GPU-accelerated Adaptive MEsh Refinement code

GAMER (GPU-accelerated Adaptive MEsh Refinement) serves as a general-purpose adaptive mesh refinement + GPU framework and solves hydrodynamics with self-gravity. The code supports adaptive mesh refinement (AMR), hydrodynamics with self-gravity, and a variety of GPU-accelerated hydrodynamic and Poisson solvers. It also supports hybrid OpenMP/MPI/GPU parallelization, concurrent CPU/GPU execution for performance optimization, and Hilbert space-filling curve for load balance. Although the code is designed for simulating galaxy formation, it can be easily modified to solve a variety of applications with different governing equations. All optimization strategies implemented in the code can be inherited straightforwardly.

[ascl:1612.016] CELib: Software library for simulations of chemical evolution

CELib (Chemical Evolution Library) simulates chemical evolution of galaxy formation under the simple stellar population (SSP) approximation and can be used by any simulation code that uses the SSP approximation, such as particle-base and mesh codes as well as semi-analytical models. Initial mass functions, stellar lifetimes, yields from type II and Ia supernovae, asymptotic giant branch stars, and neutron star mergers components are included and a variety of models are available for use. The library allows comparisons of the impact of individual models on the chemical evolution of galaxies by changing control flags and parameters of the library.

[ascl:1612.015] Superplot: Graphical interface for plotting and analyzing data

Superplot calculates and plots statistical quantities relevant to parameter inference from a "chain" of samples drawn from a parameter space produced by codes such as MultiNest (ascl:1109.006), BAYES-X (ascl:1505.027), and PolyChord (ascl:1502.011). It offers a graphical interface for browsing a chain of many variables quickly and can produce numerous kinds of publication quality plots, including one- and two-dimensional profile likelihood, three-dimensional scatter plots, and confidence intervals and credible regions. Superplot can also save plots in PDF format, create a summary text file, and export a plot as a pickled object for importing and manipulating in a Python interpreter.

[ascl:1612.014] AUTOSTRUCTURE: General program for calculation of atomic and ionic properties

AUTOSTRUCTURE calculates atomic and ionic energy levels, radiative rates, autoionization rates, photoionization cross sections, plane-wave Born and distorted-wave excitation cross sections in LS- and intermediate-coupling using non- or (kappa-averaged) relativistic wavefunctions. These can then be further processed to form Auger yields, fluorescence yields, partial and total dielectronic and radiative recombination cross sections and rate coefficients, photoabsorption cross sections, and monochromatic opacities, among other properties.

[ascl:1612.013] InversionKit: Linear inversions from frequency data

InversionKit is an interactive Java program that performs rotational and structural linear inversions from frequency data.

[ascl:1612.012] Meso-NH: Non-hydrostatic mesoscale atmospheric model

Meso-NH is the non-hydrostatic mesoscale atmospheric model of the French research community jointly developed by the Laboratoire d'Aérologie (UMR 5560 UPS/CNRS) and by CNRM (UMR 3589 CNRS/Météo-France). Meso-NH incorporates a non-hydrostatic system of equations for dealing with scales ranging from large (synoptic) to small (large eddy) scales while calculating budgets and has a complete set of physical parameterizations for the representation of clouds and precipitation. It is coupled to the surface model SURFEX for representation of surface atmosphere interactions by considering different surface types (vegetation, city​​, ocean, lake) and allows a multi-scale approach through a grid-nesting technique. Meso-NH is versatile, vectorized, parallelized, and operates in 1D, 2D or 3D; it is coupled with a chemistry module (including gas-phase, aerosol, and aqua-phase components) and a lightning module, and has observation operators that compare model output directly with satellite observations, radar, lidar and GPS.

[ascl:1612.011] QSFit: Quasar Spectral FITting

QSFit performs automatic analysis of Active Galactic Nuclei (AGN) optical spectra. It provides estimates of: AGN continuum luminosities and slopes at several restframe wavelengths; luminosities, widths and velocity offsets of 20 emission lines; luminosities of iron blended lines at optical and UV wavelengths; host galaxy luminosities. The whole fitting process is customizable for specific needs, and can be extended to analyze spectra from other data sources. The ultimate purpose of QSFit is to allow astronomers to run standardized recipes to analyze the AGN data, in a simple, replicable and shareable way.

[ascl:1612.010] Earthshine simulator: Idealized images of the Moon

Terrestrial albedo can be determined from observations of the relative intensity of earthshine. Images of the Moon at different lunar phases can be analyzed to derive the semi-hemispheric mean albedo of the Earth, and an important tool for doing this is simulations of the appearance of the Moon for any time. This software produces idealized images of the Moon for arbitrary times. It takes into account the libration of the Moon and the distances between Sun, Moon and the Earth, as well as the relevant geometry. The images of the Moon are produced as FITS files. User input includes setting the Julian Day of the simulation. Defaults for image size and field of view are set to produce approximately 1x1 degree images with the Moon in the middle from an observatory on Earth, currently set to Mauna Loa.

[ascl:1612.009] CRETE: Comet RadiativE Transfer and Excitation

CRETE (Comet RadiativE Transfer and Excitation) is a one-dimensional water excitation and radiation transfer code for sub-millimeter wavelengths based on the RATRAN code (ascl:0008.002). The code considers rotational transitions of water molecules given a Haser spherically symmetric distribution for the cometary coma and produces FITS image cubes that can be analyzed with tools like MIRIAD (ascl:1106.007). In addition to collisional processes to excite water molecules, the effect of infrared radiation from the Sun is approximated by effective pumping rates for the rotational levels in the ground vibrational state.

[ascl:1612.008] PyORBIT: Exoplanet orbital parameters and stellar activity

PyORBIT handles several kinds of datasets, such as radial velocity (RV), activity indexes, and photometry, to simultaneously characterize the orbital parameters of exoplanets and the noise induced by the activity of the host star. RV computation is performed using either non-interacting Kepler orbits or n-body integration. Stellar activity can be modeled either with sinusoids at the rotational period and its harmonics or Gaussian process. In addition, the code can model offsets and systematics in measurements from several instruments. The PyORBIT code is modular; new methods for stellar activity modeling or parameter estimation can easily be incorporated into the code.

[ascl:1612.007] dacapo_calibration: Photometric calibration code

dacapo_calibration implements the DaCapo algorithm used in the Planck/LFI 2015 data release for photometric calibration. The code takes as input a set of TODs and calibrates them using the CMB dipole signal. DaCapo is a variant of the well-known family of destriping algorithms for map-making.

[ascl:1612.006] flexCE: Flexible one-zone chemical evolution code

flexCE (flexible Chemical Evolution) computes the evolution of a one-zone chemical evolution model with inflow and outflow in which gas is instantaneously and completely mixed. It can be used to demonstrate the sensitivity of chemical evolution models to parameter variations, show the effect of CCSN yields on chemical evolution models, and reproduce the 2D distribution in [O/Fe]{[Fe/H] by mixing models with a range of inflow and outflow histories. It can also post-process cosmological simulations to predict element distributions.

[ascl:1612.005] PyProfit: Wrapper for libprofit

pyprofit is a python wrapper for libprofit (ascl:1612.003).

[ascl:1612.004] ProFit: Bayesian galaxy fitting tool

ProFit is a Bayesian galaxy fitting tool that uses the fast C++ image generation library libprofit (ascl:1612.003) and a flexible R interface to a large number of likelihood samplers. It offers a fully featured Bayesian interface to galaxy model fitting (also called profiling), using mostly the same standard inputs as other popular codes (e.g. GALFIT ascl:1104.010), but it is also able to use complex priors and a number of likelihoods.

[ascl:1612.003] libprofit: Image creation from luminosity profiles

libprofit is a C++ library for image creation based on different luminosity profiles. It offers fast and accurate two-dimensional integration for a useful number of profiles, including Sersic, Core-Sersic, broken-exponential, Ferrer, Moffat, empirical King, point-source and sky, with a simple mechanism for adding new profiles. libprofit provides a utility to read the model and profile parameters from the command-line and generate the corresponding image. It can output the resulting image as text values, a binary stream, or as a simple FITS file. It also provides a shared library exposing an API that can be used by any third-party application. R and Python interfaces are available: ProFit (ascl:1612.004) and PyProfit (ascl:1612.005).

[ascl:1612.002] LSDCat: Line Source Detection and Cataloguing Tool

LSDCat is a conceptually simple but robust and efficient detection package for emission lines in wide-field integral-field spectroscopic datacubes. The detection utilizes a 3D matched-filtering approach for compact single emission line objects. Furthermore, the software measures fluxes and extents of detected lines. LSDCat is implemented in Python, with a focus on fast processing of large data-volumes.

[ascl:1612.001] Python-CPL: Python interface for the ESO Common Pipeline Library

Python-CPL is a framework to configure and execute pipeline recipes written with the Common Pipeline Library (CPL) (ascl:1402.010) with Python2 or Python3. The input, calibration and output data can be specified as FITS files or as astropy.io.fits objects in memory. The package is used to implement the MUSE pipeline in the AstroWISE data management system.

[ascl:1611.021] SlicerAstro: Astronomy (HI) extension for 3D Slicer

SlicerAstro extends 3D Slicer, a multi-platform package for visualization and medical image processing, to provide a 3-D interactive viewer with 3-D human-machine interaction features, based on traditional 2-D input/output hardware, and analysis capabilities.

[ascl:1611.020] CMCIRSED: Far-infrared spectral energy distribution fitting for galaxies near and far

The Caitlin M. Casey Infra Red Spectral Energy Distribution model (CMCIRSED) provides a simple SED fitting technique suitable for a wide range of IR data, from sources which have only three IR photometric points to sources with >10 photometric points. These SED fits produce accurate estimates to a source's integrated IR luminosity, dust temperature and dust mass. CMCIRSED is based on a single dust temperature greybody fit linked to a MIR power law, fitted simultaneously to data across ∼5–2000 μm.

[ascl:1611.019] phase_space_cosmo_fisher: Fisher matrix 2D contours

phase_space_cosmo_fisher produces Fisher matrix 2D contours from which the constraints on cosmological parameters can be derived. Given a specified redshift array and cosmological case, 2D marginalized contours of cosmological parameters are generated; the code can also plot the derivatives used in the Fisher matrix. In addition, this package can generate 3D plots of qH^2 and other cosmological quantities as a function of redshift and cosmology.

[ascl:1611.018] Icarus: Stellar binary light curve synthesis tool

Icarus is a stellar binary light curve synthesis tool that generates a star, given some basic binary parameters, by solving the gravitational potential equation, creating a discretized stellar grid, and populating the stellar grid with physical parameters, including temperature and surface gravity. Icarus also evaluates the outcoming flux from the star given an observer's point of view (i.e., orbital phase and orbital orientation).

[ascl:1611.017] SNCosmo: Python library for supernova cosmology

SNCosmo synthesizes supernova spectra and photometry from SN models, and has functions for fitting and sampling SN model parameters given photometric light curve data. It offers fast implementations of several commonly used extinction laws and can be used to construct SN models that include dust. The SNCosmo library includes supernova models such as SALT2, MLCS2k2, Hsiao, Nugent, PSNID, SNANA and Whalen models, as well as a variety of built-in bandpasses and magnitude systems, and provides convenience functions for reading and writing peculiar data formats used in other packages. The library is extensible, allowing new models, bandpasses, and magnitude systems to be defined using an object-oriented interface.

[ascl:1611.016] Carpet: Adaptive Mesh Refinement for the Cactus Framework

Carpet is an adaptive mesh refinement and multi-patch driver for the Cactus Framework (ascl:1102.013). Cactus is a software framework for solving time-dependent partial differential equations on block-structured grids, and Carpet acts as driver layer providing adaptive mesh refinement, multi-patch capability, as well as parallelization and efficient I/O.

[ascl:1611.015] Pippi: Parse and plot MCMC chains

Pippi (parse it, plot it) operates on MCMC chains and related lists of samples from a function or distribution, and can merge, parse, and plot sample ensembles ('chains') either in terms of the likelihood/fitness function directly, or as implied posterior probability densities. Pippi is compatible with ASCII text and hdf5 chains, operates out of core, and can post-process chains on the fly.

[ascl:1611.014] AIMS: Asteroseismic Inference on a Massive Scale

AIMS (Asteroseismic Inference on a Massive Scale) estimates stellar parameters and credible intervals/error bars in a Bayesian manner from a set of seismic frequency data and so-called classic constraints. To achieve reliable parameter estimates and computational efficiency it searches through a grid of pre-computed models using an MCMC algorithm; interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modeling consists of individual frequencies from peak-bagging, which can be complemented with classic spectroscopic constraints.

[ascl:1611.013] pyGMMis: Mixtures-of-Gaussians density estimation method

pyGMMis is a mixtures-of-Gaussians density estimation method that accounts for arbitrary incompleteness in the process that creates the samples as long as the incompleteness is known over the entire feature space and does not depend on the sample density (missing at random). pyGMMis uses the Expectation-Maximization procedure and generates its best guess of the unobserved samples on the fly. It can also incorporate an uniform "background" distribution as well as independent multivariate normal measurement errors for each of the observed samples, and then recovers an estimate of the error-free distribution from which both observed and unobserved samples are drawn. The code automatically segments the data into localized neighborhoods, and is capable of performing density estimation with millions of samples and thousands of model components on machines with sufficient memory.

[ascl:1611.012] EarthShadow: Calculator for dark matter particle velocity distribution after Earth-scattering

EarthShadow calculates the impact of Earth-scattering on the distribution of Dark Matter (DM) particles. The code calculates the speed and velocity distributions of DM at various positions on the Earth and also helps with the calculation of the average scattering probabilities. Tabulated data for DM-nuclear scattering cross sections and various numerical results, plots and animations are also included in the code package.

[ascl:1611.011] OXAF: Ionizing spectra of Seyfert galaxies for photoionization modeling

OXAF provides a simplified model of Seyfert Active Galactic Nucleus (AGN) continuum emission designed for photoionization modeling. It removes degeneracies in the effects of AGN parameters on model spectral shapes and reproduces the diversity of spectral shapes that arise in physically-based models. OXAF accepts three parameters which directly describe the shape of the output ionizing spectrum: the energy of the peak of the accretion disk emission Epeak, the photon power-law index of the non-thermal X-ray emission Γ, and the proportion of the total flux which is emitted in the non-thermal component pNT. OXAF accounts for opacity effects where the accretion disk is ionized because it inherits the ‘color correction’ of OPTXAGNF, the physical model upon which OXAF is based.

[ascl:1611.010] Kapteyn Package: Tools for developing astronomical applications

The Kapteyn Package provides tools for the development of astronomical applications with Python. It handles spatial and spectral coordinates, WCS projections and transformations between different sky systems; spectral translations (e.g., between frequencies and velocities) and mixed coordinates are also supported. Kapteyn offers versatile tools for writing small and dedicated applications for the inspection of FITS headers, the extraction and display of (FITS) data, interactive inspection of this data (color editing) and for the creation of plots with world coordinate information. It includes utilities for use with matplotlib such as obtaining coordinate information from plots, interactively modifiable colormaps and timer events (module mplutil); tools for parsing and interpreting coordinate information entered by the user (module positions); a function to search for gaussian components in a profile (module profiles); and a class for non-linear least squares fitting (module kmpfit).

[ascl:1611.009] RHOCUBE: 3D density distributions modeling code

RHOCUBE models 3D density distributions on a discrete Cartesian grid and their integrated 2D maps. It can be used for a range of applications, including modeling the electron number density in LBV shells and computing the emission measure. The RHOCUBE Python package provides several 3D density distributions, including a powerlaw shell, truncated Gaussian shell, constant-density torus, dual cones, and spiralling helical tubes, and can accept additional distributions. RHOCUBE provides convenient methods for shifts and rotations in 3D, and if necessary, an arbitrary number of density distributions can be combined into the same model cube and the integration ∫ dz performed through the joint density field.

[ascl:1611.008] Transit Clairvoyance: Predicting multiple-planet systems for TESS

Transit Clairvoyance uses Artificial Neural Networks (ANNs) to predict the most likely short period transiters to have additional transiters, which may double the discovery yield of the TESS (Transiting Exoplanet Survey Satellite). Clairvoyance is a simple 2-D interpolant that takes in the number of planets in a system with period less than 13.7 days, as well as the maximum radius amongst them (in Earth radii) and orbital period of the planet with maximum radius (in Earth days) in order to predict the probability of additional transiters in this system with period greater than 13.7 days.

[ascl:1611.007] GRASP2K: Relativistic Atomic Structure Package

GRASP2K is a revised and greatly expanded version of GRASP (ascl:1609.008) and is adapted for 64-bit computer architecture. It includes new angular libraries, can transform from jj- to LSJ-coupling, and coefficients of fractional parentage have been extended to j=9/2, making calculations feasible for the lanthanides and actinides. GRASP2K identifies each atomic state by the total energy and a label for the configuration state function with the largest expansion coefficient in LSJLSJ intermediate coupling.

[ascl:1611.006] GalPot: Galaxy potential code

GalPot finds the gravitational potential associated with axisymmetric density profiles. The package includes code that performs transformations between commonly used coordinate systems for both positions and velocities (the class OmniCoords), and that integrates orbits in the potentials. GalPot is a stand-alone version of Walter Dehnen's GalaxyPotential C++ code taken from the falcON code in the NEMO Stellar Dynamics Toolbox (ascl:1010.051).

[ascl:1611.005] Exo-Transmit: Radiative transfer code for calculating exoplanet transmission spectra

Exo-Transmit calculates the transmission spectrum of an exoplanet atmosphere given specified input information about the planetary and stellar radii, the planet's surface gravity, the atmospheric temperature-pressure (T-P) profile, the location (in terms of pressure) of any cloud layers, the composition of the atmosphere, and opacity data for the atoms and molecules that make up the atmosphere. The code solves the equation of radiative transfer for absorption of starlight passing through the planet's atmosphere as it transits, accounting for the oblique path of light through the planetary atmosphere along an Earth-bound observer's line of sight. The fraction of light absorbed (or blocked) by the planet plus its atmosphere is calculated as a function of wavelength to produce the wavelength-dependent transmission spectrum. Functionality is provided to simulate the presence of atmospheric aerosols in two ways: an optically thick (gray) cloud deck can be generated at a user-specified height in the atmosphere, and the nominal Rayleigh scattering can be increased by a specified factor.

[ascl:1611.004] PRECESSION: Python toolbox for dynamics of spinning black-hole binaries

PRECESSION is a comprehensive toolbox for exploring the dynamics of precessing black-hole binaries in the post-Newtonian regime. It allows study of the evolution of the black-hole spins along their precession cycles, performs gravitational-wave-driven binary inspirals using both orbit-averaged and precession-averaged integrations, and predicts the properties of the merger remnant through fitting formulas obtained from numerical-relativity simulations. PRECESSION can add the black-hole spin dynamics to larger-scale numerical studies such as gravitational-wave parameter estimation codes, population synthesis models to predict gravitational-wave event rates, galaxy merger trees and cosmological simulations of structure formation, and provides fast and reliable integration methods to propagate statistical samples of black-hole binaries from/to large separations where they form to/from small separations where they become detectable, thus linking gravitational-wave observations of spinning black-hole binaries to their astrophysical formation history. The code is also useful for computing initial parameters for numerical-relativity simulations targeting specific precessing systems.

[ascl:1611.003] MPDAF: MUSE Python Data Analysis Framework

MPDAF, the MUSE Python Data Analysis Framework, provides tools to work with MUSE-specific data (for example, raw data and pixel tables), and with more general data such as spectra, images, and data cubes. Originally written to work with MUSE data, it can also be used for other data, such as that from the Hubble Space Telescope. MPDAF also provides MUSELET, a SExtractor-based tool to detect emission lines in a data cube, and a format to gather all the information on a source in one FITS file. MPDAF was developed and is maintained by CRAL (Centre de Recherche Astrophysique de Lyon).

[ascl:1611.002] tf_unet: Generic convolutional neural network U-Net implementation in Tensorflow

tf_unet mitigates radio frequency interference (RFI) signals in radio data using a special type of Convolutional Neural Network, the U-Net, that enables the classification of clean signal and RFI signatures in 2D time-ordered data acquired from a radio telescope. The code is not tied to a specific segmentation and can be used, for example, to detect radio frequency interference (RFI) in radio astronomy or galaxies and stars in widefield imaging data. This U-Net implementation can outperform classical RFI mitigation algorithms.

[ascl:1611.001] UltraNest: Pythonic Nested Sampling Development Framework and UltraNest

This three-component package provides a Pythonic implementation of the Nested Sampling integration algorithm for Bayesian model comparison and parameter estimation. It offers multiple implementations for constrained drawing functions and a test suite to evaluate the correctness, accuracy and efficiency of various implementations. The three components are:

- a modular framework for nested sampling algorithms (nested_sampling) and their development;
- a test framework to evaluate the performance and accuracy of algorithms (testsuite); and
- UltraNest, a fast C implementation of a mixed RadFriends/MCMC nested sampling algorithm.

[ascl:1610.016] PyMC3: Python probabilistic programming framework

PyMC3 performs Bayesian statistical modeling and model fitting focused on advanced Markov chain Monte Carlo and variational fitting algorithms. It offers powerful sampling algorithms, such as the No U-Turn Sampler, allowing complex models with thousands of parameters with little specialized knowledge of fitting algorithms, intuitive model specification syntax, and optimization for finding the maximum a posteriori (MAP) point. PyMC3 uses Theano to compute gradients via automatic differentiation as well as compile probabilistic programs on-the-fly to C for increased speed.

[ascl:1610.015] NuPyCEE: NuGrid Python Chemical Evolution Environment

The NuGrid Python Chemical Evolution Environment (NuPyCEE) simulates the chemical enrichment and stellar feedback of stellar populations. It contains three modules. The Stellar Yields for Galactic Modeling Applications module (SYGMA) models the enrichment and feedback of simple stellar populations which can be included in hydrodynamic simulations and semi-analytic models of galaxies. It is the basic building block of the One-zone Model for the Evolution of GAlaxies (OMEGA, ascl:1806.018) module which models the chemical evolution of galaxies such as the Milky Way and its dwarf satellites. The STELLAB (STELLar ABundances) module provides a library of observed stellar abundances useful for comparing predictions of SYGMA and OMEGA.

[ascl:1610.014] Freddi: Fast Rise Exponential Decay accretion Disk model Implementation

Freddi (Fast Rise Exponential Decay: accretion Disk model Implementation) solves 1-D evolution equations of the Shakura-Sunyaev accretion disk. It simulates fast rise exponential decay (FRED) light curves of low mass X-ray binaries (LMXBs). The basic equation of the viscous evolution relates the surface density and viscous stresses and is of diffusion type; evolution of the accretion rate can be found on solving the equation. The distribution of viscous stresses defines the emission from the source. The standard model for the accretion disk is implied; the inner boundary of the disk is at the ISCO or can be explicitely set. The boundary conditions in the disk are the zero stress at the inner boundary and the zero accretion rate at the outer boundary. The conditions are suitable during the outbursts in X-ray binary transients with black holes. In a binary system, the accretion disk is radially confined. In Freddi, the outer radius of the disk can be set explicitely or calculated as the position of the tidal truncation radius.

[ascl:1610.013] MC3: Multi-core Markov-chain Monte Carlo code

MC3 (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC3 can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

[ascl:1610.012] Fourierdimredn: Fourier dimensionality reduction model for interferometric imaging

Fourierdimredn (Fourier dimensionality reduction) implements Fourier-based dimensionality reduction of interferometric data. Written in Matlab, it derives the theoretically optimal dimensionality reduction operator from a singular value decomposition perspective of the measurement operator. Fourierdimredn ensures a fast implementation of the full measurement operator and also preserves the i.i.d. Gaussian properties of the original measurement noise.

[ascl:1610.011] BXA: Bayesian X-ray Analysis

BXA connects the nested sampling algorithm MultiNest (ascl:1109.006) to the X-ray spectral analysis environments Xspec (ascl:9910.005) and Sherpa (ascl:1107.005) for Bayesian parameter estimation and model comparison. It provides parameter estimation in arbitrary dimensions and plotting of spectral model vs. the data for best fit, posterior samples, or each component. BXA allows for model selection; it computes the evidence for the considered model, ready for use in computing Bayes factors and is not limited to nested models. It also visualizes deviations between model and data with Quantile-Quantile (QQ) plots, which do not require binning and are more comprehensive than residuals.

[ascl:1610.010] BurnMan: Lower mantle mineral physics toolkit

BurnMan determines seismic velocities for the lower mantle. Written in Python, BurnMan calculates the isotropic thermoelastic moduli by solving the equations-of-state for a mixture of minerals defined by the user. The user may select from a list of minerals applicable to the lower mantle included or can define one. BurnMan provides choices in methodology, both for the EoS and for the multiphase averaging scheme and the results can be visually or quantitatively compared to observed seismic models.

[ascl:1610.009] velbin: radial velocity corrected for binary orbital motions

Velbin convolves the radial velocity offsets due to binary orbital motions with a Gaussian to model an observed velocity distribution. This can be used to measure the mean velocity and velocity dispersion from an observed radial velocity distribution, corrected for binary orbital motions. Velbin fits single- or multi-epoch data with any arbitrary binary orbital parameter distribution (as long as it can be sampled properly), however it always assumes that the intrinsic velocity distribution (i.e. corrected for binary orbital motions) is a Gaussian. Velbin samples (and edits) a binary orbital parameter distribution, fits an observed radial velocity distribution, and creates a mock radial velocity distribution that can be used to provide the fitted radial velocities in the single_epoch or multi_epoch methods.

[ascl:1610.008] cluster-in-a-box: Statistical model of sub-millimeter emission from embedded protostellar clusters

Cluster-in-a-box provides a statistical model of sub-millimeter emission from embedded protostellar clusters and consists of three modules grouped in two scripts. The first (cluster_distribution) generates the cluster based on the number of stars, input initial mass function, spatial distribution and age distribution. The second (cluster_emission) takes an input file of observations, determines the mass-intensity correlation and generates outflow emission for all low-mass Class 0 and I sources. The output is stored as a FITS image where the flux density is determined by the desired resolution, pixel scale and cluster distance.

[ascl:1610.007] gatspy: General tools for Astronomical Time Series in Python

Gatspy contains efficient, well-documented implementations of several common routines for Astronomical time series analysis, including the Lomb-Scargle periodogram, the Supersmoother method, and others.

[ascl:1610.006] C3: Command-line Catalogue Crossmatch for modern astronomical surveys

The Command-line Catalogue Cross-matching (C3) software efficiently performs the positional cross-match between massive catalogues from modern astronomical surveys, whose size have rapidly increased in the current data-driven science era. Based on a multi-core parallel processing paradigm, it is executed as a stand-alone command-line process or integrated within any generic data reduction/analysis pipeline. C3 provides its users with flexibility in portability, parameter configuration, catalogue formats, angular resolution, region shapes, coordinate units and cross-matching types.

[ascl:1610.005] GSGS: In-Focus Phase Retrieval Using Non-Redundant Mask Data

GSGS does phase retrieval on images given an estimate of the pupil phase (from a non-redundant mask or other interferometric approach), the pupil geometry, and the in-focus image. The code uses a modified Gerchberg-Saxton algorithm that iterates between pupil plane and image plane to measure the pupil phase.

[ascl:1610.004] MUSE-DRP: MUSE Data Reduction Pipeline

The MUSE pipeline turns the complex raw data of the MUSE integral field spectrograph into a ready-to-use datacube for scientific analysis.

[ascl:1610.003] DSDEPROJ: Direct Spectral Deprojection

Deprojection of X-ray data by methods such as PROJCT, which are model dependent, can produce large and unphysical oscillating temperature profiles. Direct Spectral Deprojection (DSDEPROJ) solves some of the issues inherent to model-dependent deprojection routines. DSDEPROJ is a model-independent approach, assuming only spherical symmetry, which subtracts projected spectra from each successive annulus to produce a set of deprojected spectra.

[ascl:1610.002] CERES: Collection of Extraction Routines for Echelle Spectra

The Collection of Extraction Routines for Echelle Spectra (CERES) constructs automated pipelines for the reduction, extraction, and analysis of echelle spectrograph data. This modular code includes tools for handling the different steps of the processing: CCD reductions, tracing of the echelle orders, optimal and simple extraction, computation of the wave-length solution, estimation of radial velocities, and rough and fast estimation of the atmospheric parameters. The standard output of pipelines constructed with CERES is a FITS cube with the optimally extracted, wavelength calibrated and instrumental drift-corrected spectrum for each of the science images. Additionally, CERES includes routines for the computation of precise radial velocities and bisector spans via the cross-correlation method, and an automated algorithm to obtain an estimate of the atmospheric parameters of the observed star.

[ascl:1610.001] Piccard: Pulsar timing data analysis package

Piccard is a Bayesian-inference pipeline for Pulsar Timing Array (PTA) data and interacts with Tempo2 (ascl:1210.015) through libstempo (ascl:2002.017). The code is used mainly for single-pulsar analysis and gravitational-wave detection purposes of full Pulsar Timing Array datasets. Modeling of the data can include correlated signals per frequency or modeled spectrum, with uniform, dipolar, quadrupolar, or anisotropic correlations; multiple error bars and EFACs per pulsar; and white and red noise. Timing models can be numerically included, either by using the design matrix (linear timing model), or by calling libstempo for the full non-linear timing model. Many types of samplers are included. For common-mode mitigation, the signals can be reconstructed mitigating arbitrary signals simultaneously.

[ascl:1609.025] PYESSENCE: Generalized Coupled Quintessence Linear Perturbation Python Code

PYESSENCE evolves linearly perturbed coupled quintessence models with multiple (cold dark matter) CDM fluid species and multiple DE (dark energy) scalar fields, and can be used to generate quantities such as the growth factor of large scale structure for any coupled quintessence model with an arbitrary number of fields and fluids and arbitrary couplings.

[ascl:1609.024] AdaptiveBin: Adaptive Binning

AdaptiveBin takes one or more images and adaptively bins them. If one image is supplied, then the pixels are binned by fractional error on the intensity. If two or more images are supplied, then the pixels are fractional binned by error on the combined color.

[ascl:1609.023] contbin: Contour binning and accumulative smoothing

Contbin bins X-ray data using contours on an adaptively smoothed map. The generated bins closely follow the surface brightness, and are ideal where the surface brightness distribution is not smooth, or the spectral properties are expected to follow surface brightness. Color maps can be used instead of surface brightness maps.

[ascl:1609.022] PyPHER: Python-based PSF Homogenization kERnels

PyPHER (Python-based PSF Homogenization kERnels) computes an homogenization kernel between two PSFs; the code is well-suited for PSF matching applications in both an astronomical or microscopy context. It can warp (rotation + resampling) the PSF images (if necessary), filter images in Fourier space using a regularized Wiener filter, and produce a homogenization kernel. PyPHER requires the pixel scale information to be present in the FITS files, which can if necessary be added by using the provided ADDPIXSCL method.

[ascl:1609.021] TIDEV: Tidal Evolution package

TIDEV (Tidal Evolution package) calculates the evolution of rotation for tidally interacting bodies using Efroimsky-Makarov-Williams (EMW) formalism. The package integrates tidal evolution equations and computes the rotational and dynamical evolution of a planet under tidal and triaxial torques. TIDEV accounts for the perturbative effects due to the presence of the other planets in the system, especially the secular variations of the eccentricity. Bulk parameters include the mass and radius of the planet (and those of the other planets involved in the integration), the size and mass of the host star, the Maxwell time and Andrade's parameter. TIDEV also calculates the time scale that a planet takes to be tidally locked as well as the periods of rotation reached at the end of the spin-orbit evolution.

[ascl:1609.020] Askaryan Module: Askaryan electric fields predictor

The Askaryan Module is a C++ class that predicts the electric fields that Askaryan-based detectors detect; it is computationally efficient and accurate, performing fully analytic calculations requiring no a priori MC analysis to compute the entire field, for any frequencies, times, or viewing angles chosen by the user.

[ascl:1609.019] SuperBoL: Module for calculating the bolometric luminosities of supernovae

SuperBoL calculates the bolometric lightcurves of Type II supernovae using observed photometry; it includes three different methods for calculating the bolometric luminosity: quasi-bolometric, direct, and bolometric correction. SuperBoL propagates uncertainties in the input data through the calculations made by the code, allowing for error bars to be included in plots of the lightcurve.

[ascl:1609.018] SIP: Systematics-Insensitive Periodograms

SIP (Systematics-Insensitive Periodograms) extends the generative model used to create traditional sine-fitting periodograms for finding the frequency of a sinusoid by including systematic trends based on a set of eigen light curves in the generative model in addition to using a sum of sine and cosine functions over a grid of frequencies, producing periodograms with vastly reduced systematic features. Acoustic oscillations in giant stars and measurement of stellar rotation periods can be recovered from the SIP periodograms without detrending. The code can also be applied to detection other periodic phenomena, including eclipsing binaries and short-period exoplanet candidates.

[ascl:1609.017] spectral-cube: Read and analyze astrophysical spectral data cubes

Spectral-cube provides an easy way to read, manipulate, analyze, and write data cubes with two positional dimensions and one spectral dimension, optionally with Stokes parameters. It is a versatile data container for building custom analysis routines. It provides a uniform interface to spectral cubes, robust to the wide range of conventions of axis order, spatial projections, and spectral units that exist in the wild, and allows easy extraction of cube sub-regions using physical coordinates. It has the ability to create, combine, and apply masks to datasets and is designed to work with datasets too large to load into memory, and provide basic summary statistic methods like moments and array aggregates.

[ascl:1609.016] PKDGRAV3: Parallel gravity code

Pkdgrav3 is an 𝒪(N) gravity calculation method; it uses a binary tree algorithm with fifth order fast multipole expansion of the gravitational potential, using cell-cell interactions. Periodic boundaries conditions require very little data movement and allow a high degree of parallelism; the code includes GPU acceleration for all force calculations, leading to a significant speed-up with respect to previous versions (ascl:1305.005). Pkdgrav3 also has a sophisticated time-stepping criterion based on an estimation of the local dynamical time.

[ascl:1609.015] FIT3D: Fitting optical spectra

FIT3D fits optical spectra to deblend the underlying stellar population and the ionized gas, and extract physical information from each component. FIT3D is focused on the analysis of Integral Field Spectroscopy data, but is not restricted to it, and is the basis of Pipe3D, a pipeline used in the analysis of datasets like CALIFA, MaNGA, and SAMI. It can run iteratively or in an automatic way to derive the parameters of a large set of spectra.

[ascl:1609.014] Sky3D: Time-dependent Hartree-Fock equation solver

Written in Fortran 90, Sky3D solves the static or dynamic equations on a three-dimensional Cartesian mesh with isolated or periodic boundary conditions and no further symmetry assumptions. Pairing can be included in the BCS approximation for the static case. The code can be easily modified to include additional physics or special analysis of the results and requires LAPACK and FFTW3.

[ascl:1609.013] 21cmSense: Calculating the sensitivity of 21cm experiments to the EoR power spectrum

21cmSense calculates the expected sensitivities of 21cm experiments to the Epoch of Reionization power spectrum. Written in Python, it requires NumPy, SciPy, and AIPY (ascl:1609.012).

[ascl:1609.012] AIPY: Astronomical Interferometry in PYthon

AIPY collects together tools for radio astronomical interferometry. In addition to pure-python phasing, calibration, imaging, and deconvolution code, this package includes interfaces to MIRIAD (ascl:1106.007) and HEALPix (ascl:1107.018), and math/fitting routines from SciPy.

[ascl:1609.011] Photutils: Photometry tools

Photutils provides tools for detecting and performing photometry of astronomical sources. It can estimate the background and background rms in astronomical images, detect sources in astronomical images, estimate morphological parameters of those sources (e.g., centroid and shape parameters), and perform aperture and PSF photometry. Written in Python, it is an affiliated package of Astropy (ascl:1304.002).

[ascl:1609.010] CuBANz: Photometric redshift estimator

CuBANz is a photometric redshift estimator code for high redshift galaxies that uses the back propagation neural network along with clustering of the training set, making it very efficient. The training set is divided into several self learning clusters with galaxies having similar photometric properties and spectroscopic redshifts within a given span. The clustering algorithm uses the color information (i.e. u-g, g-r etc.) rather than the apparent magnitudes at various photometric bands, as the photometric redshift is more sensitive to the flux differences between different bands rather than the actual values. The clustering method enables accurate determination of the redshifts. CuBANz considers uncertainty in the photometric measurements as well as uncertainty in the neural network training. The code is written in C.

[ascl:1609.009] NSCool: Neutron star cooling code

NSCool is a 1D (i.e., spherically symmetric) neutron star cooling code written in Fortran 77. The package also contains a series of EOSs (equation of state) to build stars, a series of pre-built stars, and a TOV (Tolman- Oppenheimer-Volkoff) integrator to build stars from an EOS. It can also handle “strange stars” that have a huge density discontinuity between the quark matter and the covering thin baryonic crust. NSCool solves the heat transport and energy balance equations in whole GR, resulting in a time sequence of temperature profiles (and, in particular, a Teff - age curve). Several heating processes are included, and more can easily be incorporated. In particular it can evolve a star undergoing accretion with the resulting deep crustal heating, under a steady or time-variable accretion rate. NSCool is robust, very fast, and highly modular, making it easy to add new subroutines for new processes.

[ascl:1609.008] GRASP: General-purpose Relativistic Atomic Structure Package

GRASP (General-purpose Relativistic Atomic Structure Package) calculates atomic structure, including energy levels, radiative rates (A-values) and lifetimes; it is a fully relativistic code based on the jj coupling scheme. This code has been superseded by GRASP2K (ascl:1611.007).

[ascl:1609.007] Weighted EMPCA: Weighted Expectation Maximization Principal Component Analysis

Weighted EMPCA performs principal component analysis (PCA) on noisy datasets with missing values. Estimates of the measurement error are used to weight the input data such that the resulting eigenvectors, when compared to classic PCA, are more sensitive to the true underlying signal variations rather than being pulled by heteroskedastic measurement noise. Missing data are simply limiting cases of weight = 0. The underlying algorithm is a noise weighted expectation maximization (EM) PCA, which has additional benefits of implementation speed and flexibility for smoothing eigenvectors to reduce the noise contribution.

[ascl:1609.006] SCIMES: Spectral Clustering for Interstellar Molecular Emission Segmentation

SCIMES identifies relevant molecular gas structures within dendrograms of emission using the spectral clustering paradigm. It is useful for decomposing objects in complex environments imaged at high resolution.

[ascl:1609.005] FISHPACK90: Efficient FORTRAN Subprograms for the Solution of Separable Elliptic Partial Differential Equations

FISHPACK90 is a modernization of the original FISHPACK (ascl:1609.004), employing Fortran90 to slightly simplify and standardize the interface to some of the routines. This collection of Fortran programs and subroutines solves second- and fourth-order finite difference approximations to separable elliptic Partial Differential Equations (PDEs). These include Helmholtz equations in cartesian, polar, cylindrical, and spherical coordinates, as well as more general separable elliptic equations. The solvers use the cyclic reduction algorithm. When the problem is singular, a least-squares solution is computed. Singularities induced by the coordinate system are handled, including at the origin r=0 in cylindrical coordinates, and at the poles in spherical coordinates. Test programs are provided for the 19 solvers. Each serves two purposes: as a template to guide you in writing your own codes utilizing the FISHPACK90 solvers, and as a demonstration on your computer that you can correctly produce FISHPACK90 executables.

[ascl:1609.004] FISHPACK: Efficient FORTRAN Subprograms for the Solution of Separable Elliptic Partial Differential Equations

The FISHPACK collection of Fortran77 subroutines solves second- and fourth-order finite difference approximations to separable elliptic Partial Differential Equations (PDEs). These include Helmholtz equations in cartesian, polar, cylindrical, and spherical coordinates, as well as more general separable elliptic equations. The solvers use the cyclic reduction algorithm. When the problem is singular, a least-squares solution is computed. Singularities induced by the coordinate system are handled, including at the origin r=0 in cylindrical coordinates, and at the poles in spherical coordinates. A modernization of FISHPACK is available as FISHPACK90 (ascl:1609.005).

[ascl:1609.003] Kranc: Cactus modules from Mathematica equations

Kranc turns a tensorial description of a time dependent partial differential equation into a module for the Cactus Computational Toolkit (ascl:1102.013). This Mathematica application takes a simple continuum description of a problem and generates highly efficient and portable code, and can be used both for rapid prototyping of evolution systems and for high performance supercomputing.

[ascl:1609.002] StarPy: Quenched star formation history parameters of a galaxy using MCMC

StarPy derives the quenching star formation history (SFH) of a single galaxy through the Bayesian Markov Chain Monte Carlo method code emcee (ascl:1303.002). The sample function implements the emcee EnsembleSampler function for the galaxy colors input. Burn-in is run and calculated for the length specified before the sampler is reset and then run for the length of steps specified. StarPy provides the ability to use the look-up tables provided or creating your own.

[ascl:1609.001] T-PHOT: PSF-matched, prior-based, multiwavelength extragalactic deconfusion photometry

T-PHOT extracts accurate photometry from low-resolution images of extragalactic fields, where the blending of sources can be a serious problem for accurate and unbiased measurement of fluxes and colors. It gathers data from a high-resolution image of a region of the sky and uses the source positions and morphologies to obtain priors for the photometric analysis of the lower resolution image of the same field. T-PHOT handles different types of datasets as input priors, including a list of objects that will be used to obtain cutouts from the real high-resolution image, a set of analytical models (as .fits stamps), and a list of unresolved, point-like sources, useful for example for far-infrared wavelength domains. T-PHOT yields accurate estimations of fluxes within the intrinsic uncertainties of the method when systematic errors are taken into account (which can be done using a flagging code given in the output), and handles multiwavelength optical to far-infrared image photometry. T-PHOT was developed as part of the ASTRODEEP project (www.astrodeep.eu).

[ascl:1608.020] SPIDERz: SuPport vector classification for IDEntifying Redshifts

SPIDERz (SuPport vector classification for IDEntifying Redshifts) applies powerful support vector machine (SVM) optimization and statistical learning techniques to custom data sets to obtain accurate photometric redshift (photo-z) estimations. It is written for the IDL environment and can be applied to traditional data sets consisting of photometric band magnitudes, or alternatively to data sets with additional galaxy parameters (such as shape information) to investigate potential correlations between the extra galaxy parameters and redshift.

[ascl:1608.019] NEBULAR: Spectrum synthesis for mixed hydrogen-helium gas in ionization equilibrium

NEBULAR synthesizes the spectrum of a mixed hydrogen helium gas in collisional ionization equilibrium. It is not a spectral fitting code, but it can be used to resample a model spectrum onto the wavelength grid of a real observation. It supports a wide range of temperatures and densities. NEBULAR includes free-free, free-bound, two-photon and line emission from HI, HeI and HeII. The code will either return the composite model spectrum, or, if desired, the unrescaled atomic emission coefficients. It is written in C++ and depends on the GNU Scientific Library (GSL).

[ascl:1608.018] LORENE: Spectral methods differential equations solver

LORENE (Langage Objet pour la RElativité NumériquE) solves various problems arising in numerical relativity, and more generally in computational astrophysics. It is a set of C++ classes and provides tools to solve partial differential equations by means of multi-domain spectral methods. LORENE classes implement basic structures such as arrays and matrices, but also abstract mathematical objects, such as tensors, and astrophysical objects, such as stars and black holes.

[ascl:1608.017] 21CMMC: Parallelized Monte Carlo Markov Chain analysis tool for the epoch of reionization (EoR)

21CMMC is an efficient Python sampler of the semi-numerical reionization simulation code 21cmFAST (ascl:1102.023). It can recover constraints on astrophysical parameters from current or future 21 cm EoR experiments, accommodating a variety of EoR models, as well as priors on individual model parameters and the reionization history. By studying the resulting impact on the EoR astrophysical constraints, 21CMMC can be used to optimize foreground cleaning algorithms; interferometer designs; observing strategies; alternate statistics characterizing the 21cm signal; and synergies with other observational programs.

[ascl:1608.016] NICIL: Non-Ideal magnetohydrodynamics Coefficients and Ionisation Library

NICIL (Non-Ideal magnetohydrodynamics Coefficients and Ionisation Library) calculates the ionization values and the coefficients of the non-ideal magnetohydrodynamics terms of Ohmic resistivity, the Hall effect, and ambipolar diffusion. Written as a standalone Fortran90 module that can be implemented in existing codes, NICIL is fully parameterizable, allowing the user to choose which processes to include and decide the values of the free parameters. The module includes both cosmic ray and thermal ionization; the former includes two ion species and three species of dust grains (positively charged, negatively charged and neutral), and the latter includes five elements which can be doubly ionized.

[ascl:1608.015] 2DFFT: Measuring Galactic Spiral Arm Pitch Angle

2DFFT utilizes two-dimensional fast Fourier transformations of images of spiral galaxies to isolate and measure the pitch angles of their spiral arms; this provides a quantitative way to measure this morphological feature and allows comparison of spiral galaxy pitch angle to other galactic parameters and test spiral arm genesis theories. 2DFFT requires fourn.c from Numerical Recipes in C (Press et al. 1989).

P2DFFT (ascl:1806.011) is a parallelized version of 2DFFT.

[ascl:1608.014] gevolution: General Relativity Cosmological N-body code for evolution of large scale structures

The N-body code gevolution complies with general relativity principles at every step; it calculates all six metric degrees of freedom in Poisson gauge. N-body particles are evolved by solving the geodesic equation written in terms of a canonical momentum to remain valid for relativistic particles. gevolution can be extended to include different kinds of dark energy or modified gravity models, going beyond the usually adopted quasi-static approximation. A weak field expansion is the central element of gevolution; this permits the code to treat settings in which no strong gravitational fields appear, including arbitrary scenarios with relativistic sources as long as gravitational fields are not very strong. The framework is well suited for cosmology, but may also be useful for astrophysical applications with moderate gravitational fields where a Newtonian treatment is insufficient.

[ascl:1608.013] DOLPHOT: Stellar photometry

DOLPHOT is a stellar photometry package that was adapted from HSTphot for general use. It supports two modes; the first is a generic PSF-fitting package, which uses analytic PSF models and can be used for any camera. The second mode uses ACS PSFs and calibrations, and is effectively an ACS adaptation of HSTphot. A number of utility programs are also included with the DOLPHOT distribution, including basic image reduction routines.

[submitted] ExoPlanet

ExoPlanet provides a graphical interface for the construction, evaluation and application of a machine learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, ExoPlanet couples fast and well tested algorithms, a UI designed over the PyQt framework, and graphs rendered using Matplotlib. This serves to provide the user with a rich interface, rapid analytics and interactive visuals.

ExoPlanet is designed to have a minimal learning curve to allow researchers to focus more on the applicative aspect of machine learning algorithms rather than their implementation details and supports both methods of learning, providing algorithms for unsupervised and supervised training, which may be done with continuous or discrete labels. The parameters of each algorithms can be adjusted to ensure the best fit for the data. Training data is read from a CSV file, and after training is complete, ExoPlanet automates the building of the visual representations for the trained model. Once training and evaluation yield satisfactory results, the model may be used to make data based predictions on a new data set.

[ascl:1608.012] OBERON: OBliquity and Energy balance Run on N-body systems

OBERON (OBliquity and Energy balance Run on N-body systems) models the climate of Earthlike planets under the effects of an arbitrary number and arrangement of other bodies, such as stars, planets and moons. The code, written in C++, simultaneously computes N body motions using a 4th order Hermite integrator, simulates climates using a 1D latitudinal energy balance model, and evolves the orbital spin of bodies using the equations of Laskar (1986a,b).

[ascl:1608.011] PROFFIT: Analysis of X-ray surface-brightness profiles

PROFFIT analyzes X-ray surface-brightness profiles for data from any X-ray instrument. It can extract surface-brightness profiles in circular or elliptical annuli, using constant or logarithmic bin size, from the image centroid, the surface-brightness peak, or any user-given center, and provides surface-brightness profiles in any circular or elliptical sectors. It offers background map support to extract background profiles, can excise areas using SAO DS9-compatible (ascl:0003.002) region files to exclude point sources, provides fitting with a number of built-in models, including the popular beta model, double beta, cusp beta, power law, and projected broken power law, uses chi-squared or C statistic, and can fit on the surface-brightness or counts data. It has a command-line interface similar to HEASOFT’s XSPEC (ascl:9910.005) package, provides interactive help with a description of all the commands, and results can be saved in FITS, ROOT or TXT format.

[ascl:1608.010] pvextractor: Position-Velocity Diagram Extractor

Given a path defined in sky coordinates and a spectral cube, pvextractor extracts a slice of the cube along that path and along the spectral axis to produce a position-velocity or position-frequency slice. The path can be defined programmatically in pixel or world coordinates, and can also be drawn interactively using a simple GUI. Pvextractor is the main function, but also includes a few utilities related to header trimming and parsing.

[ascl:1608.009] FilFinder: Filamentary structure in molecular clouds

FilFinder extracts and analyzes filamentary structure in molecular clouds. In particular, it is capable of uniformly extracting structure over a large dynamical range in intensity. It returns the main filament properties: local amplitude and background, width, length, orientation and curvature. FilFinder offers additional tools to, for example, create a filament-only image based on the properties of the radial fits. The resulting mask and skeletons may be saved in FITS format, and property tables may be saved as a CSV, FITS or LaTeX table.

[ascl:1608.008] Cuba: Multidimensional numerical integration library

The Cuba library offers four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. The four algorithms work by very different methods, and can integrate vector integrands and have very similar Fortran, C/C++, and Mathematica interfaces. Their invocation is very similar, making it easy to cross-check by substituting one method by another. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.

[ascl:1608.007] BASE-9: Bayesian Analysis for Stellar Evolution with nine variables

The BASE-9 (Bayesian Analysis for Stellar Evolution with nine variables) software suite recovers star cluster and stellar parameters from photometry and is useful for analyzing single-age, single-metallicity star clusters, binaries, or single stars, and for simulating such systems. BASE-9 uses a Markov chain Monte Carlo (MCMC) technique along with brute force numerical integration to estimate the posterior probability distribution for the age, metallicity, helium abundance, distance modulus, line-of-sight absorption, and parameters of the initial-final mass relation (IFMR) for a cluster, and for the primary mass, secondary mass (if a binary), and cluster probability for every potential cluster member. The MCMC technique is used for the cluster quantities (the first six items listed above) and numerical integration is used for the stellar quantities (the last three items in the above list).

[ascl:1608.006] Gemini IRAF: Data reduction software for the Gemini telescopes

The Gemini IRAF package processes observational data obtained with the Gemini telescopes. It is an external package layered upon IRAF and supports data from numerous instruments, including FLAMINGOS-2, GMOS-N, GMOS-S, GNIRS, GSAOI, NIFS, and NIRI. The Gemini IRAF package is organized into sub-packages; it contains a generic tools package, "gemtools", along with instrument-specific packages. The raw data from the Gemini facility instruments are stored as Multi-Extension FITS (MEF) files. Therefore, all the tasks in the Gemini IRAF package, intended for processing data from the Gemini facility instruments, are capable of handling MEF files.

[ascl:1608.005] AstroVis: Visualizing astronomical data cubes

AstroVis enables rapid visualization of large data files on platforms supporting the OpenGL rendering library. Radio astronomical observations are typically three dimensional and stored as data cubes. AstroVis implements a scalable approach to accessing these files using three components: a File Access Component (FAC) that reduces the impact of reading time, which speeds up access to the data; the Image Processing Component (IPC), which breaks up the data cube into smaller pieces that can be processed locally and gives a representation of the whole file; and Data Visualization, which implements an approach of Overview + Detail to reduces the dimensions of the data being worked with and the amount of memory required to store it. The result is a 3D display paired with a 2D detail display that contains a small subsection of the original file in full resolution without reducing the data in any way.

[ascl:1608.004] BART: Bayesian Atmospheric Radiative Transfer fitting code

BART implements a Bayesian, Monte Carlo-driven, radiative-transfer scheme for extracting parameters from spectra of planetary atmospheres. BART combines a thermochemical-equilibrium code, a one-dimensional line-by-line radiative-transfer code, and the Multi-core Markov-chain Monte Carlo statistical module to constrain the atmospheric temperature and chemical-abundance profiles of exoplanets.

[ascl:1608.003] appaloosa: Python-based flare finding code for Kepler light curves

The appaloosa suite automates flare-finding in every Kepler light curves. It builds quiescent light curve models that include long- and short-cadence data through iterative de-trending and includes completeness estimates via artificial flare injection and recovery tests.

[ascl:1608.002] pyXSIM: Synthetic X-ray observations generator

pyXSIM simulates X-ray observations from astrophysical sources. X-rays probe the high-energy universe, from hot galaxy clusters to compact objects such as neutron stars and black holes and many interesting sources in between. pyXSIM generates synthetic X-ray observations of these sources from a wide variety of models, whether from grid-based simulation codes such as FLASH (ascl:1010.082), Enzo (ascl:1010.072), and Athena (ascl:1010.014), to particle-based codes such as Gadget (ascl:0003.001) and AREPO (ascl:1909.010), and even from datasets that have been created “by hand”, such as from NumPy arrays. pyXSIM can also manipulate the synthetic observations it produces in various ways and export the simulated X-ray events to other software packages to simulate the end products of specific X-ray observatories. pyXSIM is an implementation of the PHOX (ascl:1112.004) algorithm and was initially the photon_simulator analysis module in yt (ascl:1011.022); it is dependent on yt.

[ascl:1608.001] Stingray: Spectral-timing software

Stingray is a spectral-timing software package for astrophysical X-ray (and more) data. The package merges existing efforts for a (spectral-)timing package in Python and is composed of a library of time series methods (including power spectra, cross spectra, covariance spectra, and lags); scripts to load FITS data files from different missions; a simulator of light curves and event lists that includes different kinds of variability and more complicated phenomena based on the impulse response of given physical events (e.g. reverberation); and a GUI to ease the learning curve for new users.

[ascl:1607.020] SEEK: Signal Extraction and Emission Kartographer

SEEK (Signal Extraction and Emission Kartographer) processes time-ordered-data from single dish radio telescopes or from the simulation pipline HIDE (ascl:1607.019), removes artifacts from Radio Frequency Interference (RFI), automatically applies flux calibration, and recovers the astronomical radio signal. With its companion code HIDE (ascl:1607.019), it provides end-to-end simulation and processing of radio survey data.

[ascl:1607.019] HIDE: HI Data Emulator

HIDE (HI Data Emulator) forward-models the process of collecting astronomical radio signals in a single dish radio telescope instrument and outputs pixel-level time-ordered-data. Written in Python, HIDE models the noise and RFI modeling of the data and with its companion code SEEK (ascl:1607.020) provides end-to-end simulation and processing of radio survey data.

[ascl:1607.018] LZIFU: IDL emission line fitting pipeline for integral field spectroscopy data

LZIFU (LaZy-IFU) is an emission line fitting pipeline for integral field spectroscopy (IFS) data. Written in IDL, the pipeline turns IFS data to 2D emission line flux and kinematic maps for further analysis. LZIFU has been applied and tested extensively to various IFS data, including the SAMI Galaxy Survey, the Wide-Field Spectrograph (WiFeS), the CALIFA survey, the S7 survey and the MUSE instrument on the VLT.

[ascl:1607.017] BoxRemap: Volume and local structure preserving mapping of periodic boxes

BoxRemap remaps the cubical domain of a cosmological simulation into simple non-cubical shapes. It can be used for on-the-fly remappings of the simulation geometry and is volume-preserving; remapped geometry has the same volume V = L3 as the original simulation box. The remappings are structure-preserving (local neighboring structures are mapped to neighboring places) and one-to-one, with every particle/halo/galaxy/etc. appearing once and only once in the remapped volume.

[ascl:1607.016] astLib: Tools for research astronomers

astLib is a set of Python modules for performing astronomical plots, some statistics, common calculations, coordinate conversions, and manipulating FITS images with World Coordinate System (WCS) information through PyWCSTools, a simple wrapping of WCSTools (ascl:1109.015).

[ascl:1607.015] RT1D: 1D code for Rayleigh-Taylor instability

The parallel one-dimensional moving-mesh hydrodynamics code RT1D reproduces the multidimensional dynamics from Rayleigh-Taylor instability in supernova remnants.

[ascl:1607.014] SOPIE: Sequential Off-Pulse Interval Estimation

SOPIE (Sequential Off-Pulse Interval Estimation) provides functions to non-parametrically estimate the off-pulse interval of a source function originating from a pulsar. The technique is based on a sequential application of P-values obtained from goodness-of-fit tests for the uniform distribution, such as the Kolmogorov-Smirnov, Cramér-von Mises, Anderson-Darling and Rayleigh goodness-of-fit tests.

[ascl:1607.013] Kālī: Time series data modeler

The fully parallelized and vectorized software package Kālī models time series data using various stochastic processes such as continuous-time ARMA (C-ARMA) processes and uses Bayesian Markov Chain Monte-Carlo (MCMC) for inferencing a stochastic light curve. Kālī is written in c++ with Python language bindings for ease of use. Kālī is named jointly after the Hindu goddess of time, change, and power and also as an acronym for KArma LIbrary.

[ascl:1607.012] ZASPE: Zonal Atmospheric Stellar Parameters Estimator

ZASPE (Zonal Atmospheric Stellar Parameters Estimator) computes the atmospheric stellar parameters (Teff, log(g), [Fe/H] and vsin(i)) from echelle spectra via least squares minimization with a pre-computed library of synthetic spectra. The minimization is performed only in the most sensitive spectral zones to changes in the atmospheric parameters. The uncertainities and covariances computed by ZASPE assume that the principal source of error is the systematic missmatch between the observed spectrum and the sythetic one that produces the best fit. ZASPE requires a grid of synthetic spectra and can use any pre-computed library minor modifications.

[ascl:1607.011] HfS: Hyperfine Structure fitting tool

HfS fits the hyperfine structure of spectral lines, with multiple velocity components. The HfS_nh3 procedures included in HfS fit simultaneously the hyperfine structure of the NH3 (J,K)= (1,1) and (2,2) inversion transitions, and perform a standard analysis to derive the NH3 column density, rotational temperature Trot, and kinetic temperature Tk. HfS uses a Monte Carlo approach for fitting the line parameters, with special attention to the derivation of the parameter uncertainties. HfS includes procedures that make use of parallel computing for fitting spectra from a data cube.

[ascl:1607.009] PICsar: Particle in cell pulsar magnetosphere simulator

PICsar simulates the magnetosphere of an aligned axisymmetric pulsar and can be used to simulate other arbitrary electromagnetics problems in axisymmetry. Written in Fortran, this special relativistic, electromagnetic, charge conservative particle in cell code features stretchable body-fitted coordinates that follow the surface of a sphere, simplifying the application of boundary conditions in the case of the aligned pulsar; a radiation absorbing outer boundary, which allows a steady state to be set up dynamically and maintained indefinitely from transient initial conditions; and algorithms for injection of charged particles into the simulation domain. PICsar is parallelized using MPI and has been used on research problems with ~1000 CPUs.

[ascl:1607.010] K2PS: K2 Planet search

K2PS is an Oxford K2 planet search pipeline. Written in Python, it searches for transit-like signals from the k2sc-detrended light curves.

[ascl:1607.008] BLS: Box-fitting Least Squares

BLS (Box-fitting Least Squares) is a box-fitting algorithm that analyzes stellar photometric time series to search for periodic transits of extrasolar planets. It searches for signals characterized by a periodic alternation between two discrete levels, with much less time spent at the lower level.

[ascl:1607.007] JUDE: An Utraviolet Imaging Telescope pipeline

JUDE (Jayant's UVIT Data Explorer) converts the Level 1 data (FITS binary table) from the Ultraviolet Imaging Telescope (UVIT) on ASTROSAT into three output files: a photon event list as a function of frame number (FITS binary table); a FITS image file with two extensions; and a PNG file created from the FITS image file with an automated scaling.

[ascl:1607.006] Cholla: 3D GPU-based hydrodynamics code for astrophysical simulation

Cholla (Computational Hydrodynamics On ParaLLel Architectures) models the Euler equations on a static mesh and evolves the fluid properties of thousands of cells simultaneously using GPUs. It can update over ten million cells per GPU-second while using an exact Riemann solver and PPM reconstruction, allowing computation of astrophysical simulations with physically interesting grid resolutions (>256^3) on a single device; calculations can be extended onto multiple devices with nearly ideal scaling beyond 64 GPUs.

[ascl:1607.005] Planetary3br: Three massive body resonance calculator

Given two planets P1 and P2 with arbitrary orbits, planetary3br calculates all possible semimajor axes that a third planet P0 can have in order for the system to be in a three body resonance; these are identified by the combination k0*P0 + k1*P1 + k2*P2. P1 and P2 are assumed to be not in an exact two-body resonance. The program also calculates three "strengths" of the resonance, one for each planet, which are only indicators of the dynamical relevance of the resonance on each planet. Sample input data are available along with the Fortran77 source code.

[ascl:1607.004] Atlas3bgeneral: Three-body resonance calculator

For a massless test particle and given a planetary system, atlas3bgeneral calculates all three body resonances in a given range of semimajor axes with all the planets taken by pairs. Planets are assumed in fixed circular and coplanar orbits and the test particle with arbitrary orbit. A sample input data file to calculate the three-body resonances is available for use with the Fortran77 source code.

[ascl:1607.003] Atlas2bgeneral: Two-body resonance calculator

For a massless test particle and given a planetary system, Atlas2bgeneral calculates all resonances in a given range of semimajor axes with all the planets taken one by one. Planets are assumed in fixed circular and coplanar orbits and the test particle with arbitrary orbit. A sample input data file to calculate the two-body resonances is available for use with the Fortran77 source code.

[ascl:1607.002] DICE: Disk Initial Conditions Environment

DICE models initial conditions of idealized galaxies to study their secular evolution or their more complex interactions such as mergers or compact groups using N-Body/hydro codes. The code can set up a large number of components modeling distinct parts of the galaxy, and creates 3D distributions of particles using a N-try MCMC algorithm which does not require a prior knowledge of the distribution function. The gravitational potential is then computed on a multi-level Cartesian mesh by solving the Poisson equation in the Fourier space. Finally, the dynamical equilibrium of each component is computed by integrating the Jeans equations for each particles. Several galaxies can be generated in a row and be placed on Keplerian orbits to model interactions. DICE writes the initial conditions in the Gadget1 or Gadget2 (ascl:0003.001) format and is fully compatible with Ramses (ascl:1011.007).

[ascl:1607.001] AGNfitter: SED-fitting code for AGN and galaxies from a MCMC approach

AGNfitter is a fully Bayesian MCMC method to fit the spectral energy distributions (SEDs) of active galactic nuclei (AGN) and galaxies from the sub-mm to the UV; it enables robust disentanglement of the physical processes responsible for the emission of sources. Written in Python, AGNfitter makes use of a large library of theoretical, empirical, and semi-empirical models to characterize both the nuclear and host galaxy emission simultaneously. The model consists of four physical emission components: an accretion disk, a torus of AGN heated dust, stellar populations, and cold dust in star forming regions. AGNfitter determines the posterior distributions of numerous parameters that govern the physics of AGN with a fully Bayesian treatment of errors and parameter degeneracies, allowing one to infer integrated luminosities, dust attenuation parameters, stellar masses, and star formation rates.

[ascl:1606.015] FLASK: Full-sky Lognormal Astro-fields Simulation Kit

FLASK (Full-sky Lognormal Astro-fields Simulation Kit) makes tomographic realizations on the sphere of an arbitrary number of correlated lognormal or Gaussian random fields; it can create joint simulations of clustering and lensing with sub-per-cent accuracy over relevant angular scales and redshift ranges. It is C++ code parallelized with OpenMP; FLASK generates fast full-sky simulations of cosmological large-scale structure observables such as multiple matter density tracers (galaxies, quasars, dark matter haloes), CMB temperature anisotropies and weak lensing convergence and shear fields. The mutiple fields can be generated tomographically in an arbitrary number of redshift slices and all their statistical properties (including cross-correlations) are determined by the angular power spectra supplied as input and the multivariate lognormal (or Gaussian) distribution assumed for the fields. Effects like redshift space distortions, doppler distortions, magnification biases, evolution and intrinsic aligments can be introduced in the simulations via the input power spectra which must be supplied by the user.

[ascl:1606.014] Lmfit: Non-Linear Least-Square Minimization and Curve-Fitting for Python

Lmfit provides a high-level interface to non-linear optimization and curve fitting problems for Python. Lmfit builds on and extends many of the optimization algorithm of scipy.optimize, especially the Levenberg-Marquardt method from optimize.leastsq. Its enhancements to optimization and data fitting problems include using Parameter objects instead of plain floats as variables, the ability to easily change fitting algorithms, and improved estimation of confidence intervals and curve-fitting with the Model class. Lmfit includes many pre-built models for common lineshapes.

[ascl:1606.013] Pulse Portraiture: Pulsar timing

Pulse Portraiture is a wideband pulsar timing code written in python. It uses an extension of the FFTFIT algorithm (Taylor 1992) to simultaneously measure a phase (TOA) and dispersion measure (DM). The code includes a Gaussian-component-based portrait modeling routine. The code uses the python interface to the pulsar data analysis package PSRCHIVE (ascl:1105.014) and also requires the non-linear least-squares minimization package lmfit (ascl:1606.014).

[ascl:1606.012] KMDWARFPARAM: Parameters estimator for K and M dwarf stars

KMDWARFPARAM estimates the physical parameters of a star with mass M < 0.8 M_sun given one or more observational constraints. The code runs a Markov-Chain Monte Carlo procedure to estimate the parameter values and their uncertainties.

[ascl:1606.011] FDIPS: Finite Difference Iterative Potential-field Solver

FDIPS is a finite difference iterative potential-field solver that can generate the 3D potential magnetic field solution based on a magnetogram. It is offered as an alternative to the spherical harmonics approach, as when the number of spherical harmonics is increased, using the raw magnetogram data given on a grid that is uniform in the sine of the latitude coordinate can result in inaccurate and unreliable results, especially in the polar regions close to the Sun. FDIPS is written in Fortran 90 and uses the MPI library for parallel execution.

[ascl:1606.010] SimpLens: Interactive gravitational lensing simulator

SimpLens illustrates some of the theoretical ideas important in gravitational lensing in an interactive way. After setting parameters for elliptical mass distribution and external mass, SimpLens displays the mass profile and source position, the lens potential and image locations, and indicate the image magnifications and contours of virtual light-travel time. A lens profile can be made shallower or steeper with little change in the image positions and with only total magnification affected.

[ascl:1606.009] Companion-Finder: Planets and binary companions in time series spectra

Companion-Finder looks for planets and binary companions in time series spectra by searching for the spectral lines of stellar companions to other stars observed with high-precision radial-velocity surveys.

[ascl:1606.008] s2: Object oriented wrapper for functions on the sphere

The s2 package can represent any arbitrary function defined on the sphere. Both real space map and harmonic space spherical harmonic representations are supported. Basic sky representations have been extended to simulate full sky noise distributions and Gaussian cosmic microwave background realisations. Support for the representation and convolution of beams is also provided. The code requires HEALPix (ascl:1107.018) and CFITSIO (ascl:1010.001).

[ascl:1606.007] COMB: Compact embedded object simulations

COMB supports the simulation on the sphere of compact objects embedded in a stochastic background process of specified power spectrum. Support is provided to add additional white noise and convolve with beam functions. Functionality to support functions defined on the sphere is provided by the S2 code (ascl:1606.008); HEALPix (ascl:1107.018) and CFITSIO (ascl:1010.001) are also required.

[ascl:1606.006] uvmcmcfit: Parametric models to interferometric data fitter

Uvmcmcfit fits parametric models to interferometric data. It is ideally suited to extract the maximum amount of information from marginally resolved observations with interferometers like the Atacama Large Millimeter Array (ALMA), Submillimeter Array (SMA), and Plateau de Bure Interferometer (PdBI). uvmcmcfit uses emcee (ascl:1303.002) to do Markov Chain Monte Carlo (MCMC) and can measure the goodness of fit from visibilities rather than deconvolved images, an advantage when there is strong gravitational lensing and in other situations. uvmcmcfit includes a pure-Python adaptation of Miriad’s (ascl:1106.007) uvmodel task to generate simulated visibilities given observed visibilities and a model image and a simple ray-tracing routine that allows it to account for both strongly lensed systems (where multiple images of the lensed galaxy are detected) and weakly lensed systems (where only a single image of the lensed galaxy is detected).

[ascl:1606.005] PyMultiNest: Python interface for MultiNest

PyMultiNest provides programmatic access to MultiNest (ascl:1109.006) and PyCuba, integration existing Python code (numpy, scipy), and enables writing Prior & LogLikelihood functions in Python. PyMultiNest can plot and visualize MultiNest's progress and allows easy plotting, visualization and summarization of MultiNest results. The plotting can be run on existing MultiNest output, and when not using PyMultiNest for running MultiNest.

[ascl:1606.004] HIBAYES: Global 21-cm Bayesian Monte-Carlo Model Fitting

HIBAYES implements fully-Bayesian extraction of the sky-averaged (global) 21-cm signal from the Cosmic Dawn and Epoch of Reionization in the presence of foreground emission. User-defined likelihood and prior functions are called by the sampler PyMultiNest (ascl:1606.005) in order to jointly explore the full (signal plus foreground) posterior probability distribution and evaluate the Bayesian evidence for a given model. Implemented models, for simulation and fitting, include gaussians (HI signal) and polynomials (foregrounds). Some simple plotting and analysis tools are supplied. The code can be extended to other models (physical or empirical), to incorporate data from other experiments, or to use alternative Monte-Carlo sampling engines as required.

[ascl:1606.003] Cygrid: Cython-powered convolution-based gridding module for Python

The Python module Cygrid grids (resamples) data to any collection of spherical target coordinates, although its typical application involves FITS maps or data cubes. The module supports the FITS world coordinate system (WCS) standard; its underlying algorithm is based on the convolution of the original samples with a 2D Gaussian kernel. A lookup table scheme allows parallelization of the code and is combined with the HEALPix tessellation of the sphere for fast neighbor searches. Cygrid's runtime scales between O(n) and O(nlog n), with n being the number of input samples.

[ascl:1606.002] PAL: Positional Astronomy Library

The PAL library is a partial re-implementation of Pat Wallace's popular SLALIB library written in C using a Gnu GPL license and layered on top of the IAU's SOFA library (or the BSD-licensed ERFA) where appropriate. PAL attempts to stick to the SLA C API where possible.

[ascl:1606.001] SWOC: Spectral Wavelength Optimization Code

SWOC (Spectral Wavelength Optimization Code) determines the wavelength ranges that provide the optimal amount of information to achieve the required science goals for a spectroscopic study. It computes a figure-of-merit for different spectral configurations using a user-defined list of spectral features, and, utilizing a set of flux-calibrated spectra, determines the spectral regions showing the largest differences among the spectra.

[ascl:1605.017] Surprise Calculator: Estimating relative entropy and Surprise between samples

The Surprise is a measure for consistency between posterior distributions and operates in parameter space. It can be used to analyze either the compatibility of separately analyzed posteriors from two datasets, or the posteriors from a Bayesian update. The Surprise Calculator estimates relative entropy and Surprise between two samples, assuming they are Gaussian. The software requires the R package CompQuadForm to estimate the significance of the Surprise, and rpy2 to interface R with Python.

[ascl:1605.016] zeldovich-PLT: Zel'dovich approximation initial conditions generator

zeldovich-PLT generates Zel'dovich approximation (ZA) initial conditions (i.e. first-order Lagrangian perturbation theory) for cosmological N-body simulations, optionally applying particle linear theory (PLT) corrections.

[ascl:1605.015] SAND: Automated VLBI imaging and analyzing pipeline

The Search And Non-Destroy (SAND) is a VLBI data reduction pipeline composed of a set of Python programs based on the AIPS interface provided by ObitTalk. It is designed for the massive data reduction of multi-epoch VLBI monitoring research. It can automatically investigate calibrated visibility data, search all the radio emissions above a given noise floor and do the model fitting either on the CLEANed image or directly on the uv data. It then digests the model-fitting results, intelligently identifies the multi-epoch jet component correspondence, and recognizes the linear or non-linear proper motion patterns. The outputs including CLEANed image catalogue with polarization maps, animation cube, proper motion fitting and core light curves. For uncalibrated data, a user can easily add inline modules to do the calibration and self-calibration in a batch for a specific array.

[ascl:1605.014] DUO: Spectra of diatomic molecules

Duo computes rotational, rovibrational and rovibronic spectra of diatomic molecules. The software, written in Fortran 2003, solves the Schrödinger equation for the motion of the nuclei for the simple case of uncoupled, isolated electronic states and also for the general case of an arbitrary number and type of couplings between electronic states. Possible couplings include spin–orbit, angular momenta, spin-rotational and spin–spin. Introducing the relevant couplings using so-called Born–Oppenheimer breakdown curves can correct non-adiabatic effects.

[ascl:1605.013] grtrans: Polarized general relativistic radiative transfer via ray tracing

grtrans calculates ray tracing radiative transfer in the Kerr metric, including the full treatment of polarised radiative transfer and parallel transport along geodesics, for comparing theoretical models of black hole accretion flows and jets with observations. The code is written in Fortran 90 and parallelizes with OpenMP; the full code and several components have Python interfaces. grtrans includes Geokerr (ascl:1011.015) and requires cfitsio (ascl:1010.001) and pyfits (ascl:1207.009).

[ascl:1605.012] K2SC: K2 Systematics Correction

K2SC (K2 Systematics Correction) models instrumental systematics and astrophysical variability in light curves from the K2 mission. It enables the user to remove both position-dependent systematics and time-dependent variability (e.g., for transit searches) or to remove systematics while preserving variability (for variability studies). K2SC automatically computes estimates of the period, amplitude and evolution timescale of the variability for periodic variables and can be run on ASCII and FITS light curve files. Written in Python, this pipeline requires NumPy, SciPy, MPI4Py, Astropy (ascl:1304.002), and George (ascl:1511.015).

[ascl:1605.011] DISCO: 3-D moving-mesh magnetohydrodynamics package

DISCO evolves orbital fluid motion in two and three dimensions, especially at high Mach number, for studying astrophysical disks. The software uses a moving-mesh approach with a dynamic cylindrical mesh that can shear azimuthally to follow the orbital motion of the gas, thus removing diffusive advection errors and permitting longer timesteps than a static grid. DISCO uses an HLLD Riemann solver and a constrained transport scheme compatible with the mesh motion to implement magnetohydrodynamics.

[ascl:1605.010] TRIPPy: Python-based Trailed Source Photometry

TRIPPy (TRailed Image Photometry in Python) uses a pill-shaped aperture, a rectangle described by three parameters (trail length, angle, and radius) to improve photometry of moving sources over that done with circular apertures. It can generate accurate model and trailed point-spread functions from stationary background sources in sidereally tracked images. Appropriate aperture correction provides accurate, unbiased flux measurement. TRIPPy requires numpy, scipy, matplotlib, Astropy (ascl:1304.002), and stsci.numdisplay; emcee (ascl:1303.002) and SExtractor (ascl:1010.064) are optional.

[ascl:1605.009] ASTRiDE: Automated Streak Detection for Astronomical Images

ASTRiDE detects streaks in astronomical images using a "border" of each object (i.e. "boundary-tracing" or "contour-tracing") and their morphological parameters. Fast moving objects such as meteors, satellites, near-Earth objects (NEOs), or even cosmic rays can leave streak-like traces in the images; ASTRiDE can detect not only long streaks but also relatively short or curved streaks.

[ascl:1605.008] PDT: Photometric DeTrending Algorithm Using Machine Learning

PDT removes systematic trends in light curves. It finds clusters of light curves that are highly correlated using machine learning, constructs one master trend per cluster and detrends an individual light curve using the constructed master trends by minimizing residuals while constraining coefficients to be positive.

[ascl:1605.007] MUSCLE: MUltiscale Spherical-ColLapse Evolution

MUSCLE (MUltiscale Spherical ColLapse Evolution) produces low-redshift approximate N-body realizations accurate to few-Megaparsec scales. It applies a spherical-collapse prescription on multiple Gaussian-smoothed scales. It achieves higher accuracy than perturbative schemes (Zel'dovich and second-order Lagrangian perturbation theory - 2LPT), and by including the void-in-cloud process (voids in large-scale collapsing regions), solves problems with a single-scale spherical-collapse scheme.

[ascl:1605.006] CAMELOT: Cloud Archive for MEtadata, Library and Online Toolkit

CAMELOT facilitates the comparison of observational data and simulations of molecular clouds and/or star-forming regions. The central component of CAMELOT is a database summarizing the properties of observational data and simulations in the literature through pertinent metadata. The core functionality allows users to upload metadata, search and visualize the contents of the database to find and match observations/simulations over any range of parameter space.

To bridge the fundamental disconnect between inherently 2D observational data and 3D simulations, the code uses key physical properties that, in principle, are straightforward for both observers and simulators to measure — the surface density (Sigma), velocity dispersion (sigma) and radius (R). By determining these in a self-consistent way for all entries in the database, it should be possible to make robust comparisons.

[ascl:1605.005] TMBIDL: Single dish radio astronomy data reduction package

The IDL package reduces and analyzes radio astronomy data. It translates SDFITS files into TMBIDL format, and can average and display spectra, remove baselines, and fit Gaussian models.

[ascl:1605.004] BACCHUS: Brussels Automatic Code for Characterizing High accUracy Spectra

BACCHUS (Brussels Automatic Code for Characterizing High accUracy Spectra) derives stellar parameters (Teff, log g, metallicity, microturbulence velocity and rotational velocity), equivalent widths, and abundances. The code includes on the fly spectrum synthesis, local continuum normalization, estimation of local S/N, automatic line masking, four methods for abundance determinations, and a flagging system aiding line selection. BACCHUS relies on the grid of MARCS model atmospheres, Masseron's model atmosphere thermodynamic structure interpolator, and the radiative transfer code Turbospectrum (ascl:1205.004).

[ascl:1605.003] Shadowfax: Moving mesh hydrodynamical integration code

Shadowfax simulates galaxy evolution. Written in object-oriented modular C++, it evolves a mixture of gas, subject to the laws of hydrodynamics and gravity, and any collisionless fluid only subject to gravity, such as cold dark matter or stars. For the hydrodynamical integration, it makes use of a (co-) moving Lagrangian mesh. The code has a 2D and 3D version, contains utility programs to generate initial conditions and visualize simulation snapshots, and its input/output is compatible with a number of other simulation codes, e.g. Gadget2 (ascl:0003.001) and GIZMO (ascl:1410.003).

[ascl:1605.002] cluster-lensing: Tools for calculating properties and weak lensing profiles of galaxy clusters

The cluster-lensing package calculates properties and weak lensing profiles of galaxy clusters. Implemented in Python, it includes cluster mass-richness and mass-concentration scaling relations, and NFW halo profiles for weak lensing shear, the differential surface mass density ΔΣ(r), and for magnification, Σ(r). Optionally the calculation will include the effects of cluster miscentering offsets.

[ascl:1605.001] MARZ: Redshifting Program

MARZ analyzes objects and produces high quality spectroscopic redshift measurements. Spectra not matched correctly by the automatic algorithm can be redshifted manually by cycling automatic results, manual template comparison, or marking spectral features. The software has an intuitive interface and powerful automatic matching capabilities on spectra, and can be run interactively or from the command line, and runs as a Web application. MARZ can be run on a local server; it is also available for use on a public server.

[ascl:1604.012] TTVFaster: First order eccentricity transit timing variations (TTVs)

TTVFaster implements analytic formulae for transit time variations (TTVs) that are accurate to first order in the planet–star mass ratios and in the orbital eccentricities; the implementations are available in several languages, including IDL, Julia, Python and C. These formulae compare well with more computationally expensive N-body integrations in the low-eccentricity, low mass-ratio regime when applied to simulated and to actual multi-transiting Kepler planet systems.

[ascl:1604.011] FDPS: Framework for Developing Particle Simulators

FDPS provides the necessary functions for efficient parallel execution of particle-based simulations as templates independent of the data structure of particles and the functional form of the interaction. It is used to develop particle-based simulation programs for large-scale distributed-memory parallel supercomputers. FDPS includes templates for domain decomposition, redistribution of particles, and gathering of particle information for interaction calculation. It uses algorithms such as Barnes-Hut tree method for long-range interactions; methods to limit the calculation to neighbor particles are used for short-range interactions. FDPS reduces the time and effort necessary to write a simple, sequential and unoptimized program of O(N^2) calculation cost, and produces compiled programs that will run efficiently on large-scale parallel supercomputers.

[ascl:1604.009] CCSNMultivar: Core-Collapse Supernova Gravitational Waves

CCSNMultivar aids the analysis of core-collapse supernova gravitational waves. It includes multivariate regression of Fourier transformed or time domain waveforms, hypothesis testing for measuring the influence of physical parameters, and the Abdikamalov et. al. catalog for example use. CCSNMultivar can optionally incorporate additional uncertainty due to detector noise and approximate waveforms from anywhere within the parameter space.

[ascl:1604.008] The Tractor: Probabilistic astronomical source detection and measurement

The Tractor optimizes or samples from models of astronomical objects. The approach is generative: given astronomical sources and a description of the image properties, the code produces pixel-space estimates or predictions of what will be observed in the images. This estimate can be used to produce a likelihood for the observed data given the model: assuming the model space actually includes the truth (it doesn’t, in detail), then if we had the optimal model parameters, the predicted image would differ from the actually observed image only by noise. Given a noise model of the instrument and assuming pixelwise independent noise, the log-likelihood is the negative chi-squared difference: (image - model) / noise.

[ascl:1604.007] DNest3: Diffusive Nested Sampling

DNest3 is a C++ implementation of Diffusive Nested Sampling (ascl:1010.029), a Markov Chain Monte Carlo (MCMC) algorithm for Bayesian Inference and Statistical Mechanics. Relative to older DNest versions, DNest3 has improved performance (in terms of the sampling overhead, likelihood evaluations still dominate in general) and is cleaner code: implementing new models should be easier than it was before. In addition, DNest3 is multi-threaded, so one can run multiple MCMC walkers at the same time, and the results will be combined together.

[ascl:1604.006] 2-DUST: Dust radiative transfer code

2-DUST is a general-purpose dust radiative transfer code for an axisymmetric system that reveals the global energetics of dust grains in the shell and the 2-D projected morphologies of the shell that are strongly dependent on the mixed effects of the axisymmetric dust distribution and inclination angle. It can be used to model a variety of axisymmetric astronomical dust systems.

[ascl:1604.005] Halotools: Galaxy-Halo connection models

Halotools builds and tests models of the galaxy-halo connection and analyzes catalogs of dark matter halos. The core functions of the package include fast generation of synthetic galaxy populations using HODs, abundance matching, and related methods; efficient algorithms for calculating galaxy clustering, lensing, z-space distortions, and other astronomical statistics; a modular, object-oriented framework for designing galaxy evolution models; and end-to-end support for reducing halo catalogs and caching them as hdf5 files.

[ascl:1604.004] magicaxis: Pretty scientific plotting with minor-tick and log minor-tick support

The R suite magicaxis makes useful and pretty plots for scientific plotting and includes functions for base plotting, with particular emphasis on pretty axis labelling in a number of circumstances that are often used in scientific plotting. It also includes functions for generating images and contours that reflect the 2D quantile levels of the data designed particularly for output of MCMC posteriors where visualizing the location of the 68% and 95% 2D quantiles for covariant parameters is a necessary part of the post MCMC analysis, can generate low and high error bars, and allows clipping of values, rejection of bad values, and log stretching.

[ascl:1604.003] LAMBDAR: Lambda Adaptive Multi-Band Deblending Algorithm in R

LAMBDAR measures galaxy fluxes from an arbitrary FITS image, covering an arbitrary photometric wave-band, when provided all parameters needed to construct galactic apertures at the required locations for multi-band matched aperture galactic photometry. Through sophisticated matched aperture photometry, the package develops robust Spectral Energy Distributions (SEDs) and accurately establishes the physical properties of galactic objects. LAMBDAR was based on a package detailed in Bourne et al. (2012) that determined galactic fluxes in low resolution Herschel images.

[ascl:1604.002] libpolycomp: Compression/decompression library

Libpolycomp compresses and decompresses one-dimensional streams of numbers by means of several algorithms. It is well-suited for time-ordered data acquired by astronomical instruments or simulations. One of the algorithms, called "polynomial compression", combines two widely-used ideas (namely, polynomial approximation and filtering of Fourier series) to achieve substantial compression ratios for datasets characterized by smoothness and lack of noise. Notable examples are the ephemerides of astronomical objects and the pointing information of astronomical telescopes. Other algorithms implemented in this C library are well known and already widely used, e.g., RLE, quantization, deflate (via libz) and Burrows-Wheeler transform (via libbzip2). Libpolycomp can compress the timelines acquired by the Planck/LFI instrument with an overall compression ratio of ~9, while other widely known programs (gzip, bzip2) reach compression ratios less than 1.5.

[ascl:1604.001] OpenMHD: Godunov-type code for ideal/resistive magnetohydrodynamics (MHD)

OpenMHD is a Godunov-type finite-volume code for ideal/resistive magnetohydrodynamics (MHD). It is written in Fortran 90 and is parallelized by using MPI-3 and OpenMP. The code was originally developed for studying magnetic reconnection problems and has been made publicly available in the hope that others may find it useful.

[ascl:1603.018] PolRadTran: Polarized Radiative Transfer Model Distribution

PolRadTran is a plane-parallel polarized radiative transfer model. It is used to compute the radiance exiting a vertically inhomogeneous atmosphere containing randomly-oriented particles. Both solar and thermal sources of radiation are considered. A direct method of incorporating the polarized scattering information is combined with the doubling and adding method to produce a relatively simple formulation.

[ascl:1603.017] HIIexplorer: Detect and extract integrated spectra of HII regions

HIIexplorer detects and extracts the integrated spectra of HII regions from IFS datacubes. The procedure assumes H ii regions are peaky/isolated structures with a strong ionized gas emission, clearly above the continuum emission and the average ionized gas emission across the galaxy and that H ii regions have a typical physical size of about a hundred or a few hundreds of parsecs, which corresponds to a typical projected size at the distance of the galaxies of a few arcsec for galaxies at z~0.016. All input parameters can be derived from either a visual inspection and/or a statistical analysis of the Hα emission line map. The algorithm produces a segmentation FITS file describing the pixels associated to each H ii region. A newer version of this code, pyHIIexplorer (ascl:2206.010), is available.

[ascl:1603.016] ellc: Light curve model for eclipsing binary stars and transiting exoplanets

ellc analyzes the light curves of detached eclipsing binary stars and transiting exoplanet systems. The model represents stars as triaxial ellipsoids, and the apparent flux from the binary is calculated using Gauss-Legendre integration over the ellipses that are the projection of these ellipsoids on the sky. The code can also calculate the fluxweighted radial velocity of the stars during an eclipse (Rossiter-McLaghlin effect). ellc can model a wide range of eclipsing binary stars and extrasolar planetary systems, and can enable the use of modern Monte Carlo methods for data analysis and model testing.

[ascl:1603.015] Dedalus: Flexible framework for spectrally solving differential equations

Dedalus solves differential equations using spectral methods. It implements flexible algorithms to solve initial-value, boundary-value, and eigenvalue problems with broad ranges of custom equations and spectral domains. Its primary features include symbolic equation entry, multidimensional parallelization, implicit-explicit timestepping, and flexible analysis with HDF5. The code is written primarily in Python and features an easy-to-use interface. The numerical algorithm produces highly sparse systems for many equations which are efficiently solved using compiled libraries and MPI.

[ascl:1603.014] fibmeasure: Python/Cython module to find the center of back-illuminated optical fibers in metrology images

fibmeasure finds the precise locations of the centers of back-illuminated optical fibers in images. It was developed for astronomical fiber positioning feedback via machine vision cameras and is optimized for high-magnification images where fibers appear as resolvable circles. It was originally written during the design of the WEAVE pick-and-place fiber positioner for the William Herschel Telescope.

[ascl:1603.013] PyGDSM: Python interface to Global Diffuse Sky Models

PyGDSM (formely PyGSM) is a Python interface for the Global Sky Model (GSM, ascl:1011.010). The GSM is a model of diffuse galactic radio emission, constructed from a variety of all-sky surveys spanning the radio band (e.g. Haslam and WMAP). PyGDSM uses the GSM to generate all-sky maps in Healpix format of diffuse Galactic radio emission from 10 MHz to 94 GHz. The PyGDSM module provides visualization utilities, file output in FITS format, and the ability to generate observed skies for a given location and date. PyGDSM requires Healpy (ascl:2008.022), PyEphem (ascl:1112.014), and AstroPy (ascl:1304.002).

[ascl:1603.012] tpipe: Searching radio interferometry data for fast, dispersed transients

Visibilities from radio interferometers have not traditionally been used to study the fast transient sky. Millisecond transients (e.g., fast radio bursts) and periodic sources (e.g., pulsars) have been studied with single-dish radio telescopes and a software stack developed over the past few decades. tpipe is an initial attempt to develop the fast transient algorithms for visibility data. Functions exist for analysis of visibilties, such as reading data, flagging data, applying interferometric gain calibration, and imaging. These functions are given equal footing as time-domain techniques like filters and dedispersion.

tpipe has been largely superseded by rtpipe (ascl:1706.002).

[ascl:1603.011] DiskJockey: Protoplanetary disk modeling for dynamical mass derivation

DiskJockey derives dynamical masses for T Tauri stars using the Keplerian motion of their circumstellar disks, applied to radio interferometric data from the Atacama Large Millimeter Array (ALMA) and the Submillimeter Array (SMA). The package relies on RADMC-3D (ascl:1202.015) to perform the radiative transfer of the disk model. DiskJockey is designed to work in a parallel environment where the calculations for each frequency channel can be distributed to independent processors. Due to the computationally expensive nature of the radiative synthesis, fitting sizable datasets (e.g., SMA and ALMA) will require a substantial amount of CPU cores to explore a posterior distribution in a reasonable timeframe.

[ascl:1603.010] ExoPriors: Accounting for observational bias of transiting exoplanets

ExoPriors calculates a log-likelihood penalty for an input set of transit parameters to account for observational bias (geometric and signal-to-noise ratio detection bias) of transiting exoplanets. Written in Python, the code calculates this log-likelihood penalty in one of seven user-specified cases specified with Boolean input parameters for geometric and/or SNR bias, grazing or non-grazing events, and occultation events.

[ascl:1603.009] Asfgrid: Asteroseismic parameters for a star

asfgrid computes asteroseismic parameters for a star with given stellar parameters and vice versa. Written in Python, it determines delta_nu, nu_max or masses via interpolation over a grid.

[ascl:1603.008] ROBAST: ROOT-based ray-tracing library for cosmic-ray telescopes

ROBAST (ROOT-based simulator for ray tracing) is a non-sequential ray-tracing simulation library developed for wide use in optical simulations of gamma-ray and cosmic-ray telescopes. The library is written in C++ and fully utilizes the geometry library of the ROOT analysis framework, and can build the complex optics geometries typically used in cosmic ray experiments and ground-based gamma-ray telescopes.

[ascl:1603.007] SMARTIES: Spheroids Modelled Accurately with a Robust T-matrix Implementation for Electromagnetic Scattering

SMARTIES calculates the optical properties of oblate and prolate spheroidal particles, with comparable capabilities and ease-of-use as Mie theory for spheres. This suite of MATLAB codes provides a fully documented implementation of an improved T-matrix algorithm for the theoretical modelling of electromagnetic scattering by particles of spheroidal shape. Included are scripts that cover a range of scattering problems relevant to nanophotonics and plasmonics, including calculation of far-field scattering and absorption cross-sections for fixed incidence orientation, orientation-averaged cross-sections and scattering matrix, surface-field calculations as well as near-fields, wavelength-dependent near-field and far-field properties, and access to lower-level functions implementing the T-matrix calculations, including the T-matrix elements which may be calculated more accurately than with competing codes.

[ascl:1603.006] FAST-PT: Convolution integrals in cosmological perturbation theory calculator

FAST-PT calculates 1-loop corrections to the matter power spectrum in cosmology. The code utilizes Fourier methods combined with analytic expressions to reduce the computation time down to scale as N log N, where N is the number of grid point in the input linear power spectrum. FAST-PT is extremely fast, enabling mode-coupling integral computations fast enough to embed in Monte Carlo Markov Chain parameter estimation.

[ascl:1603.005] EQUIB: Atomic level populations and line emissivities calculator

The Fortran program EQUIB solves the statistical equilibrium equation for each ion and yields atomic level populations and line emissivities for given physical conditions, namely electron temperature and electron density, appropriate to the zones in an ionized nebula where the ions are expected to exist.

[ascl:1603.004] gPhoton: Time-tagged GALEX photon events analysis tools

Written in Python, gPhoton calibrates and sky-projects the ~1.1 trillion ultraviolet photon events detected by the microchannel plates on the Galaxy Evolution Explorer Spacecraft (GALEX), archives these events in a publicly accessible database at the Mikulski Archive for Space Telescopes (MAST), and provides tools for working with the database to extract scientific results, particularly over short time domains. The software includes a re-implementation of core functionality of the GALEX mission calibration pipeline to produce photon list files from raw spacecraft data as well as a suite of command line tools to generate calibrated light curves, images, and movies from the MAST database.

[ascl:1603.003] VIP: Vortex Image Processing pipeline for high-contrast direct imaging of exoplanets

VIP (Vortex Image Processing pipeline) provides pre- and post-processing algorithms for high-contrast direct imaging of exoplanets. Written in Python, VIP provides a very flexible framework for data exploration and image processing and supports high-contrast imaging observational techniques, including angular, reference-star and multi-spectral differential imaging. Several post-processing algorithms for PSF subtraction based on principal component analysis are available as well as the LLSG (Local Low-rank plus Sparse plus Gaussian-noise decomposition) algorithm for angular differential imaging. VIP also implements the negative fake companion technique coupled with MCMC sampling for rigorous estimation of the flux and position of potential companions.

[ascl:1603.002] CORBITS: Efficient Geometric Probabilities of Multi-Transiting Exoplanetary Systems

CORBITS (Computed Occurrence of Revolving Bodies for the Investigation of Transiting Systems) computes the probability that any particular group of exoplanets can be observed to transit from a collection of conjectured exoplanets orbiting a star. The efficient, semi-analytical code computes the areas bounded by circular curves on the surface of a sphere by applying elementary differential geometry. CORBITS is faster than previous algorithms, based on comparisons with Monte Carlo simulations, and tests show that it is extremely accurate even for highly eccentric planets.

[ascl:1603.001] SILSS: SPHERE/IRDIS Long-Slit Spectroscopy pipeline

The ESO's VLT/SPHERE instrument includes a unique long-slit spectroscopy (LSS) mode coupled with Lyot coronagraphy in its infrared dual-band imager and spectrograph (IRDIS) for spectral characterization of young, giant exoplanets detected by direct imaging. The SILSS pipeline is a combination of the official SPHERE pipeline and additional custom IDL routines developed within the SPHERE consortium for the speckle subtraction and spectral extraction of a companion's spectrum; it offers a complete end-to-end pipeline, from raw data (science+calibrations) to a final spectrum of the companion. SILSS works on both the low-resolution (LRS) and medium-resolution (MRS) data, and allows correction for some of the known biases of the instrument. Documentation is included in the header of the main routine of the pipeline.

[ascl:1602.021] COLAcode: COmoving Lagrangian Acceleration code

COLAcode is a serial particle mesh-based N-body code illustrating the COLA (COmoving Lagrangian Acceleration) method; it solves for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). It differs from standard N-body code by trading accuracy at small-scales to gain computational speed without sacrificing accuracy at large scales. This is useful for generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing; such catalogs are needed to perform detailed error analysis for ongoing and future surveys of LSS.

[ascl:1602.020] mbb_emcee: Modified Blackbody MCMC

Mbb_emcee fits modified blackbodies to photometry data using an affine invariant MCMC. It has large number of options which, for example, allow computation of the IR luminosity or dustmass as part of the fit. Carrying out a fit produces a HDF5 output file containing the results, which can either be read directly, or read back into a mbb_results object for analysis. Upper and lower limits can be imposed as well as Gaussian priors on the model parameters. These additions are useful for analyzing poorly constrained data. In addition to standard Python packages scipy, numpy, and cython, mbb_emcee requires emcee (ascl:1303.002), Astropy (ascl:1304.002), h5py, and for unit tests, nose.

[ascl:1602.019] CLOC: Cluster Luminosity Order-Statistic Code

CLOC computes cluster order statistics, i.e. the luminosity distribution of the Nth most luminous cluster in a population. It is flexible and requires few assumptions, allowing for parametrized variations in the initial cluster mass function and its upper and lower cutoffs, variations in the cluster age distribution, stellar evolution and dust extinction, as well as observational uncertainties in both the properties of star clusters and their underlying host galaxies. It uses Markov chain Monte Carlo methods to search parameter space to find best-fitting values for the parameters describing cluster formation and disruption, and to obtain rigorous confidence intervals on the inferred values.

[ascl:1602.018] POPPY: Physical Optics Propagation in PYthon

POPPY (Physical Optics Propagation in PYthon) simulates physical optical propagation including diffraction. It implements a flexible framework for modeling Fraunhofer and Fresnel diffraction and point spread function formation, particularly in the context of astronomical telescopes. POPPY provides the optical modeling framework for WebbPSF (ascl:1504.007) and was developed as part of a simulation package for JWST, but is available separately and is broadly applicable to many kinds of imaging simulations.

[ascl:1602.017] CHIP: Caltech High-res IRS Pipeline

CHIP (Caltech High-res IRS Pipeline) reduces high signal-to-noise short-high and long-high Spitzer-IRS spectra, especially that taken with dedicated background exposures. Written in IDL, it is independent of other Spitzer reduction tools except IRSFRINGE (ascl:1602.016).

[ascl:1602.016] IRSFRINGE: Interactive tool for fringe removal from Spitzer IRS spectra

IRSFRINGE is an IDL-based GUI package that allows observers to interactively remove fringes from IRS spectra. Fringes that originate from the detector subtrates are observed in the IRS Short-High (SH) and Long-High (LH) modules. In the Long-Low (LL) module, another fringe component is seen as a result of the pre-launch change in one of the LL filters. The fringes in the Short-Low (SL) module are not spectrally resolved. the fringes are already largely removed in the pipeline processing when the flat field is applied. However, this correction is not perfect and remaining fringes can be removed with IRSFRINGE from data in each module. IRSFRINGE is available as a stand-alone package and is also part of the Spectroscopic Modeling, Analysis and Reduction Tool (SMART, ascl:1210.021).

[ascl:1602.015] GANDALF: Graphical Astrophysics code for N-body Dynamics And Lagrangian Fluids

GANDALF, a successor to SEREN (ascl:1102.010), is a hybrid self-gravitating fluid dynamics and collisional N-body code primarily designed for investigating star formation and planet formation problems. GANDALF uses various implementations of Smoothed Particle Hydrodynamics (SPH) to perform hydrodynamical simulations of gas clouds undergoing gravitational collapse to form new stars (or other objects), and can perform simulations of pure N-body dynamics using high accuracy N-body integrators, model the intermediate phase of cluster evolution, and provide visualizations via its python interface as well as interactive simulations. Although based on many of the SEREN routines, GANDALF has been largely re-written from scratch in C++ using more optimal algorithms and data structures.

[ascl:1602.014] k2photometry: Read, reduce and detrend K2 photometry

k2photometry reads, reduces and detrends K2 photometry and searches for transiting planets. MAST database pixel files are used as input; the output includes raw lightcurves, detrended lightcurves and a transit search can be performed as well. Stellar variability is not typically well-preserved but parameters can be tweaked to change that. The BLS algorithm used to detect periodic events is a Python implementation by Ruth Angus and Dan Foreman-Mackey (https://github.com/dfm/python-bls).

[ascl:1602.013] TailZ: Redshift distributions estimator of photometric samples of galaxies

TailZ estimates redshift distributions of photometric samples of galaxies selected photometrically given a subsample with measured spectroscopic redshifts. The approach uses a non-parametric Voronoi tessellation density estimator to interpolate the galaxy distribution in the redshift and photometric color space. The Voronoi tessellation estimator performs well at reconstructing the tails of the redshift distribution of individual galaxies and gives unbiased estimates of the first and second moments.

[ascl:1602.012] DELightcurveSimulation: Light curve simulation code

DELightcurveSimulation (also called DELCgen) simulates light curves with any given power spectral density and any probability density function, following the algorithm described in Emmanoulopoulos et al. (2013). The simulated products have exactly the same variability and statistical properties as the observed light curves. The code is a Python implementation of the Mathematica code provided by Emmanoulopoulos et al.

[ascl:1602.011] Celestial: Common astronomical conversion routines and functions

The R package Celestial contains common astronomy conversion routines, particularly the HMS and degrees schemes, and a large range of functions for calculating properties of different cosmologies (as used by the cosmocalc website). This includes distances, ages, growth rate/factor and densities (e.g., Omega evolution and critical energy density). It also includes functions for calculating thermal properties of the CMB and Planck's equations and virial properties of halos in different cosmologies, and standard NFW and weak-lensing formulas and low level orbital routines for calculating Roche properties, Vis-Viva and free-fall times.

[ascl:1602.010] The Cannon: Data-driven method for determining stellar parameters and abundances from stellar spectra

The Cannon is a data-driven method for determining stellar labels (physical parameters and chemical abundances) from stellar spectra in the context of vast spectroscopic surveys. It fits for the spectral model given training spectra and labels, with the polynomial order for the spectral model decided by the user, infers labels for the test spectra, and provides diagnostic output for monitoring and evaluating the process. It offers SNR-independent continuum normalization, performs well at lower signal-to-noise, and is very accurate.

[ascl:1602.009] LensTools: Weak Lensing computing tools

LensTools implements a wide range of routines frequently used in Weak Gravitational Lensing, including tools for image analysis, statistical processing and numerical theory predictions. The package offers many useful features, including complete flexibility and easy customization of input/output formats; efficient measurements of power spectrum, PDF, Minkowski functionals and peak counts of convergence maps; survey masks; artificial noise generation engines; easy to compute parameter statistical inferences; ray tracing simulations; and many others. It requires standard numpy and scipy, and depending on tools used, may require Astropy (ascl:1304.002), emcee (ascl:1303.002), matplotlib, and mpi4py.

[ascl:1602.008] NuCraft: Oscillation probabilities for atmospheric neutrinos calculator

NuCraft calculates oscillation probabilities for atmospheric neutrinos, taking into account matter effects and the Earth's atmosphere, and supports an arbitrary number of sterile neutrino flavors with easily configurable continuous Earth models. Continuous modeling of the Earth instead of the often-used approximation of four layers with constant density and consideration of the smearing of baseline lengths due to the variable neutrino production heights in Earth's atmosphere each lead to deviations of 10% or more for conventional neutrinos between 1 and 10 GeV.

[ascl:1602.007] FilTER: Filament Trait-Evaluated Reconstruction

FilTER (Filament Trait-Evaluated Reconstruction) post-processes output from DisPerSE (ascl:1302.015 ) to produce a set of filaments that are well-defined and have measured properties (e.g. width), then cuts the profiles, fits and assesses them to reconstruct new filaments according to defined criteria.

[ascl:1602.006] LIRA: LInear Regression in Astronomy

LIRA (LInear Regression in Astronomy) performs Bayesian linear regression that accounts for heteroscedastic errors in both the independent and the dependent variables, intrinsic scatters (in both variables), time evolution of slopes, normalization and scatters, Malmquist and Eddington bias, and break of linearity. The posterior distribution of the regression parameters is sampled with a Gibbs method exploiting the JAGS (ascl:1209.002) library.

[ascl:1602.005] LRGS: Linear Regression by Gibbs Sampling

LRGS (Linear Regression by Gibbs Sampling) implements a Gibbs sampler to solve the problem of multivariate linear regression with uncertainties in all measured quantities and intrinsic scatter. LRGS extends an algorithm by Kelly (2007) that used Gibbs sampling for performing linear regression in fairly general cases in two ways: generalizing the procedure for multiple response variables, and modeling the prior distribution of covariates using a Dirichlet process.

[ascl:1602.004] DUSTYWAVE: Linear waves in gas and dust

Written in Fortran, DUSTYWAVE computes the exact solution for linear waves in a two-fluid mixture of gas and dust. The solutions are general with respect to both the dust-to-gas ratio and the amplitude of the drag coefficient.

[ascl:1602.003] ZAP: Zurich Atmosphere Purge

ZAP (Zurich Atmosphere Purge) provides sky subtraction for integral field spectroscopy; its approach is based on principal component analysis (PCA) developed for the Multi Unit Spectrographic Explorer (MUSE) integral field spectrograph. ZAP employs filtering and data segmentation to enhance the inherent capabilities of PCA for sky subtraction. ZAP reduces sky emission residuals while robustly preserving the flux and line shapes of astronomical sources; this method works in a variety of observational situations from sparse fields with a low density of sources to filled fields in which the target source fills the field of view. With the inclusion of both of these situations the method is generally applicable to many different science cases and should also be useful for other instrumentation.

[ascl:1602.002] pyraf-dbsp: Reduction pipeline for the Palomar Double Beam Spectrograph

pyraf-dbsp is a PyRAF-based (ascl:1207.011) reduction pipeline for optical spectra taken with the Palomar 200-inch Double Beam Spectrograph. The pipeline provides a simplified interface for basic reduction of single-object spectra with minimal overhead. It is suitable for quicklook classification of transients as well as moderate-precision (few km/s) radial velocity work.

[ascl:1602.001] Automark: Automatic marking of marked Poisson process in astronomical high-dimensional datasets

Automark models photon counts collected form observation of variable-intensity astronomical sources. It aims to mark the abrupt changes in the corresponding wavelength distribution of the emission automatically. In the underlying methodology, change points are embedded into a marked Poisson process, where photon wavelengths are regarded as marks and both the Poisson intensity parameter and the distribution of the marks are allowed to change.

[ascl:1601.021] ISO: Isochrone construction

ISO transforms MESA history files into a uniform basis for interpolation and then constructs new stellar evolution tracks and isochrones from that basis. It is written in Fortran and requires MESA (ascl:1010.083), primarily for interpolation. Though designed to ingest MESA star history files, tracks from other stellar evolution codes can be incorporated by loading the tracks into the data structures used in the codes.

[ascl:1601.020] ProC: Process Coordinator

ProC (short for Process Coordinator) is a versatile workflow engine that allows the user to build, run and manage workflows with just a few clicks. It automatically documents every processing step, making every modification to data reproducible. ProC provides a graphical user interface for constructing complex data processing workflows out of a given set of computer programs. The user can, for example, specify that only data products which are affected by a change in the input data are updated selectively, avoiding unnecessary computations. The ProC suite is flexible and satisfies basic needs of data processing centers that have to be able to restructure their data processing along with the development of a project.

[ascl:1601.019] WzBinned: Binned and uncorrelated estimates of dark energy EOS extractor

WzBinned extracts binned and uncorrelated estimates of dark energy equation of state w(z) using Type Ia supernovae Hubble diagram and other cosmological probes and priors. It can handle an arbitrary number of input distance modulus data (entered as an input file SNdata.dat) and various existing cosmological information.

[ascl:1601.018] MATPHOT: Stellar photometry and astrometry with discrete point spread functions

A discrete Point Spread Function (PSF) is a sampled version of a continuous two-dimensional PSF. The shape information about the photon scattering pattern of a discrete PSF is typically encoded using a numerical table (matrix) or a FITS image file. MATPHOT shifts discrete PSFs within an observational model using a 21-pixel- wide damped sinc function and position partial derivatives are computed using a five-point numerical differentiation formula. MATPHOT achieves accurate and precise stellar photometry and astrometry of undersampled CCD observations by using supersampled discrete PSFs that are sampled two, three, or more times more finely than the observational data.

[ascl:1601.017] BASCS: Bayesian Separation of Close Sources

BASCS models spatial and spectral information from overlapping sources and the background, and jointly estimates all individual source parameters. The use of spectral information improves the detection of both faint and closely overlapping sources and increases the accuracy with which source parameters are inferred.

[ascl:1601.016] Fit Kinematic PA: Fit the global kinematic position-angle of galaxies

Fit kinematic PA measures the global kinematic position-angle (PA) from integral field observations of a galaxy stellar or gas kinematics; the code is available in IDL and Python.

[ascl:1601.015] QDPHOT: Quick & Dirty PHOTometry

QDPHOT is a fast CCD stellar photometry task which quickly produces CCD stellar photometry from two CCD images of a star field. It was designed to be a data mining tool for finding high-quality stellar observations in the data archives of the National Virtual Observatory. QDPHOT typically takes just a few seconds to analyze two Hubble Space Telescope WFPC2 observations of Local Group star clusters. It is also suitable for real-time data-quality analysis of CCD observations; on-the-fly instrumental color-magnitude diagrams can be produced at the telescope console during the few seconds between CCD readouts.

[ascl:1601.014] Nulike: Neutrino telescope likelihood tools

Nulike is software for including full event-level information in likelihood calculations for neutrino telescope searches for dark matter annihilation. It includes both angular and spectral information about neutrino events as well as their total number, and can be used for single models without reference to the rest of a parameter space.

[ascl:1601.013] ImpactModel: Black Hole Accretion Disk Impact Model

ImpactModel, written in Cython, computes the accretion disc impact spectrum at given frequencies and can compute other model quantities as a function of time.

[ascl:1601.012] SavGolFilterCov: Savitzky Golay filter for data with error covariance

A Savitzky–Golay filter is often applied to data to smooth the data without greatly distorting the signal; however, almost all data inherently comes with noise, and the noise properties can differ from point to point. This python script improves upon the traditional Savitzky-Golay filter by accounting for error covariance in the data. The inputs and arguments are modeled after scipy.signal.savgol_filter.

[ascl:1601.011] LACEwING: LocAting Constituent mEmbers In Nearby Groups

LACEwING (LocAting Constituent mEmbers In Nearby Groups) uses the kinematics (positions and motions) of stars to determine if they are members of one of 10 nearby young moving groups or 4 nearby open clusters within 100 parsecs. It is written for Python 2.7 and depends upon Numpy, Scipy, and Astropy (ascl:1304.002) modules. LACEwING can be used as a stand-alone code or as a module in other code. Additional python programs are present in the repository for the purpose of recalibrating the code and producing other analyses, including a traceback analysis.

[ascl:1601.010] PARAVT: Parallel Voronoi Tessellation

PARAVT offers massive parallel computation of Voronoi tessellations (VT hereafter) in large data sets. The code is focused for astrophysical purposes where VT densities and neighbors are widely used. There are several serial Voronoi tessellation codes, however no open source and parallel implementations are available to handle the large number of particles/galaxies in current N-body simulations and sky surveys. Parallelization is implemented under MPI and VT using Qhull library. Domain decomposition take into account consistent boundary computation between tasks, and support periodic conditions. In addition, the code compute neighbors lists, Voronoi density and Voronoi cell volumes for each particle, and can compute density on a regular grid.

[ascl:1601.009] K2fov: Field of view software for NASA's K2 mission

K2fov allows users to transform celestial coordinates into K2's pixel coordinate system for the purpose of preparing target proposals and field of view visualizations. In particular, the package, written in Python, adds the "K2onSilicon" and "K2findCampaigns" tools to the command line, allowing the visibility of targets to be checked in a user-friendly way.

[ascl:1601.008] CosmicPy: Interactive cosmology computations

CosmicPy performs simple and interactive cosmology computations for forecasting cosmological parameters constraints; it computes tomographic and 3D Spherical Fourier-Bessel power spectra as well as Fisher matrices for galaxy clustering. Written in Python, it relies on a fast C++ implementation of Fourier-Bessel related computations, and requires NumPy, SciPy, and Matplotlib.

[ascl:1601.007] LIRA: Low-counts Image Reconstruction and Analysis

LIRA (Low-counts Image Reconstruction and Analysis) deconvolves any unknown sky components, provides a fully Poisson 'goodness-of-fit' for any best-fit model, and quantifies uncertainties on the existence and shape of unknown sky. It does this without resorting to χ2 or rebinning, which can lose high-resolution information. It is written in R and requires the FITSio package.

[ascl:1601.006] SAGE: Semi-Analytic Galaxy Evolution

SAGE (Semi-Analytic Galaxy Evolution) models galaxy formation in a cosmological context. SAGE has been rebuilt to be modular and customizable. The model runs on any dark matter cosmological N-body simulation whose trees are organized in a supported format and contain a minimum set of basic halo properties.

[ascl:1601.005] ctools: Cherenkov Telescope Science Analysis Software

ctools provides tools for the scientific analysis of Cherenkov Telescope Array (CTA) data. Analysis of data from existing Imaging Air Cherenkov Telescopes (such as H.E.S.S., MAGIC or VERITAS) is also supported, provided that the data and response functions are available in the format defined for CTA. ctools comprises a set of ftools-like binary executables with a command-line interface allowing for interactive step-wise data analysis. A Python module allows control of all executables, and the creation of shell or Python scripts and pipelines is supported. ctools provides cscripts, which are Python scripts complementing the binary executables. Extensions of the ctools package by user defined binary executables or Python scripts is supported. ctools are based on GammaLib (ascl:1110.007).

[ascl:1601.004] Odyssey: Ray tracing and radiative transfer in Kerr spacetime

Odyssey is a GPU-based General Relativistic Radiative Transfer (GRRT) code for computing images and/or spectra in Kerr metric describing the spacetime around a rotating black hole. Odyssey is implemented in CUDA C/C++. For flexibility, the namespace structure in C++ is used for different tasks; the two default tasks presented in the source code are the redshift of a Keplerian disk and the image of a Keplerian rotating shell at 340GHz. Odyssey_Edu, an educational software package for visualizing the ray trajectories in the Kerr spacetime that uses Odyssey, is also available.

[ascl:1601.003] SCOUSE: Semi-automated multi-COmponent Universal Spectral-line fitting Engine

The Semi-automated multi-COmponent Universal Spectral-line fitting Engine (SCOUSE) is a spectral line fitting algorithm that fits Gaussian files to spectral line emission. It identifies the spatial area over which to fit the data and generates a grid of spectral averaging areas (SAAs). The spatially averaged spectra are fitted according to user-provided tolerance levels, and the best fit is selected using the Akaike Information Criterion, which weights the chisq of a best-fitting solution according to the number of free-parameters. A more detailed inspection of the spectra can be performed to improve the fit through an iterative process, after which SCOUSE integrates the new solutions into the solution file.

[ascl:1601.002] Hyper-Fit: Fitting routines for multidimensional data with multivariate Gaussian uncertainties

The R package Hyper-Fit fits hyperplanes (hyper.fit) and creates 2D/3D visualizations (hyper.plot2d / hyper.plot3d) to produce robust 1D linear fits for 2D x vs y type data, and robust 2D plane fits to 3D x vs y vs z type data. This hyperplane fitting works generically for any N-1 hyperplane model being fit to a N dimensional dataset. All fits include intrinsic scatter in the generative model orthogonal to the hyperplane. A web interface for online fitting is also available at http://hyperfit.icrar.org.

[ascl:1601.001] TRADES: TRAnsits and Dynamics of Exoplanetary Systems

TRADES (TRAnsits and Dynamics of Exoplanetary Systems) simultaneously fits observed radial velocities and transit times data to determine the orbital parameters of exoplanetary systems from observational data. It uses a dynamical simulator for N-body systems that also fits the available data during the orbital integration and determines the best combination of the orbital parameters using grid search, χ2 minimization, genetic algorithms, particle swarm optimization, and bootstrap analysis.

[submitted] pyreaclib

A python interface to the JINA reaclib nuclear reaction database

[ascl:1512.020] TACT: The Action Computation Tool

The Action Computation Tool (TACT) tests methods for estimating actions, angles and frequencies of orbits in both axisymmetric and triaxial potentials, including general spherical potentials, analytic potentials (Isochrone and Harmonic oscillator), axisymmetric Stackel fudge, average generating function from orbit (AvGF), and others. It is written in C++; code is provided to compile the routines into a Python library. TM (ascl:1512.014) and LAPACK are required to access some features.

[ascl:1512.019] UPSILoN: AUtomated Classification of Periodic Variable Stars using MachIne LearNing

UPSILoN (AUtomated Classification of Periodic Variable Stars using MachIne LearNing) classifies periodic variable stars such as Delta Scuti stars, RR Lyraes, Cepheids, Type II Cepheids, eclipsing binaries, and long-period variables (i.e. superclasses), and their subclasses (e.g. RR Lyrae ab, c, d, and e types) using well-sampled light curves from any astronomical time-series surveys in optical bands regardless of their survey-specific characteristics such as color, magnitude, and sampling rate. UPSILoN consists of two parts, one which extracts variability features from a light curve, and another which classifies a light curve, and returns extracted features, a predicted class, and a class probability. In principle, UPSILoN can classify any light curves having arbitrary number of data points, but using light curves with more than ~80 data points provides the best classification quality.

[ascl:1512.018] growl: Growth factor and growth rate of expanding universes

Growl calculates the linear growth factor Da and its logarithmic derivative dln D/dln a in expanding Friedmann-Robertson-Walker universes with arbitrary matter and vacuum densities. It permits rapid and stable numerical evaluation.

[ascl:1512.017] FFTLog: Fast Fourier or Hankel transform

FFTLog is a set of Fortran subroutines that compute the fast Fourier or Hankel (= Fourier-Bessel) transform of a periodic sequence of logarithmically spaced points. FFTLog can be regarded as a natural analogue to the standard Fast Fourier Transform (FFT), in the sense that, just as the normal FFT gives the exact (to machine precision) Fourier transform of a linearly spaced periodic sequence, so also FFTLog gives the exact Fourier or Hankel transform, of arbitrary order m, of a logarithmically spaced periodic sequence.

[ascl:1512.016] ZeldovichRecon: Halo correlation function using the Zeldovich approximation

ZeldovichRecon computes the halo correlation function using the Zeldovich approximation. It includes 3 variants: 1.) zelrecon.cpp, which computes the various contributions to the correlation function; 2.) zelrecon_ctypes.cpp, which is designed to be called from Python using the ctypes library; and 3.) a version which implements the "ZEFT" formalism of "A Lagrangian effective field theory" [arxiv:1506.05264] including the alpha term described in that paper.

[ascl:1512.015] Spirality: Spiral arm pitch angle measurement

Spirality measures spiral arm pitch angles by fitting galaxy images to spiral templates of known pitch. Written in MATLAB, the code package also includes GenSpiral, which produces FITS images of synthetic spirals, and SpiralArmCount, which uses a one-dimensional Fast Fourier Transform to count the spiral arms of a galaxy after its pitch is determined.

[ascl:1512.014] TM: Torus Mapper

TM (Torus Mapper) produces models for orbits in action-angle coordinates in axisymmetric potentials using torus mapping, a non-perturbative technique for creating orbital tori for specified values of the action integrals. It can compute a star's position at any time given an orbital torus and a star’s position at a reference time, and also provides a way to choose initial conditions for N-body simulations of realistic disc galaxies that start in perfect equilibrium. TM provides some advantages over use of a standard time-stepper to create orbits.

[ascl:1512.013] CounterPoint: Zeeman-split absorption lines

CounterPoint works in concert with MoogStokes (ascl:1308.018). It applies the Zeeman effect to the atomic lines in the region of study, splitting them into the correct number of Zeeman components and adjusting their relative intensities according to the predictions of Quantum Mechanics, and finally creates a Moog-readable line list for use with MoogStokes. CounterPoint has the ability to use VALD and HITRAN line databases for both atomic and molecular lines.

[ascl:1512.012] DiffuseModel: Modeling the diffuse ultraviolet background

DiffuseModel calculates the scattered radiation from dust scattering in the Milky Way based on stars from the Hipparcos catalog. It uses Monte Carlo to implement multiple scattering and assumes a user-supplied grid for the dust distribution. The output is a FITS file with the diffuse light over the Galaxy. It is intended for use in the UV (900 - 3000 A) but may be modified for use in other wavelengths and galaxies.

[ascl:1512.011] ExoData: Open Exoplanet Catalogue exploration and analysis tool

ExoData is a python interface for accessing and exploring the Open Exoplanet Catalogue. It allows searching of planets (including alternate names) and easy navigation of hierarchy, parses spectral types and fills in missing parameters based on programmable specifications, and provides easy reference of planet parameters such as GJ1214b.ra, GJ1214b.T, and GJ1214b.R. It calculates values such as transit duration, can easily rescale units, and can be used as an input catalog for large scale simulation and analysis of planets.

[ascl:1512.010] CubeIndexer: Indexer for regions of interest in data cubes

CubeIndexer indexes regions of interest (ROIs) in data cubes reducing the necessary storage space. The software can process data cubes containing megabytes of data in fractions of a second without human supervision, thus allowing it to be incorporated into a production line for displaying objects in a virtual observatory. The software forms part of the Chilean Virtual Observatory (ChiVO) and provides the capability of content-based searches on data cubes to the astronomical community.

[ascl:1512.009] DRACULA: Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy

DRACULA classifies objects using dimensionality reduction and clustering. The code has an easy interface and can be applied to separate several types of objects. It is based on tools developed in scikit-learn, with some usage requiring also the H2O package.

[ascl:1512.008] Bisous model: Detecting filamentary pattern in point processes

The Bisous model is a marked point process that models multi-dimensional patterns. The Bisous filament finder works directly with galaxy distribution data and the model intrinsically takes into account the connectivity of the filamentary network. The Bisous model generates the visit map (the probability to find a filament at a given point) together with the filament orientation field; these two fields are used to extract filament spines from the data.

[ascl:1512.007] AstroBlend: Visualization package for use with Blender

AstroBlend is a visualization package for use in the three dimensional animation and modeling software, Blender. It reads data in via a text file or can use pre-fab isosurface files stored as OBJ or Wavefront files. AstroBlend supports a variety of codes such as FLASH (ascl:1010.082), Enzo (ascl:1010.072), and Athena (ascl:1010.014), and combines artistic 3D models with computational astrophysics datasets to create models and animations.

[ascl:1512.006] GPC: General Polygon Clipper library

The University of Manchester GPC library is a flexible and highly robust polygon set operations library for use with C, C#, Delphi, Java, Perl, Python, Haskell, Lua, VB.Net and other applications. It supports difference, intersection, exclusive-or and union clip operations, and polygons may be comprised of multiple disjoint contours. Contour vertices may be given in any order - clockwise or anticlockwise, and contours may be convex, concave or self-intersecting, and may be nested (i.e. polygons may have holes). Output may take the form of either polygon contours or tristrips, and hole and external contours are differentiated in the result. GPC is free for non-profit and educational use; a Commercial Use License is required for commercial use.

Internet Archive link provided for archival purposes; per its website, GPC is no longer distributed or available as of August 2020.

[ascl:1512.005] ALFA: Automated Line Fitting Algorithm

ALFA fits emission line spectra of arbitrary wavelength coverage and resolution, fully automatically. It uses a catalog of lines which may be present to construct synthetic spectra, the parameters of which are then optimized by means of a genetic algorithm. Uncertainties are estimated using the noise structure of the residuals. An emission line spectrum containing several hundred lines can be fitted in a few seconds using a single processor of a typical contemporary desktop or laptop PC. Data cubes in FITS format can be analysed using multiple processors, and an analysis of tens of thousands of deep spectra obtained with instruments such as MUSE will take a few hours.

[ascl:1512.004] EDRSX: Extensions to the EDRS package

EDRSX extends the Electronography Data Reduction System (EDRS, ascl:1512.0030). It makes more versatile analysis of IRAS images than was otherwise available possible. EDRSX provides facilities for converting images into and out of EDRS format, accesses RA and DEC information stored with IRAS images, and performs several standard image processing operations such as displaying image histograms and statistics, and Fourier transforms. This enables such operations to be performed as estimation and subtraction of non-linear backgrounds, de-striping of IRAS images, modelling of image features, and easy aligning of separate images, among others.

[ascl:1512.003] EDRS: Electronography Data Reduction System

The Electronography Data Reduction System (EDRS) reduces and analyzes large format astronomical images and was written to be used from within ASPIC (ascl:1510.006). In its original form it specialized in the reduction of electronographic data but was built around a set of utility programs which were widely applicable to astronomical images from other sources. The programs align and calibrate images, handle lists of (X,Y) positions, apply linear geometrical transformations and do some stellar photometry. This package is now obsolete.

[ascl:1512.002] GetData: A filesystem-based, column-oriented database format for time-ordered binary data

The GetData Project is the reference implementation of the Dirfile Standards, a filesystem-based, column-oriented database format for time-ordered binary data. Dirfiles provide a fast, simple format for storing and reading data, suitable for both quicklook and analysis pipelines. GetData provides a C API and bindings exist for various other languages. GetData is distributed under the terms of the GNU Lesser General Public License.

[ascl:1512.001] IRACpm: Distortion correction for IRAC astrometric data

The IRACpm R package applies a 7-8 order distortion correction to IRAC astrometric data from the Spitzer Space Telescope and includes a function for measuring apparent proper motions between different Epochs. These corrections are applicable only to positions measured by APEX; cryogenic images benefit from a correction for varying intra-pixel sensitivity prior to the application of the distortion.

[ascl:1511.023] PromptNuFlux: Prompt atmospheric neutrino flux calculator

PromptNuFlux computes the prompt atmospheric neutrino flux E3Φ(GeV2/(cm2ssr)), including the total associated theory uncertainty, for a range of energies between E=103 GeV and E=107.5 GeV. Results are available for five different parametrizations of the input cosmic ray flux: BPL, H3P, H3A, H14a, H14b.

[ascl:1511.022] ZInCo: Zoomed Initial Conditions

ZInCo manipulates existing initial conditions (ICs) compatible with GADGET-2/3 (ascl:0003.001) ICs, allowing different flavors of zoom-in simulations rather then producing new ICs from scratch. The code can manipulate initial conditions with multiple types of particles, unlike the vast majority of zoom-in ICs codes available, preserving their properties and random field. This allows ZInCo to take advantage of other codes that produce ICs featuring a broad range of different cosmologies; it can be used also on existing ICs even in the unlikely case nothing is known about their properties. The code is written in C++ and parallelized using MPI.

[ascl:1511.021] EPIC: E-field Parallel Imaging Correlator

E-field Parallel Imaging Correlator (EPIC), a highly parallelized Object Oriented Python package, implements the Modular Optimal Frequency Fourier (MOFF) imaging technique. It also includes visibility-based imaging using the software holography technique and a simulator for generating electric fields from a sky model. EPIC can accept dual-polarization inputs and produce images of all four instrumental cross-polarizations.

[ascl:1511.020] Mercury-T: Tidally evolving multi-planet systems code

Mercury-T calculates the evolution of semi-major axis, eccentricity, inclination, rotation period and obliquity of the planets as well as the rotation period evolution of the host body; it is based on the N-body code Mercury (Chambers 1999, ascl:1201.008). It is flexible, allowing computation of the tidal evolution of systems orbiting any non-evolving object (if its mass, radius, dissipation factor and rotation period are known), but also evolving brown dwarfs (BDs) of mass between 0.01 and 0.08 M⊙, an evolving M-dwarf of 0.1 M⊙, an evolving Sun-like star, and an evolving Jupiter.

[ascl:1511.019] CosmoBolognaLib: Open source C++ libraries for cosmological calculations

CosmoBolognaLib contains numerical libraries for cosmological calculations; written in C++, it is intended to define a common numerical environment for cosmological investigations of the large-scale structure of the Universe. The software aids in handling real and simulated astronomical catalogs by measuring one-point, two-point and three-point statistics in configuration space and performing cosmological analyses. These open source libraries can be included in either C++ or Python codes.

[ascl:1511.018] LDC3: Three-parameter limb darkening coefficient sampling

LDC3 samples physically permissible limb darkening coefficients for the Sing et al. (2009) three-parameter law. It defines the physically permissible intensity profile as being everywhere-positive, monotonically decreasing from center to limb and having a curl at the limb. The approximate sampling method is analytic and thus very fast, reproducing physically permissible samples in 97.3% of random draws (high validity) and encompassing 94.4% of the physically permissible parameter volume (high completeness).

[ascl:1511.017] DES exposure checker: Dark Energy Survey image quality control crowdsourcer

DES exposure checker renders science-grade images directly to a web browser and allows users to mark problematic features from a set of predefined classes, thus allowing image quality control for the Dark Energy Survey to be crowdsourced through its web application. Users can also generate custom labels to help identify previously unknown problem classes; generated reports are fed back to hardware and software experts to help mitigate and eliminate recognized issues. These problem reports allow rapid correction of artifacts that otherwise may be too subtle or infrequent to be recognized.

[ascl:1511.016] JKTLD: Limb darkening coefficients

JKTLD outputs theoretically-calculated limb darkening (LD) strengths for equations (LD laws) which predict the amount of LD as a function of the part of the star being observed. The coefficients of these laws are obtained by bilinear interpolation (in effective temperature and surface gravity) in published tables of coefficients calculated from stellar model atmospheres by several researchers. Many observations of stars require the strength of limb darkening (LD) to be estimated, which can be done using theoretical models of stellar atmospheres; JKTLD can help in these circumstances.

[ascl:1511.015] George: Gaussian Process regression

George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.

[ascl:1511.014] HumVI: Human Viewable Image creation

HumVI creates a composite color image from sets of input FITS files, following the Lupton et al (2004, ascl:1511.013) composition algorithm. Written in Python, it takes three FITS files as input and returns a color composite, color-saturated png image with an arcsinh stretch. HumVI reads the zero points out of the FITS headers and uses them to put all the images on the same flux scale; photometrically calibrated images produce the best results.

[ascl:1511.013] CCDtoRGB: RGB image production from three-band astronomical images

CCDtoRGB produces red‐green‐blue (RGB) composites from three‐band astronomical images, ensuring an object with a specified astronomical color has a unique color in the RGB image rather than burnt‐out white stars. Use of an arcsinh stretch shows faint objects while simultaneously preserving the structure of brighter objects in the field, such as the spiral arms of large galaxies.

[ascl:1511.012] milkywayproject_triggering: Correlation functions for two catalog datasets

This triggering code calculates the correlation function between two astrophysical data catalogs using the Landy-Szalay approximator generalized for heterogeneous datasets (Landy & Szalay, 1993; Bradshaw et al, 2011) or the auto-correlation function of one dataset. It assumes that one catalog has positional information as well as an object size (effective radius), and the other only positional information.

[ascl:1511.011] SparsePZ: Sparse Representation of Photometric Redshift PDFs

SparsePZ uses sparse basis representation to fully represent individual photometric redshift probability density functions (PDFs). This approach requires approximately half the parameters for the same multi-Gaussian fitting accuracy, and has the additional advantage that an entire PDF can be stored by using a 4-byte integer per basis function. Only 10-20 points per galaxy are needed to reconstruct both the individual PDFs and the ensemble redshift distribution, N(z), to an accuracy of 99.9 per cent when compared to the one built using the original PDFs computed with a resolution of δz = 0.01, reducing the required storage of 200 original values by a factor of 10-20. This basis representation can be directly extended to a cosmological analysis, thereby increasing computational performance without losing resolution or accuracy.

[ascl:1511.010] Galileon-Solver: N-body code

Galileon-Solver adds an extra force to PMCode (ascl:9909.001) using a modified Poisson equation to provide a non-linearly transformed density field, with the operations all performed in real space. The code's implicit spherical top-hat assumption only works over fairly long distance averaging scales, where the coarse-grained picture it relies on is a good approximation of reality; it uses discrete Fourier transforms and cyclic reduction in the usual way.

[ascl:1511.009] Pangloss: Reconstructing lensing mass

Pangloss reconstructs all the mass within a light cone through the Universe. Understanding complex mass distributions like this is important for accurate time delay lens cosmography, and also for accurate lens magnification estimation. It aspires to use all available data in an attempt to make the best of all mass maps.

[ascl:1511.008] MCAL: M dwarf metallicity and temperature calculator

MCAL calculates high precision metallicities and effective temperatures for M dwarfs; the method behaves properly down to R = 40 000 and S/N = 25, and results were validated against a sample of stars in common with SOPHIE high resolution spectra.

[ascl:1511.007] MHF: MLAPM Halo Finder

MHF is a Dark Matter halo finder that is based on the refinement grids of MLAPM. The grid structure of MLAPM adaptively refines around high-density regions with an automated refinement algorithm, thus naturally "surrounding" the Dark Matter halos, as they are simply manifestations of over-densities within (and exterior) to the underlying host halo. Using this grid structure, MHF restructures the hierarchy of nested isolated MLAPM grids into a "grid tree". The densest cell in the end of a tree branch marks center of a prospective Dark Matter halo. All gravitationally bound particles about this center are collected to obtain the final halo catalog. MHF automatically finds halos within halos within halos.

[ascl:1511.006] T-Matrix: Codes for Computing Electromagnetic Scattering by Nonspherical and Aggregated Particles

The T-Matrix package includes codes to compute electromagnetic scattering by homogeneous, rotationally symmetric nonspherical particles in fixed and random orientations, randomly oriented two-sphere clusters with touching or separated components, and multi-sphere clusters in fixed and random orientations. All codes are written in Fortran-77. LAPACK-based, extended-precision, Gauss-elimination- and NAG-based, and superposition codes are available, as are double-precision superposition, parallelized double-precision, double-precision Lorenz-Mie codes, and codes for the computation of the coefficients for the generalized Chebyshev shape.

[ascl:1511.005] pyhrs: Spectroscopic data reduction package for SALT

The pyhrs package reduces data from the High Resolution Spectrograph (HRS) on the Southern African Large Telescope (SALT). HRS is a dual-beam, fiber fed echelle spectrectrograph with four modes of operation: low (R~16000), medium (R~34000), high (R~65000), and high stability (R~65000). pyhrs, written in Python, includes all of the steps necessary to reduce HRS low, medium, and high resolution data; this includes basic CCD reductions, order identification, wavelength calibration, and extraction of the spectra.

[ascl:1511.004] Xgremlin: Interferograms and spectra from Fourier transform spectrometers analysis

Xgremlin is a hardware and operating system independent version of the data analysis program Gremlin used for Fourier transform spectrometry. Xgremlin runs on PCs and workstations that use the X11 window system, including cygwin in Windows. It is used to Fourier transform interferograms, plot spectra, perform phase corrections, perform intensity and wavenumber calibration, and find and fit spectral lines. It can also be used to construct synthetic spectra, subtract continua, compare several different spectra, and eliminate ringing around lines.

[ascl:1511.003] SkyView Virtual Telescope

The SkyView Virtual telescope provides access to survey datasets ranging from radio through the gamma-ray regimes. Over 100 survey datasets are currently available. The SkyView library referenced here is used as the basis for the SkyView web site (at http://skvyiew.gsfc.nasa.gov) but is designed for individual use by researchers as well.

SkyView's approach to access surveys is distinct from most other toolkits. Rather than providing links to the original data, SkyView attempts to immediately re-render the source data in the user-requested reference frame, projection, scaling, orientation, etc. The library includes a set of geometry transformation and mosaicking tools that may be integrated into other applications independent of SkyView.

[ascl:1511.002] JSPAM: Interacting galaxies modeller

JSPAM models galaxy collisions using a restricted n-body approach to speed up computation. Instead of using a softened point-mass potential, the software supports a modified version of the three component potential created by Hernquist (1994, ApJS 86, 389). Although spherically symmetric gravitationally potentials and a Gaussian model for the bulge are used to increase computational efficiency, the potential mimics that of a fully consistent n-body model of a galaxy. Dynamical friction has been implemented in the code to improve the accuracy of close approaches between galaxies. Simulations using this code using thousands of particles over the typical interaction times of a galaxy interaction take a few seconds on modern desktop workstations, making it ideal for rapidly prototyping the dynamics of colliding galaxies. Extensive testing of the code has shown that it produces nearly identical tidal features to those from hierarchical tree codes such as Gadget but using a fraction of the computational resources. This code was used in the Galaxy Zoo: Mergers project and is very well suited for automated fitting of galaxy mergers with automated pattern fitting approaches such as genetic algorithms. Java and Fortran versions of the code are available.

[ascl:1511.001] SuperFreq: Numerical determination of fundamental frequencies of an orbit

SuperFreq numerically estimates the fundamental frequencies and orbital actions of pre-computed orbital time series. It is an implementation of a version of the Numerical Analysis of Fundamental Frequencies close to that by Monica Valluri, which itself is an implementation of an algorithm first used by Jacques Laskar.

[ascl:1510.007] ccdproc: CCD data reduction software

Ccdproc is an affiliated package for the AstroPy package for basic data reductions of CCD images. The ccdproc package provides many of the necessary tools for processing of ccd images built on a framework to provide error propagation and bad pixel tracking throughout the reduction process.

[submitted] Xsmurf - Measuring multifractal properties with the continuous wavelet transform modulus maxima (WTMM) method

Xsmurf is a software package written in C/Tcl/Tk that implements the continuous wavelet transform modulus maxima method, an image processing tool for measuring fractal and multifractal properties in experimental and simulation data.
Multifractal analysis is described in the following page: http://www.scholarpedia.org/article/Wavelet-based_multifractal_analysis

Xsmurf has been used in multiple applications in astrophysics, e.g. :
- analysis of solar magnetograms for characterizing complexity of evolving regions
- fractal/multifractal nature and anisotropic structure of Galactic atomic hydrogen (H I)
- analysis of simulation data (velocity field, ...) of turbulent flow

[ascl:1510.006] ASPIC: STARLINK image processing package

ASPIC handled basic astronomical image processing. Early releases concentrated on image arithmetic, standard filters, expansion/contraction/selection/combination of images, and displaying and manipulating images on the ARGS and other devices. Later releases added new astronomy-specific applications to this sound framework. The ASPIC collection of about 400 image-processing programs was written using the Starlink "interim" environment in the 1980; the software is now obsolete.

[ascl:1510.005] GALFORM: Galactic modeling

GALFORM is a semi-analytic model for calculating the formation and evolution of galaxies in hierarchical clustering cosmologies. Using a Monte Carlo algorithm to follow the merging evolution of dark matter haloes with arbitrary mass resolution, it incorporates realistic descriptions of the density profiles of dark matter haloes and the gas they contain. It follows the chemical evolution of gas and stars, and the associated production of dust and includes a detailed calculation of the sizes of discs and spheroids.

[ascl:1510.004] DEBiL: Detached Eclipsing Binary Light curve fitter

DEBiL rapidly fits a large number of light curves to a simple model. It is the central component of a pipeline for systematically identifying and analyzing eclipsing binaries within a large dataset of light curves; the results of DEBiL can be used to flag light curves of interest for follow-up analysis.

[ascl:1510.003] PyLDTk: Python toolkit for calculating stellar limb darkening profiles and model-specific coefficients for arbitrary filters

PyLDTk automates the calculation of custom stellar limb darkening (LD) profiles and model-specific limb darkening coefficients (LDC) using the library of PHOENIX-generated specific intensity spectra by Husser et al. (2013). It facilitates exoplanet transit light curve modeling, especially transmission spectroscopy where the modeling is carried out for custom narrow passbands. PyLDTk construct model-specific priors on the limb darkening coefficients prior to the transit light curve modeling. It can also be directly integrated into the log posterior computation of any pre-existing transit modeling code with minimal modifications to constrain the LD model parameter space directly by the LD profile, allowing for the marginalization over the whole parameter space that can explain the profile without the need to approximate this constraint by a prior distribution. This is useful when using a high-order limb darkening model where the coefficients are often correlated, and the priors estimated from the tabulated values usually fail to include these correlations.

[ascl:1510.002] batman: BAsic Transit Model cAlculatioN in Python

batman provides fast calculation of exoplanet transit light curves and supports calculation of light curves for any radially symmetric stellar limb darkening law. It uses an integration algorithm for models that cannot be quickly calculated analytically, and in typical use, the batman Python package can calculate a million model light curves in well under ten minutes for any limb darkening profile.

[ascl:1510.001] GGADT: Generalized Geometry Anomalous Diffraction Theory

GGADT uses anomalous diffraction theory (ADT) to compute the differential scattering cross section (or the total cross sections as a function of energy) for a specified grain of arbitrary geometry (natively supports spheres, ellipsoids, and clusters of spherical monomers). It is written in Fortran 95. ADT is valid when the grain is large compared to the wavelength of incident light. GGADT can calculate either the integrated cross sections (absorption, scattering, extinction) as a function of energy, or it can calculate the differential scattering cross section as a function of scattering angle.

[ascl:1509.010] PyCS : Python Curve Shifting

PyCS is a software toolbox to estimate time delays between multiple images of strongly lensed quasars, from resolved light curves such as obtained by the COSMOGRAIL monitoring program. The pycs package defines a collection of classes and high level functions, that you can script in a flexible way. PyCS makes it easy to compare different point estimators (including your own) without much code integration. The package heavily depends on numpy, scipy, and matplotlib.

[ascl:1509.009] OPERA: Objective Prism Enhanced Reduction Algorithms

OPERA (Objective Prism Enhanced Reduction Algorithms) automatically analyzes astronomical images using the objective-prism (OP) technique to register thousands of low resolution spectra in large areas. It detects objects in an image, extracts one-dimensional spectra, and identifies the emission line feature. The main advantages of this method are: 1) to avoid subjectivity inherent to visual inspection used in past studies; and 2) the ability to obtain physical parameters without follow-up spectroscopy.

[ascl:1509.008] GFARGO: FARGO for GPU

GFARGO is a GPU version of FARGO (ascl:1102.017). It is written in C and C for CUDA and runs only on NVIDIA’s graphics cards. Though it corresponds to the standard, isothermal version of FARGO, not all functionalities of the CPU version have been translated to CUDA. The code is available in single and double precision versions, the latter compatible with FERMI architectures. GFARGO can run on a graphics card connected to the display, allowing the user to see in real time how the fields evolve.

[ascl:1509.007] pycola: N-body COLA method code

pycola is a multithreaded Python/Cython N-body code, implementing the Comoving Lagrangian Acceleration (COLA) method in the temporal and spatial domains, which trades accuracy at small-scales to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing. The COLA method achieves its speed by calculating the large-scale dynamics exactly using LPT while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos.

[ascl:1509.006] FARGO3D: Hydrodynamics/magnetohydrodynamics code

A successor of FARGO (ascl:1102.017), FARGO3D is a versatile HD/MHD code that runs on clusters of CPUs or GPUs, with special emphasis on protoplanetary disks. FARGO3D offers Cartesian, cylindrical or spherical geometry; 1-, 2- or 3-dimensional calculations; and orbital advection (aka FARGO) for HD and MHD calculations. As in FARGO, a simple Runge-Kutta N-body solver may be used to describe the orbital evolution of embedded point-like objects. There is no need to know CUDA; users can develop new functions in C and have them translated to CUDA automatically to run on GPUs.

[ascl:1509.005] TRUVOT: True Background Technique for the Swift UVOT Grisms

TRUVOT decontaminates Swift UVOT grism spectra for transient objects. The technique makes use of template images in a process similar to image subtraction.

[ascl:1509.004] FalconIC: Initial conditions generator for cosmological N-body simulations in Newtonian, Relativistic and Modified theories

FalconIC generates discrete particle positions, velocities, masses and pressures based on linear Boltzmann solutions that are computed by libraries such as CLASS and CAMB. FalconIC generates these initial conditions for any species included in the selection, including Baryons, Cold Dark Matter and Dark Energy fluids. Any species can be set in Eulerian (on a fixed grid) or Lagrangian (particle motion) representation, depending on the gauge and reality chosen. That is, for relativistic initial conditions in the synchronous comoving gauge, Dark Matter can only be described in an Eulerian representation. For all other choices (Relativistic in Longitudinal gauge, Newtonian with relativistic expansion rates, Newtonian without any notion of radiation), all species can be treated in all representations. The code also computes spectra. FalconIC is useful for comparative studies on initial conditions.

[ascl:1509.003] AFR (ASPFitsReader): A pulsar FITS file reader and analysis package

AFR, or ASPFitsReader, reduces, processes, and manipulates pulsar data, including calibration, template profile creation, and interactive excision of radio frequency interference from pulsar profile data. It also creates times-of-arrival compatible with Tempo (ascl:1509.002) and Tempo2 (ascl:1210.015) timing software.

[ascl:1509.002] Tempo: Pulsar timing data analysis

Tempo analyzes pulsar timing data. Pulse times of arrival (TOAs), pulsar model parameters, and coded instructions are read from one or more input files. The TOAs are fitted by a pulse timing model incorporating transformation to the solar-system barycenter, pulsar rotation and spin-down and, where necessary, one of several binary models. Program output includes parameter values and uncertainties, residual pulse arrival times, chi-squared statistics, and the covariance matrix of the model. In prediction mode, ephemerides of pulse phase behavior (in the form of polynomial expansions) are calculated from input timing models. Tempo is the basis for the Tempo2 (ascl:1210.015) code.

[ascl:1509.001] XSHPipelineManager: Wrapper for the VLT/X-shooter Data Reduction Pipeline

XSHPipelineManager provides a framework for reducing spectroscopic observations taken by the X-shooter spectrograph at the Very Large Telescope. This Python code wraps recipes developed by the European Southern Observatory and runs the full X-shooter data reduction pipeline. The code offers full flexibility in terms of what data reduction recipes to include and which calibration files to use. During the data reduction chain restart-files are saved, making it possible to restart at any step in the chain.

[ascl:1508.010] SHDOM: Spherical Harmonic Discrete Ordinate Method for atmospheric radiative transfer

The Spherical Harmonic Discrete Ordinate Method (SHDOM) radiative transfer model computes polarized monochromatic or spectral band radiative transfer in a one, two, or three-dimensional medium for either collimated solar and/or thermal emission sources of radiation. The model is written in a variant of Fortran 77 and in Fortran90 and requires a Fortran 90 compiler. Also included are programs for generating the optical property files input to SHDOM from physical properties of water cloud particles and aerosols.

[ascl:1508.009] Trilogy: FITS image conversion software

Trilogy automatically scales and combines FITS images to produce color or grayscale images using Python scripts. The user assigns images to each color channel (RGB) or a single image to grayscale luminosity. Trilogy determines the intensity scaling automatically and independently in each channel to display faint features without saturating bright features. Each channel's scaling is determined based on a sample of the image (or summed images) and two input parameters. One parameter sets the output luminosity of "the noise," currently determined as 1-sigma above the sigma-clipped mean. The other parameter sets what fraction of the data (if any) in the sample region should be allowed to saturate. Default values for these parameters (0.15% and 0.001%, respectively) work well, but the user is able to adjust them. The scaling is accomplished using the logarithmic function y = a log(kx + 1) clipped between 0 and 1, where a and k are constants determined based on the data and desired scaling parameters as described above.

[ascl:1508.008] NGMIX: Gaussian mixture models for 2D images

NGMIX implements Gaussian mixture models for 2D images. Both the PSF profile and the galaxy are modeled using mixtures of Gaussians. Convolutions are thus performed analytically, resulting in fast model generation as compared to methods that perform the convolution in Fourier space. For the galaxy model, NGMIX supports exponential disks and de Vaucouleurs and Sérsic profiles; these are implemented approximately as a sum of Gaussians using the fits from Hogg & Lang (2013). Additionally, any number of Gaussians can be fit, either completely free or constrained to be cocentric and co-elliptical.

[ascl:1508.007] TreeCorr: Two-point correlation functions

TreeCorr efficiently computes two-point correlation functions. It can compute correlations of regular number counts, weak lensing shears, or scalar quantities such as convergence or CMB temperature fluctuations. Two-point correlations may be auto-correlations or cross-correlations, including any combination of shear, kappa, and counts. Two-point functions can be done with correct curved-sky calculation using RA, Dec coordinates, on a Euclidean tangent plane, or in 3D using RA, Dec and a distance. The front end is written in Python, which can be used as a Python module or as a standalone executable using configuration files; the actual computation of the correlation functions is done in C++ using ball trees (similar to kd trees), making the calculation extremely efficient, and when available, OpenMP is used to run in parallel on multi-core machines.

[ascl:1508.006] SExSeg: SExtractor segmentation

SExSeg forces SExtractor (ascl:1010.064) to run using a pre-defined segmentation map (the definition of objects and their borders). The defined segments double as isophotal apertures. SExSeg alters the detection image based on a pre-defined segmenation map while preparing your "analysis image" by subtracting the background in a separate SExtractor run (using parameters you specify). SExtractor is then run in "double-image" mode with the altered detection image and background-subtracted analysis image.

[ascl:1508.005] ColorPro: PSF-corrected aperture-matched photometry

ColorPro automatically obtains robust colors across images of varied PSF. To correct for the flux lost in images with poorer PSF, the "detection image" is blurred to match the PSF of these other images, allowing observation of how much flux is lost. All photometry is performed in the highest resolution frame (images being aligned given WCS information in the FITS headers), and identical apertures are used in every image. Usually isophotal apertures are used, as determined by SExtractor (ascl:1010.064). Using SExSeg (ascl:1508.006), object aperture definitions can be pre-defined and object detections from different image filters can be combined automatically into a single comprehensive "segmentation map." After producing the final photometric catalog, ColorPro can automatically run BPZ (ascl:1108.011) to obtain Bayesian Photometric Redshifts.

[ascl:1508.004] FRELLED: FITS Realtime Explorer of Low Latency in Every Dimension

FRELLED (FITS Realtime Explorer of Low Latency in Every Dimension) creates 3D images in real time from 3D FITS files and is written in Python for the 3D graphics suite Blender. Users can interactively generate masks around regions of arbitrary geometry and use them to catalog sources, hide regions, and perform basic analysis (e.g., image statistics within the selected region, generate contour plots, query NED and the SDSS). World coordinates are supported and multi-volume rendering is possible. FRELLED is designed for viewing HI data cubes and provides a number of tasks to commonly-used MIRIAD (ascl:1106.007) tasks (e.g. mbspect); however, many of its features are suitable for any type of data set. It also includes an n-body particle viewer with the ability to display 3D vector information as well as the ability to render time series movies of multiple FITS files and setup simple turntable rotation movies for single files.

[ascl:1508.003] REDUCEME: Long-slit spectroscopic data reduction and analysis

The astronomical data reduction package REDUCEME reduces and analyzes long-slit spectroscopic data. The package uses the unformatted FORTRAN raw data format, so requires FITS files be transformed to REDUCEME format; the reverse operation (from REDUCEME to FITS format) is also available. The package is a set of programs written in FORTRAN 77 and includes shell scripts (using the C shell syntax) to perform routine tasks; it can be extended by the inclusion of external programs. REDUCEME uses PGPLOT (ascl:1103.002) for line plots and images, and a subset of subroutines, called BUTTON, enables the user to communicate interactively with the image display employing graphic buttons. One advantage of using REDUCEME is that for each image an associated error image can also be processed throughout the reduction process, allowing for a careful control of the error propagation.

[ascl:1508.002] NICOLE: NLTE Stokes Synthesis/Inversion Code

NICOLE, written in Fortran 90, seeks the model atmosphere that provides the best fit to the Stokes profiles (in a least-squares sense) of an arbitrary number of simultaneously-observed spectral lines from solar/stellar atmospheres. The inversion core used for the development of NICOLE is the LORIEN engine (the Lovely Reusable Inversion ENgine), which combines the SVD technique with the Levenberg-Marquardt minimization method to solve the inverse problem.

[ascl:1508.001] HMcode: Halo-model matter power spectrum computation

HMcode computes the halo-model matter power spectrum. It is written in Fortran90 and has been designed to quickly (~0.5s for 200 k-values across 16 redshifts on a single core) produce matter spectra for a wide range of cosmological models. In testing it was shown to match spectra produced by the 'Coyote Emulator' to an accuracy of 5 per cent for k less than 10h Mpc^-1. However, it can also produce spectra well outside of the parameter space of the emulator.

[ascl:1507.020] IEHI: Ionization Equilibrium for Heavy Ions

IEHI, written in Fortran, outputs a simple "coronal" ionization equilibrium (i.e., collisional ionization and auto-ionization balanced by radiative and dielectronic recombination) for a plasma at a given electron temperature.

[ascl:1507.019] AstroStat: Statistical analysis tool

AstroStat performs statistical analysis on data and is compatible with Virtual Observatory (VO) standards. It accepts data in a variety of formats and performs various statistical tests using a menu driven interface. Analyses, performed in R, include exploratory tests, visualizations, distribution fitting, correlation and causation, hypothesis testing, multivariate analysis and clustering. AstroStat is available in two versions with an identical interface and features: as a web service that can be run using any standard browser and as an offline application.

[ascl:1507.018] pyro: Python-based tutorial for computational methods for hydrodynamics

pyro is a simple python-based tutorial on computational methods for hydrodynamics. It includes 2-d solvers for advection, compressible, incompressible, and low Mach number hydrodynamics, diffusion, and multigrid. It is written with ease of understanding in mind. An extensive set of notes that is part of the Open Astrophysics Bookshelf project provides details of the algorithms.

[ascl:1507.017] REDSPEC: NIRSPEC data reduction

REDSPEC is an IDL based reduction package designed with NIRSPEC in mind though can be used to reduce data from other spectrographs as well. REDSPEC accomplishes spatial rectification by summing an A+B pair of a calibration star to produce an image with two spectra; the image is remapped on the basis of polynomial fits to the spectral traces and calculation of gaussian centroids to define their separation, producing straight spectral traces with respect to the detector rows. The raw images are remapped onto a coordinate system with uniform intervals in spatial extent along the slit and in wavelength along the dispersion axis.

[ascl:1507.016] Least Asymmetry: Centering Method

Least Asymmetry finds the center of a distribution of light in an image using the least asymmetry method; the code also contains center of light and fitting a Gaussian routines. All functions in Least Asymmetry are designed to take optional weights.

[ascl:1507.015] DALI: Derivative Approximation for LIkelihoods

DALI (Derivative Approximation for LIkelihoods) is a fast approximation of non-Gaussian likelihoods. It extends the Fisher Matrix in a straightforward way and allows for a wider range of posterior shapes. The code is written in C/C++.

[ascl:1507.014] getsources: Multi-scale, multi-wavelength source extraction

getsources is a powerful multi-scale, multi-wavelength source extraction algorithm. It analyzes fine spatial decompositions of original images across a wide range of scales and across all wavebands, cleans those single-scale images of noise and background, and constructs wavelength-independent single-scale detection images that preserve information in both spatial and wavelength dimensions. getsources offers several advantages over other existing methods of source extraction, including the filtering out of irrelevant spatial scales to improve detectability, especially in the crowded regions and for extended sources, the ability to combine data over all wavebands, and the full automation of the extraction process.

[ascl:1507.013] K-Inpainting: Inpainting for Kepler

Inpainting is a technique for dealing with gaps in time series data, as frequently occurs in asteroseismology data, that may generate spurious peaks in the power spectrum, thus limiting the analysis of the data. The inpainting method, based on a sparsity prior, judiciously fills in gaps in the data, preserving the asteroseismic signal as far as possible. This method can be applied both on ground and space-based data. The inpainting technique improves the oscillation modes detection and estimation, the impact of the observational window function is reduced, and the interpretation of the power spectrum is simplified. K-Inpainting can be used to study very long time series of many stars because its computation is very fast.

[ascl:1507.012] DRAMA: Instrumentation software environment

DRAMA is a fast, distributed environment for writing instrumentation control systems. It allows low level instrumentation software to be controlled from user interfaces running on UNIX, MS Windows or VMS machines in a consistent manner. Such instrumentation tasks can run either on these machines or on real time systems such as VxWorks. DRAMA uses techniques developed by the AAO while using the Starlink-ADAM environment, but is optimized for the requirements of instrumentation control, portability, embedded systems and speed. A special program is provided which allows seamless communication between ADAM and DRAMA tasks.

[ascl:1507.011] FAT: Fully Automated TiRiFiC

FAT (Fully Automated TiRiFiC) is an automated procedure that fits tilted-ring models to Hi data cubes of individual, well-resolved galaxies. The method builds on the 3D Tilted Ring Fitting Code (TiRiFiC, ascl:1208.008). FAT accurately models the kinematics and the morphologies of galaxies with an extent of eight beams across the major axis in the inclination range 20°-90° without the need for priors such as disc inclination. FAT's performance allows us to model the gas kinematics of many thousands of well-resolved galaxies, which is essential for future HI surveys, with the Square Kilometre Array and its pathfinders.

[ascl:1507.010] Astrochem: Abundances of chemical species in the interstellar medium

Astrochem computes the abundances of chemical species in the interstellar medium, as function of time. It studies the chemistry in a variety of astronomical objects, including diffuse clouds, dense clouds, photodissociation regions, prestellar cores, protostars, and protostellar disks. Astrochem reads a network of chemical reactions from a text file, builds up a system of kinetic rates equations, and solves it using a state-of-the-art stiff ordinary differential equation (ODE) solver. The Jacobian matrix of the system is computed implicitly, so the resolution of the system is extremely fast: large networks containing several thousands of reactions are usually solved in a few seconds. A variety of gas phase process are considered, as well as simple gas-grain interactions, such as the freeze-out and the desorption via several mechanisms (thermal desorption, cosmic-ray desorption and photo-desorption). The computed abundances are written in a HDF5 file, and can be plotted in different ways with the tools provided with Astrochem. Chemical reactions and their rates are written in a format which is meant to be easy to read and to edit. A tool to convert the chemical networks from the OSU and KIDA databases into this format is also provided. Astrochem is written in C, and its source code is distributed under the terms of the GNU General Public License (GPL).

[ascl:1507.009] PPInteractions: Secondary particle spectra from proton-proton interactions

PPInteractions generates the secondary particle energy spectra produced in proton-proton interactions over the entire chosen energy range for any value of the primary proton spectral index by adjusting the low energy part of the spectra (below 0.1TeV) to the high energy end of the spectra (above 0.1TeV). This code is based on the parametrization of Kelner et al (2006), in which the normalization of the low energy part of the spectra is given only for 3 values of the primary proton spectral indices (2, 2.5, 3).

[ascl:1507.008] HLINOP: Hydrogen LINe OPacity in stellar atmospheres

HLINOP is a collection of codes for computing hydrogen line profiles and opacities in the conditions typical of stellar atmospheres. It includes HLINOP for approximate quick calculation of any line of neutral hydrogen (suitable for model atmosphere calculations), based on the Fortran code of Kurucz and Peterson found in ATLAS9. It also includes HLINPROF, for detailed, accurate calculation of lower Balmer line profiles (suitable for detailed analysis of Balmer lines) and HBOP, to implement the occupation probability formalism of Daeppen, Anderson and Milhalas (1987) and thus account for the merging of bound-bound and bound-free opacity (used often as a wrapper to HLINOP for model atmosphere calculations).

[ascl:1507.007] abo-cross: Hydrogen broadening cross-section calculator

Line broadening cross sections for the broadening of spectral lines by collisions with neutral hydrogen atoms have been tabulated by Anstee & O’Mara (1995), Barklem & O’Mara (1997) and Barklem, O’Mara & Ross (1998) for s–p, p–s, p–d, d–p, d–f and f–d transitions. abo-cross, written in Fortran, interpolates in these tabulations to make these data more accessible to the end user. This code can be incorporated into existing spectrum synthesis programs or used it in a stand-alone mode to compute line broadening cross sections for specific transitions.

[ascl:1507.006] Toyz: Large datasets and astronomical images analysis framework

Toyz is a python web framework that allows scientists to interact with large images and data sets stored on a remote server. A web application is run on the server containing the data and clients are run from web browsers on the user's computer. Toyz displays large FITS images and also renders any image format supported by Pillow (a fork of the Python Imaging Library), contains a GUI to interact with linked plots, and offers a customizable framework that allows students and researchers to create their own work spaces inside a Toyz environment. Astro-Toyz extends the features of the Toyz image viewer, allowing users to view world coordinates and align images based on their WCS.

[ascl:1507.005] slimplectic: Discrete non-conservative numerical integrator

slimplectic is a python implementation of a numerical integrator that uses a fixed time-step variational integrator formalism applied to the principle of stationary nonconservative action. It allows nonconservative effects to be included in the numerical evolution while preserving the major benefits of normally conservative symplectic integrators, particularly the accurate long-term evolution of momenta and energy. slimplectic is appropriate for exploring cosmological or celestial N-body dynamics problems where nonconservative interactions, e.g. dynamical friction or dissipative tides, can play an important role.

[ascl:1507.004] L-PICOLA: Fast dark matter simulation code

L-PICOLA generates and evolves a set of initial conditions into a dark matter field and can include primordial non-Gaussianity in the simulation and simulate the past lightcone at run-time, with optional replication of the simulation volume. It is a fast, distributed-memory, planar-parallel code. L-PICOLA is extremely useful for both current and next generation large-scale structure surveys.

[ascl:1507.003] Pelican: Pipeline for Extensible, Lightweight Imaging and CAlibratioN

Pelican is an efficient, lightweight C++ library for quasi-real time data processing. The library provides a framework to separate the acquisition and processing of data, allowing the scalability and flexibility to fit a number of scenarios. Though its origin was in radio astronomy, processing data as it arrives from a telescope, the framework is sufficiently generic to be useful to any application that requires the efficient processing of incoming data streams.

[ascl:1507.002] SUPERBOX: Particle-multi-mesh code to simulate galaxies

SUPERBOX is a particle-mesh code that uses moving sub-grids to track and resolve high-density peaks in the particle distribution and a nearest grid point force-calculation scheme based on the second derivatives of the potential. The code implements a fast low-storage FFT-algorithm and allows a highly resolved treatment of interactions in clusters of galaxies, such as high-velocity encounters between elliptical galaxies and the tidal disruption of dwarf galaxies, as sub-grids follow the trajectories of individual galaxies. SUPERBOX is efficient in that the computational overhead is kept as slim as possible and is also memory efficient since it uses only one set of grids to treat galaxies in succession.

[ascl:1507.001] 3D-Barolo: 3D fitting tool for the kinematics of galaxies

3D-Barolo (3D-Based Analysis of Rotating Object via Line Observations) or BBarolo is a tool for fitting 3D tilted-ring models to emission-line datacubes. BBarolo works with 3D FITS files, i.e. image arrays with two spatial and one spectral dimensions. BBarolo recovers the true rotation curve and estimates the intrinsic velocity dispersion even in barely resolved galaxies (about 2 resolution elements) if the signal to noise of the data is larger than 2-3. It has source-detection and first-estimate modules, making it suitable for analyzing large 3D datasets automatically, and is a useful tool for deriving reliable kinematics for both local and high-redshift galaxies.

[ascl:1506.010] VAPID: Voigt Absorption-Profile [Interstellar] Dabbler

VAPID (Voigt Absorption Profile [Interstellar] Dabbler) models interstellar absorption lines. It predicts profiles and optimizes model parameters by least-squares fitting to observed spectra. VAPID allows cloud parameters to be optimized with respect to several different data set simultaneously; those data sets may include observations of different transitions of a given species, and may have different S/N ratios and resolutions.

[ascl:1506.009] HEATCVB: Coronal heating rate approximations

HEATCVB is a stand-alone Fortran 77 subroutine that estimates the local volumetric coronal heating rate with four required inputs: the radial distance r, the wind speed u, the mass density ρ, and the magnetic field strength |B0|. The primary output is the heating rate Qturb at the location defined by the input parameters. HEATCVB also computes the local turbulent dissipation rate of the waves, γ = Qturb/(2UA).

[ascl:1506.008] SPRITE: Sparsity-based super-resolution algorithm

SPRITE (Sparse Recovery of InstrumenTal rEsponse) computes a well-resolved compact source image from several undersampled and noisy observations. The algorithm is based on sparse regularization; adding a sparse penalty in the recovery leads to far better accuracy in terms of ellipticity error, especially at low S/N.

[ascl:1506.007] REALMAF: Magnetic power spectra from Faraday rotation maps

REALMAF is a maximum-a-posteriori code to measure magnetic power spectra from Faraday rotation data. It uses a sophisticated model for the magnetic autocorrelation in real space, thus alleviating the need for simplifying assumptions in the processing. REALMAF treats the divergence relation of the magnetic field with a multiplicative factor in Fourier space, which allows modeling the magnetic autocorrelation as a spherically symmetric function.

[ascl:1506.006] fsclean: Faraday Synthesis CLEAN imager

Fsclean produces 3D Faraday spectra using the Faraday synthesis method, transforming directly from multi-frequency visibility data to the Faraday depth-sky plane space. Deconvolution is accomplished using the CLEAN algorithm, and the package includes Clark and Högbom style CLEAN algorithms. Fsclean reads in MeasurementSet visibility data and produces HDF5 formatted images; it handles images and data of arbitrary size, using scratch HDF5 files as buffers for data that is not being immediately processed, and is limited only by available disk space.

[ascl:1506.005] PyMC: Bayesian Stochastic Modelling in Python

PyMC is a python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics.

[ascl:1506.004] multiband_LS: Multiband Lomb-Scargle Periodograms

The multiband periodogram is a general extension of the well-known Lomb-Scargle approach for detecting periodic signals in time-domain data. In addition to advantages of the Lomb-Scargle method such as treatment of non-uniform sampling and heteroscedastic errors, the multiband periodogram significantly improves period finding for randomly sampled multiband light curves (e.g., Pan-STARRS, DES and LSST). The light curves in each band are modeled as arbitrary truncated Fourier series, with the period and phase shared across all bands.

[ascl:1506.003] PLATO Simulator: Realistic simulations of expected observations

PLATO Simulator is an end-to-end simulation software tool designed for the performance of realistic simulations of the expected observations of the PLATO mission but easily adaptable to similar types of missions. It models and simulates photometric time-series of CCD images by including models of the CCD and its electronics, the telescope optics, the stellar field, the jitter movements of the spacecraft, and all important natural noise sources.

[ascl:1506.002] dmdd: Dark matter direct detection

The dmdd package enables simple simulation and Bayesian posterior analysis of recoil-event data from dark-matter direct-detection experiments under a wide variety of scattering theories. It enables calculation of the nuclear-recoil rates for a wide range of non-relativistic and relativistic scattering operators, including non-standard momentum-, velocity-, and spin-dependent rates. It also accounts for the correct nuclear response functions for each scattering operator and takes into account the natural abundances of isotopes for a variety of experimental target elements.

[ascl:1506.001] pyKLIP: PSF Subtraction for Exoplanets and Disks

pyKLIP subtracts out the stellar PSF to search for directly-imaged exoplanets and disks using a Python implementation of the Karhunen-Loève Image Projection (KLIP) algorithm. pyKLIP supports ADI, SDI, and ADI+SDI to model the stellar PSF and offers a large array of PSF subtraction parameters to optimize the reduction. pyKLIP relies on a minimal amount of dependencies (numpy, scipy, and astropy) and parallelizes the KLIP algorithm to speed up the reduction. pyKLIP supports GPI and P1640 data and can interface with other data sources with the addition of new modules. It also can inject simulated planets and disks as well as automatically search for point sources in PSF-subtracted data.

[ascl:1505.034] dStar: Neutron star thermal evolution code

dStar is a collection of modules for computing neutron star structure and evolution, and uses the numerical, utility, and equation of state libraries of MESA (ascl:1010.083).

[ascl:1505.033] SNEC: SuperNova Explosion Code

SNEC (SuperNova Explosion Code) is a spherically-symmetric Lagrangian radiation-hydrodynamics code that follows supernova explosions through the envelope of their progenitor star, produces bolometric (and approximate multi-color) light curve predictions, and provides input to spectral synthesis codes for spectral modeling. SNEC's features include 1D (spherical) Lagrangian Newtonian hydrodynamics with artificial viscosity, stellar equation of state with a Saha solver ionization/recombination, equilibrium flux-limited photon diffusion with OPAL opacities and low-temperature opacities, and prediction of bolometric light curves and multi-color lightcurves (in the blackbody approximation).

[ascl:1505.032] Planck Level-S: Planck Simulation Package

The Planck simulation package takes a cosmological model specified by the user and calculates a potential CMB sky consistent with this model, including astrophysical foregrounds, and then performs a simulated observation of this sky. This Simulation embraces many instrumental effects such as beam convolution and noise. Alternatively, the package can simulate the observation of a provided sky model, generated by another program such as the Planck Sky Model software. The Planck simulation package does not only provide Planck-like data, it can also be easily adopted to mimic the properties of other existing and upcoming CMB experiments.

[ascl:1505.031] TEA: Thermal Equilibrium Abundances

TEA (Thermal Equilibrium Abundances) calculates gaseous molecular abundances under thermochemical equilibrium conditions. Given a single T,P point or a list of T,P pairs (the thermal profile of an atmosphere) and elemental abundances, TEA calculates mole fractions of the desired molecular species. TEA uses 84 elemental species and thermodynamical data for more then 600 gaseous molecular species, and can adopt any initial elemental abundances.

[ascl:1505.030] CANDID: Companion Analysis and Non-Detection in Interferometric Data

CANDID finds faint companion around star in interferometric data in the OIFITS format. It allows systematically searching for faint companions in OIFITS data, and if not found, estimates the detection limit. The tool is based on model fitting and Chi2 minimization, with a grid for the starting points of the companion position. It ensures all positions are explored by estimating a-posteriori if the grid is dense enough, and provides an estimate of the optimum grid density.

[ascl:1505.029] fits2hdf: FITS to HDFITS conversion

fits2hdf ports FITS files to Hierarchical Data Format (HDF5) files in the HDFITS format. HDFITS allows faster reading of data, higher compression ratios, and higher throughput. HDFITS formatted data can be presented transparently as an in-memory FITS equivalent by changing the import lines in Python-based FITS utilities. fits2hdf includes a utility to port MeasurementSets (MS) to HDF5 files.

[ascl:1505.028] RESOLVE: Bayesian algorithm for aperture synthesis imaging in radio astronomy

RESOLVE is a Bayesian inference algorithm for image reconstruction in radio interferometry. It is optimized for extended and diffuse sources. Features include parameter-free Bayesian reconstruction of radio continuum data with a focus on extended and weak diffuse sources, reconstruction with uncertainty propagation dependent on measurement noise, and estimation of the spatial correlation structure of the radio astronomical source. RESOLVE provides full support for measurement sets and includes a simulation tool (if uv-coverage is provided).

[ascl:1505.027] BAYES-X: Bayesian inference tool for the analysis of X-ray observations of galaxy clusters

The great majority of X-ray measurements of cluster masses in the literature assume parametrized functional forms for the radial distribution of two independent cluster thermodynamic properties, such as electron density and temperature, to model the X-ray surface brightness. These radial profiles (e.g. β-model) have an amplitude normalization parameter and two or more shape parameters. BAYES-X uses a cluster model to parametrize the radial X-ray surface brightness profile and explore the constraints on both model parameters and physical parameters. Bayes-X is programmed in Fortran and uses MultiNest (ascl:1109.006) as the Bayesian inference engine.

[ascl:1505.026] Lensed: Forward parametric modelling of strong lenses

Lensed performs forward parametric modelling of strong lenses. Using a provided model, Lensed renders the expected image of the lensing event for a large number of parameter settings, thereby exploring the space of possible realizations of the observation. It compares the expectation to the observed image by calculating the likelihood that the observation was indeed produced by the assumed model, thus reconstructing the probability distribution over the parameter space of the model. Written in C, the code uses a massively parallel ray-tracing kernel to perform the necessary calculations on a graphics processing unit (GPU), making the precise rendering of the background lensed sources fast and allowing the simultaneous optimization of tens of parameters for the selected model.

[ascl:1505.025] pyMCZ: Oxygen abundances calculations and uncertainties from strong-line flux measurements

pyMCZ calculates metallicity according to a number of strong line metallicity diagnostics from spectroscopy line measurements and obtains uncertainties from the line flux errors in a Monte Carlo framework. Given line flux measurements and their uncertainties, pyMCZ produces synthetic distributions for the oxygen abundance in up to 13 metallicity scales simultaneously, as well as for E(B-V), and estimates their median values and their 68% confidence regions. The code can output the full MC distributions and their kernel density estimates.

[ascl:1505.024] PyTransit: Transit light curve modeling

PyTransit implements optimized versions of the Giménez and Mandel & Agol transit models for exoplanet transit light-curves. The two models are implemented natively in Fortran with OpenMP parallelization, and are accessed by an object-oriented python interface. PyTransit facilitates the analysis of photometric time series of exoplanet transits consisting of hundreds of thousands of data points, and of multipassband transit light curves from spectrophotometric observations. It offers efficient model evaluation for multicolour observations and transmission spectroscopy, built-in supersampling to account for extended exposure times, and routines to calculate the projected planet-to-star distance for circular and eccentric orbits, transit durations, and more.

[ascl:1505.023] SNooPy: TypeIa supernovae analysis tools

The SNooPy package (also known as SNpy), written in Python, contains tools for the analysis of TypeIa supernovae. It offers interactive plotting of light-curve data and models (and spectra), computation of reddening laws and K-corrections, LM non-linear least-squares fitting of light-curve data, and various types of spline fitting, including Diercx and tension. The package also includes a SNIa lightcurve template generator in the CSP passbands, estimates of Milky-Way Extinction, and a module for dealing with filters and spectra.

[ascl:1505.022] Snoopy: General purpose spectral solver

Snoopy is a spectral 3D code that solves the MHD and Boussinesq equations, such as compressibility, particles, and Braginskii viscosity, and several other physical effects. It's useful for turbulence study involving shear and rotation. Snoopy requires the FFTW library (ascl:1201.015), and can run on parallel machine using MPI OpenMP or both at the same time.

[ascl:1505.021] relline: Relativistic line profiles calculation

relline calculates relativistic line profiles; it is compatible with the common X-ray data analysis software XSPEC (ascl:9910.005) and ISIS (ascl:1302.002). The two basic forms are an additive line model (RELLINE) and a convolution model to calculate relativistic smearing (RELCONV).

[ascl:1505.020] rvfit: Radial velocity curves fitting for binary stars or exoplanets

rvfit, developed in IDL 7.0, fits non-precessing keplerian radial velocity (RV) curves for double-line and single-line binary stars or exoplanets. It fits a simple keplerian model to the observed RV and computes the seven parameters (six for a single-line system) from the model. Some parameters can be fixed beforehand if they are known, for instance, if photometric observations are available. The fit is done using an Adaptive Simulated Annealing algorithm optimized for this specific task. Simulated Annealing methods are powerful heuristic algorithms to minimize functions in multiparametric spaces.

[ascl:1505.019] TFIT: Mixed-resolution data set photometry package

TFIT measures galaxy photometry using prior knowledge of sources in a deep, high‐resolution image (HRI) to improve photometric measurements of objects in a corresponding low‐resolution image (LRI) of the same field, usually at a different wavelength. For background‐limited data, this technique produces optimally weighted photometry that maximizes signal‐to‐noise ratio (S/N). For objects not significantly detected in the low‐resolution image, it provides useful and quantitative information for setting upper limits.

This code is no longer updated and has been superseded by T-PHOT (ascl:1609.001).

[ascl:1505.018] POKER: P Of K EstimatoR

POKER (P Of K EstimatoR) estimates the angular power spectrum of a 2D map or the cross-power spectrum of two 2D maps in the flat sky limit approximation in a realistic data context: steep power spectrum, non periodic boundary conditions, arbitrary pixel resolution, non trivial masks and observation patch geometry.

[ascl:1505.017] HALOGEN: Approximate synthetic halo catalog generator

HALOGEN generates approximate synthetic halo catalogs. Written in C, it decomposes the problem of generating cosmological tracer distributions (eg. halos) into four steps: generating an approximate density field, generating the required number of tracers from a CDF over mass, placing the tracers on field particles according to a bias scheme dependent on local density, and assigning velocities to the tracers based on velocities of local particles. It also implements a default set of four models for these steps. HALOGEN uses 2LPTic (ascl:1201.005) and CUTE (ascl:1505.016); the software is flexible and can be adapted to varying cosmologies and simulation specifications.

[ascl:1505.016] CUTE: Correlation Utilities and Two-point Estimation

CUTE (Correlation Utilities and Two-point Estimation) extracts any two-point statistic from enormous datasets with hundreds of millions of objects, such as large galaxy surveys. The computational time grows with the square of the number of objects to be correlated; technology provides multiple means to massively parallelize this problem and CUTE is specifically designed for these kind of calculations. Two implementations are provided: one for execution on shared-memory machines using OpenMP and one that runs on graphical processing units (GPUs) using CUDA.

[ascl:1505.015] 2dfdr: Data reduction software

2dfdr is an automatic data reduction pipeline dedicated to reducing multi-fibre spectroscopy data, with current implementations for AAOmega (fed by the 2dF, KOALA-IFU, SAMI Multi-IFU or older SPIRAL front-ends), HERMES, 2dF (spectrograph), 6dF, and FMOS. A graphical user interface is provided to control data reduction and allow inspection of the reduced spectra.

[ascl:1505.014] FCLC: Featureless Classification of Light Curves

FCLC (Featureless Classification of Light Curves) software describes the static behavior of a light curve in a probabilistic way. Individual data points are converted to densities and consequently probability density are compared instead of features. This gives rise to an independent classification which can corroborate the usefulness of the selected features.

[ascl:1505.013] cosmoabc: Likelihood-free inference for cosmology

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogs. cosmoabc is a Python Approximate Bayesian Computation (ABC) sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code can be coupled to an external simulator to allow incorporation of arbitrary distance and prior functions. When coupled with the numcosmo library, it has been used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function.

[ascl:1505.012] LSSGALPY: Visualization of the large-scale environment around galaxies on the 3D space

LSSGALPY provides visualization tools to compare the 3D positions of a sample (or samples) of isolated systems with respect to the locations of the large-scale structures galaxies in their local and/or large scale environments. The interactive tools use different projections in the 3D space (right ascension, declination, and redshift) to study the relation of the galaxies with the LSS. The tools permit visualization of the locations of the galaxies for different values of redshifts and redshift ranges; the relationship of isolated galaxies, isolated pairs, and isolated triplets to the galaxies in the LSS can be visualized for different values of the declinations and declination ranges.

[ascl:1505.011] missForest: Nonparametric missing value imputation using random forest

missForest imputes missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation and can be run in parallel to save computation time. missForest has been used to, among other things, impute variable star colors in an All-Sky Automated Survey (ASAS) dataset of variable stars with no NOMAD match.

[ascl:1505.010] COBS: COnstrained B-Splines

COBS (COnstrained B-Splines), written in R, creates constrained regression smoothing splines via linear programming and sparse matrices. The method has two important features: the number and location of knots for the spline fit are established using the likelihood-based Akaike Information Criterion (rather than a heuristic procedure); and fits can be made for quantiles (e.g. 25% and 75% as well as the usual 50%) in the response variable, which is valuable when the scatter is asymmetrical or non-Gaussian. This code is useful for, for example, estimating cluster ages when there is a wide spread in stellar ages at a chosen absorption, as a standard regression line does not give an effective measure of this relationship.

[ascl:1505.009] StellaR: Stellar evolution tracks and isochrones tools

stellaR accesses and manipulates publicly available stellar evolutionary tracks and isochrones from the Pisa low-mass database. It retrieves and plots the required calculations from CDS, constructs by interpolation tracks or isochrones of compositions different to the ones available in the database, constructs isochrones for age not included in the database, and extracts relevant evolutionary points from tracks or isochrones.

[ascl:1505.008] SCEPtER: Stellar CharactEristics Pisa Estimation gRid

SCEPtER (Stellar CharactEristics Pisa Estimation gRid) estimates the stellar mass and radius given a set of observable quantities; the results are obtained by adopting a maximum likelihood technique over a grid of pre-computed stellar models. The code is quite flexible since different observables can be used, depending on their availability, as well as different grids of models.

[ascl:1505.007] Starfish: Robust spectroscopic inference tools

Starfish is a set of tools used for spectroscopic inference. It robustly determines stellar parameters using high resolution spectral models and uses Markov Chain Monte Carlo (MCMC) to explore the full posterior probability distribution of the stellar parameters. Additional potential applications include other types of spectra, such as unresolved stellar clusters or supernovae spectra.

[ascl:1505.006] Athena3D: Flux-conservative Godunov-type algorithm for compressible magnetohydrodynamics

Written in FORTRAN, Athena3D, based on Athena (ascl:1010.014), is an implementation of a flux-conservative Godunov-type algorithm for compressible magnetohydrodynamics. Features of the Athena3D code include compressible hydrodynamics and ideal MHD in one, two or three spatial dimensions in Cartesian coordinates; adiabatic and isothermal equations of state; 1st, 2nd or 3rd order reconstruction using the characteristic variables; and numerical fluxes computed using the Roe scheme. In addition, it offers the ability to add source terms to the equations and is parallelized based on MPI.

[ascl:1505.005] ARoME: Analytical Rossiter-McLaughlin Effects

The ARoMe (Analytical Rossiter-McLaughlin Effects) library generates analytical Rossiter-McLaughlin (RM) effects. It models the Doppler-shift of a star during a transit measured by the fit of a cross-correlation function by a Gaussian function, fit of an observed spectrum by a modeled one, and the weighted mean.

[ascl:1505.004] KS Integration: Kelvin-Stokes integration

KS Intergration solves for mutual photometric effects produced by planets and spots allowing for analysis of planetary occultations of spots and spots regions. It proceeds by identifying integrable and non integrable arcs on the objects profiles and analytically calculates the solution exploiting the power of Kelvin-Stokes theorem. It provides the solution up to the second degree of the limb darkening law.

[ascl:1505.003] caret: Classification and Regression Training

caret (Classification And REgression Training) provides functions for training and plotting classification and regression models. It contains tools for data splitting, pre-processing, feature selection, model tuning using resampling, and variable importance estimation, as well as other functionality.

[ascl:1505.002] ASteCA: Automated Stellar Cluster Analysis

ASteCA (Automated Stellar Cluster Analysis), written in Python, fully automates standard tests applied on star clusters in order to determine their characteristics, including center, radius, and stars' membership probabilities. It also determines associated intrinsic/extrinsic parameters, including metallicity, age, reddening, distance, total mass, and binarity fraction, among others.

[ascl:1505.001] CALCEPH: Planetary ephemeris files access code

CALCEPH accesses binary planetary ephemeris files, including INPOPxx, JPL DExxx ,and SPICE ephemeris files. It provides a C Application Programming Interface (API) and, optionally, a Fortran 77 or 2003 interface to be called by the application. Two groups of functions enable the access to the ephemeris files, single file access functions, provided to make transition easier from the JPL functions, such as PLEPH, to this library, and many ephemeris file at the same time. Although computers have different endianess (order in which integers are stored as bytes in computer memory), CALCEPH can handles the binary ephemeris files with any endianess by automatically swaps the bytes when it performs read operations on the ephemeris file.

[ascl:1504.021] SOAP 2.0: Spot Oscillation And Planet 2.0

SOAP (Spot Oscillation And Planet) 2.0 simulates the effects of dark spots and bright plages on the surface of a rotating star, computing their expected radial velocity and photometric signatures. It includes the convective blueshift and its inhibition in active regions.

[ascl:1504.020] BGLS: A Bayesian formalism for the generalised Lomb-Scargle periodogram

BGLS calculates the Bayesian Generalized Lomb-Scargle periodogram. It takes as input arrays with a time series, a dataset and errors on those data, and returns arrays with sampled periods and the periodogram values at those periods.

[ascl:1504.019] LineProf: Line Profile Indicators

LineProf implements a series of line-profile analysis indicators and evaluates its correlation with RV data. It receives as input a list of Cross-Correlation Functions and an optional list of associated RV. It evaluates the line-profile according to the indicators and compares it with the computed RV if no associated RV is provided, or with the provided RV otherwise.

[ascl:1504.018] D3PO: Denoising, Deconvolving, and Decomposing Photon Observations

D3PO (Denoising, Deconvolving, and Decomposing Photon Observations) addresses the inference problem of denoising, deconvolving, and decomposing photon observations. Its primary goal is the simultaneous but individual reconstruction of the diffuse and point-like photon flux given a single photon count image, where the fluxes are superimposed. A hierarchical Bayesian parameter model is used to discriminate between morphologically different signal components, yielding a diffuse and a point-like signal estimate for the photon flux components.

[ascl:1504.017] JWFront: Wavefronts and Light Cones for Kerr Spacetimes

JWFront visualizes wavefronts and light cones in general relativity. The interactive front-end allows users to enter the initial position values and choose the values for mass and angular momentum per unit mass. The wavefront animations are available in 2D and 3D; the light cones are visualized using the coordinate systems (t, x, y) or (t, z, x). JWFront can be easily modified to simulate wavefronts and light cones for other spacetime by providing the Christoffel symbols in the program.

[ascl:1504.016] MRrelation: Posterior predictive mass distribution

MRrelation calculates the posterior predictive mass distribution for an individual planet. The probabilistic mass-radius relationship (M-R relation) is evaluated within a Bayesian framework, which both quantifies this intrinsic dispersion and the uncertainties on the M-R relation parameters.

[ascl:1504.015] IGMtransmission: Transmission curve computation

IGMtransmission is a Java graphical user interface that implements Monte Carlo simulations to compute the corrections to colors of high-redshift galaxies due to intergalactic attenuation based on current models of the Intergalactic Medium. The effects of absorption due to neutral hydrogen are considered, with particular attention to the stochastic effects of Lyman Limit Systems. Attenuation curves are produced, as well as colors for a wide range of filter responses and model galaxy spectra. Photometric filters are included for the Hubble Space Telescope, the Keck telescope, the Mt. Palomar 200-inch, the SUBARU telescope and UKIRT; alternative filter response curves and spectra may be readily uploaded.

[ascl:1504.014] abcpmc: Approximate Bayesian Computation for Population Monte-Carlo code

abcpmc is a Python Approximate Bayesian Computing (ABC) Population Monte Carlo (PMC) implementation based on Sequential Monte Carlo (SMC) with Particle Filtering techniques. It is extendable with k-nearest neighbour (KNN) or optimal local covariance matrix (OLCM) pertubation kernels and has built-in support for massively parallelized sampling on a cluster using MPI.

[ascl:1504.013] kozai: Hierarchical triple systems evolution

The kozai Python package evolves hierarchical triple systems in the secular approximation. As its name implies, the kozai package is useful for studying Kozai-Lidov oscillations. The kozai package can represent and evolve hierarchical triples using either the Delaunay orbital elements or the angular momentum and eccentricity vectors. kozai contains functions to calculate the period of Kozai-Lidov oscillations and the maximum eccentricity reached; it also contains a module to study octupole order effects by averaging over individual Kozai-Lidov oscillations.

[ascl:1504.012] DPI: Symplectic mapping for binary star systems for the Mercury software package

DPI is a FORTRAN77 library that supplies the symplectic mapping method for binary star systems for the Mercury N-Body software package (ascl:1201.008). The binary symplectic mapping is implemented as a hybrid symplectic method that allows close encounters and collisions between massive bodies and is therefore suitable for planetary accretion simulations.

[ascl:1504.011] samiDB: A Prototype Data Archive for Big Science Exploration

samiDB is an archive, database, and query engine to serve the spectra, spectral hypercubes, and high-level science products that make up the SAMI Galaxy Survey. Based on the versatile Hierarchical Data Format (HDF5), samiDB does not depend on relational database structures and hence lightens the setup and maintenance load imposed on science teams by metadata tables. The code, written in Python, covers the ingestion, querying, and exporting of data as well as the automatic setup of an HTML schema browser. samiDB serves as a maintenance-light data archive for Big Science and can be adopted and adapted by science teams that lack the means to hire professional archivists to set up the data back end for their projects.

[ascl:1504.010] CosmoTransitions: Cosmological Phase Transitions

CosmoTransitions analyzes early-Universe finite-temperature phase transitions with multiple scalar fields. The code enables analysis of the phase structure of an input theory, determines the amount of supercooling at each phase transition, and finds the bubble-wall profiles of the nucleated bubbles that drive the transitions.

[ascl:1504.009] Self-lensing binary code with Markov chain

The self-lensing binary code with Markov chain code was used to analyze the self-lensing binary system KOI-3278. It includes the MCMC modeling and the key figures.

[ascl:1504.008] MCSpearman: Monte Carlo error analyses of Spearman's rank test

Spearman’s rank correlation test is commonly used in astronomy to discern whether a set of two variables are correlated or not. Unlike most other quantities quoted in astronomical literature, the Spearman’s rank correlation coefficient is generally quoted with no attempt to estimate the errors on its value. This code implements a number of Monte Carlo based methods to estimate the uncertainty on the Spearman’s rank correlation coefficient.

[ascl:1504.007] WebbPSF: James Webb Space Telescope PSF Simulation Tool

WebbPSF provides a PSF simulation tool in a flexible and easy-to-use software package implemented in Python. Functionality includes support for spectroscopic modes of JWST NIRISS, MIRI, and NIRSpec, including modeling of slit losses and diffractive line spread functions.

[ascl:1504.006] drive-casa: Python interface for CASA scripting

drive-casa provides a Python interface for scripting of CASA (ascl:1107.013) subroutines from a separate Python process, allowing for utilization alongside other Python packages which may not easily be installed into the CASA environment. This is particularly useful for embedding use of CASA subroutines within a larger pipeline. drive-casa runs plain-text casapy scripts directly; alternatively, the package includes a set of convenience routines which try to adhere to a consistent style and make it easy to chain together successive CASA reduction commands to generate a command-script programmatically.

[ascl:1504.005] chimenea: Multi-epoch radio-synthesis data imaging

Chimenea implements an heuristic algorithm for automated imaging of multi-epoch radio-synthesis data. It generates a deep image via an iterative Clean subroutine performed on the concatenated visibility set and locates steady sources in the field of view. The code then uses this information to apply constrained and then unconstrained (i.e., masked/open-box) Cleans to the single-epoch observations. This obtains better results than if the single-epoch data had been processed independently without prior knowledge of the sky-model. The chimenea pipeline is built upon CASA (ascl:1107.013) subroutines, interacting with the CASA environment via the drive-casa (ascl:1504.006) interface layer.

[ascl:1504.004] HOTPANTS: High Order Transform of PSF ANd Template Subtraction

HOTPANTS (High Order Transform of PSF ANd Template Subtraction) implements the Alard 1999 algorithm for image subtraction. It photometrically aligns one input image with another after they have been astrometrically aligned.

[ascl:1504.003] EsoRex: ESO Recipe Execution Tool

EsoRex (ESO Recipe Execution Tool) lists, configures, and executes Common Pipeline Library (CPL) (ascl:1402.010) recipes from the command line. Its features include automatically generating configuration files, recursive recipe-path searching, command line and configuration file parameters, and recipe product naming control, among many others.

[ascl:1504.002] SPA: Solar Position Algorithm

The Solar Position Algorithm (SPA) calculates the solar zenith and azimuth angles in the period from the year -2000 to 6000, with uncertainties of +/- 0.0003 degrees based on the date, time, and location on Earth. SPA is implemented in C; in addition to being available for download, an online calculator using this code is available at https://www.nrel.gov/midc/solpos/spa.html.

[ascl:1504.001] UPMASK: Unsupervised Photometric Membership Assignment in Stellar Clusters

UPMASK, written in R, performs membership assignment in stellar clusters. It uses photometry and spatial positions, but can take into account other types of data. UPMASK takes into account arbitrary error models; the code is unsupervised, data-driven, physical-model-free and relies on as few assumptions as possible. The approach followed for membership assessment is based on an iterative process, principal component analysis, a clustering algorithm and a kernel density estimation.

[ascl:1503.011] VESPA: False positive probabilities calculator

Validation of Exoplanet Signals using a Probabilistic Algorithm (VESPA) calculates false positive probabilities and statistically validates transiting exoplanets. Written in Python, it uses isochrones [ascl:1503.010] and the package simpledist.

[ascl:1503.010] isochrones: Stellar model grid package

Isochrones, written in Python, simplifies common tasks often done with stellar model grids, such as simulating synthetic stellar populations, plotting evolution tracks or isochrones, or estimating the physical properties of a star given photometric and/or spectroscopic observations.

[ascl:1503.009] GSD: Global Section Datafile access library

The GSD library reads data written in the James Clerk Maxwell Telescope GSD format. This format uses the General Single-Dish Data model and was used at the JCMT until 2005. The library provides an API to open GSD files and read their contents. The content of the data files is self-describing and the library can return the type and name of any component. The library is used by SPECX (ascl:1310.008), JCMTDR (ascl:1406.019) and COADD (ascl:1411.020). The SMURF (ascl:1310.007) package can convert GSD heterodyne data files to ACSIS format using this library.

[ascl:1503.008] pYSOVAR: Lightcurves analysis

The pYSOVAR code calculates properties for a stack of lightcurves, including simple descriptive statistics (mean, max, min, ...), timing (e.g. Lomb-Scargle periodograms), variability indixes (e.g. Stetson), and color properties (e.g. slope in the color-magnitude diagram). The code is written in python and is closely integrated with astropy tables. Initially, pYSOVAR was written specifically for the analysis of two clusters in the YSOVAR project, using the (not publicly released) YSOVAR database as an input. Additional functionality has been added and the code has become more general; it is now useful for other clusters in the YSOVAR dataset or for other projects that have similar data (lightcurves in one or more bands with a few hundred points for a few thousand objects), though may not work out-of-the-box for different datasets.

[ascl:1503.007] UniPOPS: Unified data reduction suite

UniPOPS, a suite of programs and utilities developed at the National Radio Astronomy Observatory (NRAO), reduced data from the observatory's single-dish telescopes: the Tucson 12-m, the Green Bank 140-ft, and archived data from the Green Bank 300-ft. The primary reduction programs, 'line' (for spectral-line reduction) and 'condar' (for continuum reduction), used the People-Oriented Parsing Service (POPS) as the command line interpreter. UniPOPS unified previous analysis packages and provided new capabilities; development of UniPOPS continued within the NRAO until 2004 when the 12-m was turned over to the Arizona Radio Observatory (ARO). The submitted code is version 3.5 from 2004, the last supported by the NRAO.

[ascl:1503.006] AMADA: Analysis of Multidimensional Astronomical DAtasets

AMADA allows an iterative exploration and information retrieval of high-dimensional data sets. This is done by performing a hierarchical clustering analysis for different choices of correlation matrices and by doing a principal components analysis in the original data. Additionally, AMADA provides a set of modern visualization data-mining diagnostics. The user can switch between them using the different tabs.

[ascl:1503.005] dust: Dust scattering and extinction in the X-ray

Written in Python, dust calculates X-ray dust scattering and extinction in the intergalactic and local interstellar media.

[ascl:1503.004] HELIOS-K: Opacity Calculator for Radiative Transfer

HELIOS-K is an opacity calculator for exoplanetary atmospheres. It takes a line list as an input and computes the line shapes of an arbitrary number of spectral lines (~millions to billions). HELIOS-K is capable of computing 100,000 spectral lines in 1 second; it is written in CUDA, is optimized for graphics processing units (GPUs), and can be used with the HELIOS radiative transfer code (ascl:1807.009).

[ascl:1503.003] TAME: Tool for Automatic Measurement of Equivalent-width

TAME measures the equivalent width (EWs) in high-resolution spectra. Written by IDL, TAME provides the EWs of spectral lines by profile fitting in an automatic or interactive mode and is reliable for measuring EWs in a spectrum with a spectral resolution of R ≳ 20000. It offers an interactive mode for more flexible measurement of the EW and a fully automatic mode that can simultaneously measure the EWs for a large set of lines.

[ascl:1503.002] Galax2d: 2D isothermal Euler equations solver

Galax2d computes the 2D stationary solution of the isothermal Euler equations of gas dynamics in a rotating galaxy with a weak bar. The gravitational potential represents a weak bar and controls the flow. A damped Newton method solves the second-order upwind discretization of the equations for a steady-state solution, using a consistent linearization and a direct solver. The code can be applied as a tool for generating flow models if used on not too fine meshes, up to 256 by 256 cells for half a disk in polar coordinates.

[ascl:1503.001] K2flix: Kepler pixel data visualizer

K2flix makes it easy to inspect the CCD pixel data obtained by NASA's Kepler space telescope. The two-wheeled extended Kepler mission, K2, is affected by new sources of systematics, including pointing jitter and foreground asteroids, that are easier to spot by eye than by algorithm. The code takes Kepler's Target Pixel Files (TPF) as input and turns them into contrast-stretched animated gifs or MPEG-4 movies. K2flix can be used both as a command-line tool or using its Python API.

[ascl:1502.023] ROBOSPECT: Width fitting program

ROBOSPECT, written in C, automatically measures and deblends line equivalent widths for absorption and emission spectra. ROBOSPECT should not be used for stars with spectra in which there is no discernible continuum over large wavelength regions, nor for the most carbon-enhanced stars for which spectral synthesis would be favored. Although ROBOSPECT was designed for metal-poor stars, it is capable of fitting absorption and emission features in a variety of astronomical sources.

[ascl:1502.022] AstroLines: Astrophysical line list generator in the H-band

AstroLines adjusts spectral line parameters (gf and damping constant) starting from an initial line list. Written in IDL and tailored to the APO Galactic Evolution Experiment (APOGEE), it runs a slightly modified version of MOOG (ascl:1202.009) to compare synthetic spectra with FTS spectra of the Sun and Arcturus.

[ascl:1502.021] MaLTPyNT: Quick look timing analysis for NuSTAR data

MaLTPyNT (Matteo's Libraries and Tools in Python for NuSTAR Timing) provides a quick-look timing analysis of NuSTAR data, properly treating orbital gaps and exploiting the presence of two independent detectors by using the cospectrum as a proxy for the power density spectrum. The output of the analysis is a cospectrum, or a power density spectrum, that can be fitted with XSPEC (ascl:9910.005) or ISIS (ascl:1302.002). The software also calculates time lags. Though written for NuSTAR data, MaLTPyNT can also perform standard spectral analysis on X-ray data from other satellite such as XMM-Newton and RXTE.

[ascl:1502.020] ketu: Exoplanet candidate search code

ketu, written in Python, searches K2 light curves for evidence of exoplanets; the code simultaneously fits for systematic effects caused by small (few-pixel) drifts in the telescope pointing and other spacecraft issues and the transit signals of interest. Though more computationally expensive than standard search algorithms, it can be efficiently implemented and used to discover transit signals.

[ascl:1502.019] XPCell: Convective plasma cells simulator

XPCell simulates convective plasma cells. The program is implemented in two versions, one using GNUPLOT and the second OpenGL. XPCell offers a GUI to introduce the parameter required by the program.

[ascl:1502.018] XFGLENSES: Gravitational lens visualizer

XFGL visualizes gravitational lenses. It has an XFORM GUI and is completely interactive with the mouse. It uses OpenGL for the simulations.

[ascl:1502.017] AMIsurvey: Calibration and imaging pipeline for radio data

AMIsurvey is a fully automated calibration and imaging pipeline for data from the AMI-LA radio observatory; it has two key dependencies. The first is drive-ami, included in this entry. Drive-ami is a Python interface to the specialized AMI-REDUCE calibration pipeline, which applies path delay corrections, automatic flags for interference, pointing errors, shadowing and hardware faults, applies phase and amplitude calibrations, Fourier transforms the data into the frequency domain, and writes out the resulting data in uvFITS format. The second is chimenea, which implements an automated imaging algorithm to convert the calibrated uvFITS into science-ready image maps. AMIsurvey links the calibration and imaging stages implemented within these packages together, configures the chimenea algorithm with parameters appropriate to data from AMI-LA, and provides a command-line interface.

[ascl:1502.016] libnova: Celestial mechanics, astrometry and astrodynamics library

libnova is a general purpose, double precision, celestial mechanics, astrometry and astrodynamics library. Among many other calculations, it can calculate aberration, apparent position, proper motion, planetary positions, orbit velocities and lengths, angular separation of bodies, and hyperbolic motion of bodies.

[ascl:1502.015] Camelus: Counts of Amplified Mass Elevations from Lensing with Ultrafast Simulations

Camelus provides a prediction on weak lensing peak counts from input cosmological parameters. Written in C, it samples halos from a mass function and assigns a profile, carries out ray-tracing simulations, and then counts peaks from ray-tracing maps. The creation of the ray-tracing simulations requires less computing time than N-body runs and the results is in good agreement with full N-body simulations.

[ascl:1502.014] Magnetron: Fitting bursts from magnetars

Magnetron, written in Python, decomposes magnetar bursts into a superposition of small spike-like features with a simple functional form, where the number of model components is itself part of the inference problem. Markov Chain Monte Carlo (MCMC) sampling and reversible jumps between models with different numbers of parameters are used to characterize the posterior distributions of the model parameters and the number of components per burst.

[ascl:1502.013] Rabacus: Analytic Cosmological Radiative Transfer Calculations

Rabacus performs analytic radiative transfer calculations in simple geometries relevant to cosmology and astrophysics; it also contains tools to calculate cosmological quantities such as the power spectrum and mass function. With core routines written in Fortran 90 and then wrapped in Python, the execution speed is thousands of times faster than equivalent routines written in pure Python.

[ascl:1502.012] SPHGR: Smoothed-Particle Hydrodynamics Galaxy Reduction

SPHGR (Smoothed-Particle Hydrodynamics Galaxy Reduction) is a python based open-source framework for analyzing smoothed-particle hydrodynamic simulations. Its basic form can run a baryonic group finder to identify galaxies and a halo finder to identify dark matter halos; it can also assign said galaxies to their respective halos, calculate halo & galaxy global properties, and iterate through previous time steps to identify the most-massive progenitors of each halo and galaxy. Data about each individual halo and galaxy is collated and easy to access.

SPHGR supports a wide range of simulations types including N-body, full cosmological volumes, and zoom-in runs. Support for multiple SPH code outputs is provided by pyGadgetReader (ascl:1411.001), mainly Gadget (ascl:0003.001) and TIPSY (ascl:1111.015).

[ascl:1502.011] PolyChord: Nested sampling for cosmology

PolyChord is a Bayesian inference tool for the simultaneous calculation of evidences and sampling of posterior distributions. It is a variation on John Skilling's Nested Sampling, utilizing Slice Sampling to generate new live points. It performs well on moderately high dimensional (~100s D) posterior distributions, and can cope with arbitrary degeneracies and multimodality.

[ascl:1502.010] nbody6tt: Tidal tensors in N-body simulations

nbody6tt, based on Aarseth's nbody6 (ascl:1102.006) code, includes the treatment of complex galactic tides in a direct N-body simulation of a star cluster through the use of tidal tensors (tt) and offers two complementary methods. The first allows consideration of any kind of galaxy and orbit, thus offering versatility; this method cannot be used to study tidal debris, as it relies on the tidal approximation (linearization of the tidal force). The second method is not limited by this and does not require a galaxy simulation; the user defines a numerical function which takes position and time as arguments, and the galactic potential is returned. The space and time derivatives of the potential are used to (i) integrate the motion of the cluster on its orbit in the galaxy (starting from user-defined initial position and velocity vector), and (ii) compute the tidal acceleration on the stars.

[ascl:1502.009] HDS: Hierarchical Data System

The Hierarchical Data System (HDS) is a file-based hierarchical data system designed for the storage of a wide variety of information. It is particularly suited to the storage of large multi-dimensional arrays (with their ancillary data) where efficient access is needed. It is a key component of the Starlink software collection (ascl:1110.012) and is used by the Starlink N-Dimensional Data Format (NDF) library (ascl:1411.023).

HDS organizes data into hierarchies, broadly similar to the directory structure of a hierarchical filing system, but contained within a single HDS container file. The structures stored in these files are self-describing and flexible; HDS supports modification and extension of structures previously created, as well as functions such as deletion, copying, and renaming. All information stored in HDS files is portable between the machines on which HDS is implemented. Thus, there are no format conversion problems when moving between machines. HDS can write files in a private binary format (version 4), or be layered on top of HDF5 (version 5).

[ascl:1502.008] KAPPA: Optically thin spectra synthesis for non-Maxwellian kappa-distributions

Based on the freely available CHIANTI (ascl:9911.004) database and software, KAPPA synthesizes line and continuum spectra from the optically thin spectra that arise from collisionally dominated astrophysical plasmas that are the result of non-Maxwellian κ-distributions detected in the solar transition region and flares. Ionization and recombination rates together with the ionization equilibria are provided for a range of κ values. Distribution-averaged collision strengths for excitation are obtained by an approximate method for all transitions in all ions available within CHIANTI; KAPPA also offers tools for calculating synthetic line and continuum intensities.

[ascl:1502.007] PyBDSF: Python Blob Detection and Source Finder

PyBDSF (Python Blob Detector and Source Finder, formerly PyBDSM) decomposes radio interferometry images into sources and makes their properties available for further use. PyBDSF can decompose an image into a set of Gaussians, shapelets, or wavelets as well as calculate spectral indices and polarization properties of sources and measure the psf variation across an image. PyBDSF uses an interactive environment based on CASA (ascl:1107.013); PyBDSF may also be used in Python scripts.

[ascl:1502.006] Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations

Montblanc, written in Python, is a GPU implementation of the Radio interferometer measurement equation (RIME) in support of the Bayesian inference for radio observations (BIRO) technique. The parameter space that BIRO explores results in tens of thousands of computationally expensive RIME evaluations before reduction to a single X2 value. The RIME is calculated over four dimensions, time, baseline, channel and source and the values in this 4D space can be independently calculated; therefore, the RIME is particularly amenable to a parallel implementation accelerated by Graphics Programming Units (GPUs). Montblanc is implemented for NVIDIA's CUDA architecture and outperforms MeqTrees (ascl:1209.010) and OSKAR.

[ascl:1502.005] PARSEC: PARametrized Simulation Engine for Cosmic rays

PARSEC (PARametrized Simulation Engine for Cosmic rays) is a simulation engine for fast generation of ultra-high energy cosmic ray data based on parameterizations of common assumptions of UHECR origin and propagation. Implemented are deflections in unstructured turbulent extragalactic fields, energy losses for protons due to photo-pion production and electron-pair production, as well as effects from the expansion of the universe. Additionally, a simple model to estimate propagation effects from iron nuclei is included. Deflections in the Galactic magnetic field are included using a matrix approach with precalculated lenses generated from backtracked cosmic rays. The PARSEC program is based on object oriented programming paradigms enabling users to extend the implemented models and is steerable with a graphical user interface.

[ascl:1502.004] ADAM: All-Data Asteroid Modeling

ADAM (All-Data Asteroid Modeling) models asteroid shape reconstruction from observations. Developed in MATLAB with core routines in C, its features include general nonconvex and non-starlike parametric 3D shape supports and reconstruction of asteroid shape from any combination of lightcurves, adaptive optics images, HST/FGS data, disk-resolved thermal images, interferometry, and range-Doppler radar images. ADAM does not require boundary contour extraction for reconstruction and can be run in parallel.

[ascl:1502.003] N-GenIC: Cosmological structure initial conditions

N-GenIC is an initial conditions code for cosmological structure formation that can be used to set-up random N-body realizations of Gaussian random fields with a prescribed power spectrum in a homogeneously sampled periodic box. The code creates cosmological initial conditions based on the Zeldovich approximation, in a format directly compatible with GADGET (ascl:0003.001) or AREPO (ascl:1909.010).

[ascl:1502.002] OpenOrb: Open-source asteroid orbit computation software

OpenOrb (OOrb) contains tools for rigorously estimating the uncertainties resulting from the inverse problem of computing orbital elements using scarce astrometry. It uses the least-squares method and also contains both Monte-Carlo (MC) and Markov-Chain MC versions of the statistical ranging method. Ranging obtains sampled, non-Gaussian orbital-element probability-density functions and is optimized for cases where the amount of astrometry is scarce or spans a relatively short time interval.

[ascl:1502.001] RH 1.5D: Polarized multi-level radiative transfer with partial frequency distribution

RH 1.5D performs Zeeman multi-level non-local thermodynamical equilibrium calculations with partial frequency redistribution for an arbitrary amount of chemical species. Derived from the RH code and written in C, it calculates spectra from 3D, 2D or 1D atmospheric models on a column-by-column basis (or 1.5D). It includes optimization features to speed up or improve convergence, which are particularly useful in dynamic models of chromospheres. While one should be aware of its limitations, the calculation of spectra using the 1.5D or column-by-column is a good approximation in many cases, and generally allows for faster convergence and more flexible methods of improving convergence. RH 1.5D scales well to at least tens of thousands of CPU cores.

[ascl:1501.016] Colossus: COsmology, haLO, and large-Scale StrUcture toolS

Colossus is a collection of Python modules for cosmology and dark matter halos calculations. It performs cosmological calculations with an emphasis on structure formation applications, implements general and specific density profiles, and provides a large range of models for the concentration-mass relation, including a conversion to arbitrary mass definitions.

[ascl:1501.015] Exoplanet: Trans-dimensional MCMC method for exoplanet discovery

Exoplanet determines the posterior distribution of exoplanets by use of a trans-dimensional Markov Chain Monte Carlo method within Nested Sampling. This method finds the posterior distribution in a single run rather than requiring multiple runs with trial values.

[ascl:1501.014] GalPaK 3D: Galaxy parameters and kinematics extraction from 3D data

GalPaK 3D extracts the intrinsic (i.e. deconvolved) galaxy parameters and kinematics from any 3-dimensional data. The algorithm uses a disk parametric model with 10 free parameters (which can also be fixed independently) and a MCMC approach with non-traditional sampling laws in order to efficiently probe the parameter space. More importantly, it uses the knowledge of the 3-dimensional spread-function to return the intrinsic galaxy properties and the intrinsic data-cube. The 3D spread-function class is flexible enough to handle any instrument.

GalPaK 3D can simultaneously constrain the kinematics and morphological parameters of (non-merging, i.e. regular) galaxies observed in non-optimal seeing conditions and can also be used on AO data or on high-quality, high-SNR data to look for non-axisymmetric structures in the residuals.

[ascl:1501.013] Molecfit: Telluric absorption correction tool

Molecfit corrects astronomical observations for atmospheric absorption features based on fitting synthetic transmission spectra to the astronomical data, which saves a significant amount of valuable telescope time and increases the instrumental efficiency. Molecfit can also estimate molecular abundances, especially the water vapor content of the Earth’s atmosphere. The tool can be run from a command-line or more conveniently through a GUI.

[ascl:1501.012] Exorings: Exoring modelling software

Exorings, written in Python, contains tools for displaying and fitting giant extrasolar planet ring systems; it uses FITS formatted data for input.

[ascl:1501.011] transfer: The Sloan Digital Sky Survey Data Transfer Infrastructure

The Sloan Digital Sky Survey (SDSS) produces large amounts of data daily. transfer, written in Python, provides the effective automation needed for daily data transfer operations and management and operates essentially free of human intervention. This package has been tested and used successfully for several years.

[ascl:1501.010] PythonPhot: Simple DAOPHOT-type photometry in Python

PythonPhot is a simple Python translation of DAOPHOT-type (ascl:1104.011) photometry procedures from the IDL AstroLib (Landsman 1993), including aperture and PSF-fitting algorithms, with a few modest additions to increase functionality and ease of use. These codes allow fast, easy, and reliable photometric measurements and are currently used in the Pan-STARRS supernova pipeline and the HST CLASH/CANDELS supernova analysis.

[ascl:1501.009] BIANCHI: Bianchi VIIh Simulations

BIANCHI provides functionality to support the simulation of Bianchi Type VIIh induced temperature fluctuations in CMB maps of a universe with shear and rotation. The implementation is based on the solutions to the Bianchi models derived by Barrow et al. (1985), which do not incorporate any dark energy component. Functionality is provided to compute the induced fluctuations on the sphere directly in either real or harmonic space.

[ascl:1501.008] Enrico: Python package to simplify Fermi-LAT analysis

Enrico analyzes Fermi data. It produces spectra (model fit and flux points), maps and lightcurves for a target by editing a config file and running a python script which executes the Fermi science tool chain.

[ascl:1501.007] LP-VIcode: La Plata Variational Indicators Code

LP-VIcode computes variational chaos indicators (CIs) quickly and easily. The following CIs are included:

  • Lyapunov Indicators, also known as Lyapunov Characteristic Exponents, Lyapunov Characteristic Numbers or Finite Time Lyapunov Characteristic Numbers (LIs)
  • Mean Exponential Growth factor of Nearby Orbits (MEGNO)
  • Slope Estimation of the largest Lyapunov Characteristic Exponent (SElLCE)
  • Smaller ALignment Index (SALI)
  • Generalized ALignment Index (GALI)
  • Fast Lyapunov Indicator (FLI)
  • Orthogonal Fast Lyapunov Indicator (OFLI)
  • Spectral Distance (SD)
  • dynamical Spectra of Stretching Numbers (SSNs)
  • Relative Lyapunov Indicator (RLI)

[ascl:1501.006] PsrPopPy: Pulsar Population Modelling Programs in Python

PsrPopPy is a Python implementation of the Galactic population and evolution of radio pulsars modelling code PSRPOP (ascl:1107.019).

[ascl:1501.005] DECA: Decomposition of images of galaxies

DECA performs photometric analysis of images of disk and elliptical galaxies having a regular structure. It is written in Python and combines the capabilities of several widely used packages for astronomical data processing such as IRAF (ascl:9911.002), SExtractor (ascl:1010.064), and the GALFIT (ascl:1104.010) code to perform two-dimensional decomposition of galaxy images into several photometric components (bulge+disk). DECA can be applied to large samples of galaxies with different orientations with respect to the line of sight (including edge-on galaxies) and requires minimum human intervention.

[ascl:1501.004] dst: Polarimeter data destriper

Dst is a fully parallel Python destriping code for polarimeter data; destriping is a well-established technique for removing low-frequency correlated noise from Cosmic Microwave Background (CMB) survey data. The software destripes correctly formatted HDF5 datasets and outputs hitmaps, binned maps, destriped maps and baseline arrays.

[ascl:1501.003] python-qucs: Python package for automating QUCS simulations

Characterization of the frequency response of coherent radiometric receivers is a key element in estimating the flux of astrophysical emissions, since the measured signal depends on the convolution of the source spectral emission with the instrument band shape. Python-qucs automates the process of preparing input data, running simulations and exporting results of QUCS (Quasi Universal Circuit Simulator) simulations.

[ascl:1501.002] NIGO: Numerical Integrator of Galactic Orbits

NIGO (Numerical Integrator of Galactic Orbits) predicts the orbital evolution of test particles moving within a fully-analytical gravitational potential generated by a multi-component galaxy. The code can simulate the orbits of stars in elliptical and disc galaxies, including non-axisymmetric components represented by a spiral pattern and/or rotating bar(s).

[ascl:1501.001] PynPoint: Exoplanet image data analysis

PynPoint uses principal component analysis to detect and estimate the flux of exoplanets in two-dimensional imaging data. It processes many, typically several thousands, of frames to remove the light from the star so as to reveal the companion planet.

The code has been significantly rewritten and expanded; please see ascl:1812.010.

[ascl:1412.014] SOPHIA: Simulations Of Photo Hadronic Interactions in Astrophysics

SOPHIA (Simulations Of Photo Hadronic Interactions in Astrophysics) solves problems connected to photohadronic processes in astrophysical environments and can also be used for radiation and background studies at high energy colliders such as LEP2 and HERA, as well as for simulations of photon induced air showers. SOPHIA implements well established phenomenological models, symmetries of hadronic interactions in a way that describes correctly the available exclusive and inclusive photohadronic cross section data obtained at fixed target and collider experiments.

[ascl:1412.013] CRPropa: Numerical tool for the propagation of UHE cosmic rays, gamma-rays and neutrinos

CRPropa computes the observable properties of UHECRs and their secondaries in a variety of models for the sources and propagation of these particles. CRPropa takes into account interactions and deflections of primary UHECRs as well as propagation of secondary electromagnetic cascades and neutrinos. CRPropa makes use of the public code SOPHIA (ascl:1412.014), and the TinyXML, CFITSIO (ascl:1010.001), and CLHEP libraries. A major advantage of CRPropa is its modularity, which allows users to implement their own modules adapted to specific UHECR propagation models. An updated version, CRPropa3 (ascl:2208.016), is available.

[ascl:1412.012] GeoTOA: Geocentric TOA tools

GeoTOA computes the pulse times of arrival (TOAs) at an observatory (or spacecraft) from unbinned Fermi LAT data. Written in Python, the software requires NumPy, matplotlib, SciPy, Fermitools (ascl:1905.011), and Tempo2 (ascl:1210.015).

[ascl:1412.011] TraP: Transients discovery pipeline for image-plane surveys

The TraP is a pipeline for detecting and responding to transient and variable sources in a stream of astronomical images. Images are initially processed using a pure-Python source-extraction package, PySE (ascl:1805.026), which is bundled with the TraP. Source positions and fluxes are then loaded into a SQL database for association and variability detection. The database structure allows for estimation of past upper limits on newly detected sources, and for forced fitting of previously detected sources which have since dropped below the blind-extraction threshold. Developed with LOFAR data in mind, the TraP has been used with data from other radio observatories.

[ascl:1412.010] MMAS: Make Me A Star

Make Me A Star (MMAS) quickly generates stellar collision remnants and can be used in combination with realistic dynamical simulations of star clusters that include stellar collisions. The code approximates the merger process (including shock heating, hydrodynamic mixing, mass ejection, and angular momentum transfer) with simple algorithms based on conservation laws and a basic qualitative understanding of the hydrodynamics. These simple models agree very well with those from SPH (smoothed particle hydrodynamics) calculations of stellar collisions, and the subsequent stellar evolution of these models also matches closely that of the more accurate hydrodynamic models.

[ascl:1412.009] URCHIN: Reverse ray tracer

URCHIN is a Smoothed Particle Hydrodynamics (SPH) reverse ray tracer (i.e. from particles to sources). It calculates the amount of shielding from a uniform background that each particle experiences. Preservation of the adaptive density field resolution present in many gas dynamics codes and uniform sampling of gas resolution elements with rays are two of the benefits of URCHIN; it also offers preservation of Galilean invariance, high spectral resolution, and preservation of the standard uniform UV background in optically thin gas.

[ascl:1412.008] Hrothgar: MCMC model fitting toolkit

Hrothgar is a parallel minimizer and Markov Chain Monte Carlo generator. It has been used to solve optimization problems in astrophysics (galaxy cluster mass profiles) as well as in experimental particle physics (hadronic tau decays).

[ascl:1412.007] PIAO: Python spherIcAl Overdensity code

PIAO is an efficient memory-controlled Python code that uses the standard spherical overdensity (SO) algorithm to identify halos. PIAO employs two additional parameters besides the overdensity Δc. The first is the mesh-box size, which splits the whole simulation box into smaller ones then analyzes them one-by-one, thereby overcoming a possible memory limitation problem that can occur when dealing with high-resolution, large-volume simulations. The second is the smoothed particle hydrodynamics (SPH) neighbors number, which is used for the SPH density calculation.

[ascl:1412.006] HMF: Halo Mass Function calculator

HMF calculates the Halo Mass Function (HMF) given any set of cosmological parameters and fitting function and serves as the backend for the web application HMFcalc. Written in Python, it allows for dynamic accurate calculation of the transfer function with CAMB (ascl:1102.026) and efficient and self-consistent parameter updates. HMF offers exploration of the effects of cosmological parameters, redshift and fitting function on the predicted HMF.

[ascl:1412.005] BRUCE/KYLIE: Pulsating star spectra synthesizer

BRUCE and KYLIE, written in Fortran 77, synthesize the spectra of pulsating stars. BRUCE constructs a point-sampled model for the surface of a rotating, gravity-darkened star, and then subjects this model to perturbations arising from one or more non-radial pulsation modes. Departures from adiabaticity can be taken into account, as can the Coriolis force through adoption of the so-called traditional approximation. BRUCE writes out a time-sequence of perturbed surface models. This sequence is read in by KYLIE, which synthesizes disk-integrated spectra for the models by co-adding the specific intensity emanating from each visible point toward the observer. The specific intensity is calculated by interpolation in a large temperature-gravity-wavelength-angle grid of pre-calculated intensity spectra.

[ascl:1412.004] DAMIT: Database of Asteroid Models from Inversion Techniques

DAMIT (Database of Asteroid Models from Inversion Techniques) is a database of three-dimensional models of asteroids computed using inversion techniques; it provides access to reliable and up-to-date physical models of asteroids, i.e., their shapes, rotation periods, and spin axis directions. Models from DAMIT can be used for further detailed studies of individual objects as well as for statistical studies of the whole set. The source codes for lightcurve inversion routines together with brief manuals, sample lightcurves, and the code for the direct problem are available for download.

[ascl:1412.003] UTM: Universal Transit Modeller

The Universal Transit Modeller (UTM) is a light-curve simulator for all kinds of transiting or eclipsing configurations between arbitrary numbers of several types of objects, which may be stars, planets, planetary moons, and planetary rings. A separate fitting program, UFIT (Universal Fitter) is part of the UTM distribution and may be used to derive best fits to light-curves for any set of continuously variable parameters. UTM/UFIT is written in IDL code and its source is released in the public domain under the GNU General Public License.

[ascl:1412.002] Cheetah: Starspot modeling code

Cheetah models starspots in photometric data (lightcurves) by calculating the modulation of a light curve due to starspots. The main parameters of the program are the linear and quadratic limb darkening coefficients, stellar inclination, spot locations and sizes, and the intensity ratio of the spots to the stellar photosphere. Cheetah uses uniform spot contrast and the minimum number of spots needed to produce a good fit and ignores bright regions for the sake of simplicity.

[ascl:1412.001] SoFiA: Source Finding Application

SoFiA is a flexible source finding pipeline designed to detect and parameterize sources in 3D spectral-line data cubes. SoFiA combines several powerful source finding and parameterization algorithms, including wavelet denoising, spatial and spectral smoothing, source mask optimization, spectral profile fitting, and calculation of the reliability of detections. In addition to source catalogues in different formats, SoFiA can also generate a range of output data cubes and images, including source masks, moment maps, sub-cubes, position-velocity diagrams, and integrated spectra. The pipeline is controlled by simple parameter files and can either be invoked on the command line or interactively through a modern graphical user interface.

A reimplementation of this pipeline using OpenMPI, SoFiA 2 (ascl:2109.005), is available.

[ascl:1411.027] BKGE: Fermi-LAT Background Estimator

The Fermi-LAT Background Estimator (BKGE) is a publicly available open-source tool that can estimate the expected background of the Fermi-LAT for any observational conguration and duration. It produces results in the form of text files, ROOT files, gtlike source-model files (for LAT maximum likelihood analyses), and PHA I/II FITS files (for RMFit/XSpec spectral fitting analyses). Its core is written in C++ and its user interface in Python.

[ascl:1411.026] sic: Sparse Inpainting Code

sic (Sparse Inpainting Code) generates Gaussian, isotropic CMB realizations, masks them, and recovers the large-scale masked data using sparse inpainting; it is written in Fortran90.

[ascl:1411.025] SPT Lensing Likelihood: South Pole Telescope CMB lensing likelihood code

The SPT lensing likelihood code, written in Fortran90, performs a Gaussian likelihood based upon the lensing potential power spectrum using a file from CAMB (ascl:1102.026) which contains the normalization required to get the power spectrum that the likelihood call is expecting.

[ascl:1411.024] CGS3DR: UKIRT CGS3 data reduction software

CGS3DR is data reduction software for the UKIRT CGS3 mid-infrared grating spectrometer instrument. It includes a command-line interface and a GUI. The software, originally on VMS, was ported to Unix. It uses Starlink (ascl:1110.012) infrastructure libraries.

[ascl:1411.023] NDF: Extensible N-dimensional Data Format Library

The Extensible N-Dimensional Data Format (NDF) stores bulk data in the form of N-dimensional arrays of numbers. It is typically used for storing spectra, images and similar datasets with higher dimensionality. The NDF format is based on the Hierarchical Data System (HDS) and is extensible; not only does it provide a comprehensive set of standard ancillary items to describe the data, it can also be extended indefinitely to handle additional user-defined information of any type. The NDF library is used to read and write files in the NDF format. It is distributed with the Starlink software (ascl:1110.012).

[ascl:1411.022] Starlink Figaro: Starlink version of the Figaro data reduction software package

Starlink Figaro is an independently-maintained fork of Figaro (ascl:1203.013) that runs in the Starlink software environment (ascl:1110.012). It is a general-purpose data reduction package targeted mainly at optical/IR spectroscopy. It uses the NDF data format and the ADAM libraries for parameters and messaging.

[ascl:1411.021] POSTMORTEM: Visibility data reduction and map making package

POSTMORTEM is the visibility data reduction and map making package from MRAO (Mullard Radio Astronomy Observatory) and is used with the Ryle and CLFST telescopes at Cambridge. It contains sub-systems for nonitoring telescope performance, displaying and editing the visibility data, performing calibrations, removing flux from interfering bright sources, and map-making. It requires PGPLOT (ascl:1103.002), SLALIB (ascl:1403.025), and NAG numerical routines, all of which are distributed with the STARLINK software collection (ascl:1110.012) or available separately.

[ascl:1411.020] JCMT COADD: UKT14 continuum and photometry data reduction

COADD was used to reduce photometry and continuum data from the UKT14 instrument on the James Clerk Maxwell Telescope in the 1990s. The software can co-add multiple observations and perform sigma clipping and Kolmogorov-Smirnov statistical analysis. Additional information on the software is available in the JCMT Spring 1993 newsletter (large PDF).

[ascl:1411.019] Anmap: Image and data analysis

Anmap analyses and processes images and spectral data. Originally written for use in radio astronomy, much of its functionality is applicable to other disciplines; additional algorithms and analysis procedures allow direct use in, for example, NMR imaging and spectroscopy. Anmap emphasizes the analysis of data to extract quantitative results for comparison with theoretical models and/or other experimental data. To achieve this, Anmap provides a wide range of tools for analysis, fitting and modelling (including standard image and data processing algorithms). It also provides a powerful environment for users to develop their own analysis/processing tools either by combining existing algorithms and facilities with the very powerful command (scripting) language or by writing new routines in FORTRAN that integrate seamlessly with the rest of Anmap.

[ascl:1411.018] GPI Pipeline: Gemini Planet Imager Data Pipeline

The GPI data pipeline allows users to reduce and calibrate raw GPI data into spectral and polarimetric datacubes, and to apply various PSF subtraction methods to those data. Written in IDL and available in a compiled version, the software includes an integrated calibration database to manage reference files and an interactive data viewer customized for high contrast imaging that allows exploration and manipulation of data.

[ascl:1411.017] ECCSAMPLES: Bayesian Priors for Orbital Eccentricity

ECCSAMPLES solves the inverse cumulative density function (CDF) of a Beta distribution, sometimes called the IDF or inverse transform sampling. This allows one to sample from the relevant priors directly. ECCSAMPLES actually provides joint samples for both the eccentricity and the argument of periastron, since for transiting systems they display non-zero covariance.

[ascl:1411.016] Flicker: Mean stellar densities from flicker

Flicker calculates the mean stellar density of a star by inputting the flicker observed in a photometric time series. Written in Fortran90, its output may be used as an informative prior on stellar density when fitting transit light curves.

[ascl:1411.015] SPOTROD: Semi-analytic model for transits of spotted stars

SPOTROD is a model for planetary transits of stars with an arbitrary limb darkening law and a number of homogeneous, circular spots on their surface. It facilitates analysis of anomalies due to starspot eclipses, and is a free, open source implementation written in C with a Python API.

[ascl:1411.014] NAFE: Noise Adaptive Fuzzy Equalization

NAFE (Noise Adaptive Fuzzy Equalization) is an image processing method allowing for visualization of fine structures in SDO AIA high dynamic range images. It produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform.

[ascl:1411.013] NEAT: Nebular Empirical Analysis Tool

NEAT is a fully automated code which carries out a complete analysis of lists of emission lines to estimate the amount of interstellar extinction, calculate representative temperatures and densities, compute ionic abundances from both collisionally excited lines and recombination lines, and finally to estimate total elemental abundances using an ionization correction scheme. NEAT uses a Monte Carlo technique to robustly propagate uncertainties from line flux measurements through to the derived abundances.

[ascl:1411.012] util_2comp: Planck-based two-component dust model utilities

The util_2comp software utilities generate predictions of far-infrared Galactic dust emission and reddening based on a two-component dust emission model fit to Planck HFI, DIRBE and IRAS data from 100 GHz to 3000 GHz. These predictions and the associated dust temperature map have angular resolution of 6.1 arcminutes and are available over the entire sky. Implementations in IDL and Python are included.

[ascl:1411.011] PyMGC3: Finding stellar streams in the Galactic Halo using a family of Great Circle Cell counts methods

PyMGC3 is a Python toolkit to apply the Modified Great Circle Cell Counts (mGC3) method to search for tidal streams in the Galactic Halo. The code computes pole count maps using the full mGC3/nGC3/GC3 family of methods. The original GC3 method (Johnston et al., 1996) uses positional information to search for 'great-circle-cell structures'; mGC3 makes use of full 6D data and nGC3 uses positional and proper motion data.

[ascl:1411.010] Raga: Monte Carlo simulations of gravitational dynamics of non-spherical stellar systems

Raga (Relaxation in Any Geometry) is a Monte Carlo simulation method for gravitational dynamics of non-spherical stellar systems. It is based on the SMILE software (ascl:1308.001) for orbit analysis. It can simulate stellar systems with a much smaller number of particles N than the number of stars in the actual system, represent an arbitrary non-spherical potential with a basis-set or spline spherical-harmonic expansion with the coefficients of expansion computed from particle trajectories, and compute particle trajectories independently and in parallel using a high-accuracy adaptive-timestep integrator. Raga can also model two-body relaxation by local (position-dependent) velocity diffusion coefficients (as in Spitzer's Monte Carlo formulation) and adjust the magnitude of relaxation to the actual number of stars in the target system, and model the effect of a central massive black hole.

[ascl:1411.009] iDealCam: Interactive Data Reduction and Analysis for CanariCam

iDealCam is an IDL GUI toolkit for processing multi-extension FITS file produced by CanariCam, the facility mid-IR instrument of Gran Telescopio CANARIAS (GTC). iDealCam is optimized for CanariCam data, but is also compatible with data generated by other instruments using similar detectors and data format (e.g., Michelle and T-ReCS at Gemini). iDealCam provides essential capabilities to examine, reduce, and analyze data obtained in the standard imaging or polarimetric imaging mode of CanariCam.

[ascl:1411.008] galpy: Galactic dynamics package

galpy is a python package for galactic dynamics. It supports orbit integration in a variety of potentials, evaluating and sampling various distribution functions, and the calculation of action-angle coordinates for all static potentials.

[ascl:1411.007] segueSelect: SDSS/SEGUE selection function modelling

The Python package segueSelect automatically models the SDSS/SEGUE selection fraction -- the fraction of stars with good spectra -- as a continuous function of apparent magnitude for each plate. The selection function can be determined for any desired sample cuts in signal-to-noise ratio, u-g, r-i, and E(B-V). The package requires Pyfits (ascl:1207.009) and, for coordinate transformations, galpy (ascl:1411.008). It can calculate the KS probability that the spectropscopic sample was drawn from the underlying photometric sample with the model selection function, plot the cumulative distribution function in r-band apparent magnitude of the spectroscopic sample (red) and the photometric sample+selection-function-model for this plate, and, if galpy is installed, can transform velocities into the Galactic coordinate frame. The code can also determine the selection function for SEGUE K stars.

[ascl:1411.006] RC3 mosaicking pipeline: Creating mosaics for the RC3 Catalogue

The RC3 mosaicking pipeline creates color composite images and scientifically-calibrated FITS mosaics in all SDSS imaging bands for all the RC3 galaxies that lie within the survey’s footprint and on photographic plates taken by the Digitized Palomar Observatory Sky Survey (DPOSS) for the B, R, IR bands. The pipeline uses SExtractor (ascl:1010.064) for extraction and STIFF (ascl:1110.006) to generating color images. The mosaicking program uses a recursive algorithm for positional update first to correct the positional inaccuracy inherent in the RC3 catalog, then conducts the mosaicking procedure using the Astropy (ascl:1304.002) wrapper to IPAC's Montage (ascl:1010.036) software. The program is generalized into a pipeline that can be easily extended to future survey data or other source catalogs; an online interface is available at
http://lcdm.astro.illinois.edu/data/rc3/search.html.

[ascl:1411.005] HOPE: Just-in-time Python compiler for astrophysical computations

HOPE is a specialized Python just-in-time (JIT) compiler designed for numerical astrophysical applications. HOPE focuses on a subset of the language and is able to translate Python code into C++ while performing numerical optimization on mathematical expressions at runtime. To enable the JIT compilation, the user only needs to add a decorator to the function definition. By using HOPE, the user benefits from being able to write common numerical code in Python while getting the performance of compiled implementation.

[ascl:1411.004] OPERA: Open-source Pipeline for Espadons Reduction and Analysis

OPERA (Open-source Pipeline for Espadons Reduction and Analysis) is an open-source collaborative software reduction pipeline for ESPaDOnS data. ESPaDOnS is a bench-mounted high-resolution echelle spectrograph and spectro-polarimeter designed to obtain a complete optical spectrum (from 370 to 1,050 nm) in a single exposure with a mode-dependent resolving power between 68,000 and 81,000. OPERA is fully automated, calibrates on two-dimensional images and reduces data to produce one-dimensional intensity and polarimetric spectra. Spectra are extracted using an optimal extraction algorithm. Though designed for CFHT ESPaDOnS data, the pipeline is extensible to other echelle spectrographs.

[ascl:1411.003] voevent-parse: Parse, manipulate, and generate VOEvent XML packets

voevent-parse, written in Python, parses, manipulates, and generates VOEvent XML packets; it is built atop lxml.objectify. Details of transients detected by many projects, including Fermi, Swift, and the Catalina Sky Survey, are currently made available as VOEvents, which is also the standard alert format by future facilities such as LSST and SKA. However, working with XML and adhering to the sometimes lengthy VOEvent schema can be a tricky process. voevent-parse provides convenience routines for common tasks, while allowing the user to utilise the full power of the lxml library when required. An earlier version of voevent-parse was part of the pysovo (ascl:1411.002) library.

[ascl:1411.002] pysovo: A library for implementing alerts triggered by VOEvents

pysovo contains basic tools to work with VOEvents. Though written for specific needs, others interested in VOEvents may find it useful to examine.

[ascl:1411.001] pyGadgetReader: GADGET snapshot reader for python

pyGadgetReader is a universal GADGET snapshot reader for python that supports type-1, type-2, HDF5, and TIPSY (ascl:1111.015) binary formats. It additionally supports reading binary outputs from FoF_Special, P-StarGroupFinder, Rockstar (ascl:1210.008), and Rockstar-Galaxies.

[ascl:1410.005] RICH: Numerical simulation of compressible hydrodynamics on a moving Voronoi mesh

RICH (Racah Institute Computational Hydrodynamics) is a 2D hydrodynamic code based on Godunov's method. The code, largely based on AREPO (ascl:1909.010), acts on an unstructured moving mesh. It differs from AREPO in the interpolation and time advancement scheme as well as a novel parallelization scheme based on Voronoi tessellation. Though not universally true, in many cases a moving mesh gives better results than a static mesh: where matter moves one way and a sound wave is traveling in the other way (such that relative to the grid the wave is not moving), a static mesh gives better results than a moving mesh. RICH is designed in an object oriented, user friendly way that facilitates incorporation of new algorithms and physical processes.

[ascl:1410.004] UVOTPY: Swift UVOT grism data reduction

The two Swift UVOT grisms provide uv (170.0-500.0 nm) and visible (285.0-660.0 nm) spectra with a resolution of R~100 and 75. To reduce the grism data, UVOTPY extracts a spectrum given source sky position, and outputs a flux calibrated spectrum. UVOTPY is a replacement for the UVOTIMGRISM FTOOL (ascl:9912.002) in the HEADAS Swift package. Its extraction uses a curved aperture for the uv spectra, accounts the coincidence losses in the detector, provides more accurate anchor positions for the wavelength scale, and is valid for the whole detector.

[ascl:1410.003] GIZMO: Multi-method magneto-hydrodynamics+gravity code

GIZMO is a flexible, multi-method magneto-hydrodynamics+gravity code that solves the hydrodynamic equations using a variety of different methods. It introduces new Lagrangian Godunov-type methods that allow solving the fluid equations with a moving particle distribution that is automatically adaptive in resolution and avoids the advection errors, angular momentum conservation errors, and excessive diffusion problems that seriously limit the applicability of “adaptive mesh” (AMR) codes, while simultaneously avoiding the low-order errors inherent to simpler methods like smoothed-particle hydrodynamics (SPH). GIZMO also allows the use of SPH either in “traditional” form or “modern” (more accurate) forms, or use of a mesh. Self-gravity is solved quickly with a BH-Tree (optionally a hybrid PM-Tree for periodic boundaries) and on-the-fly adaptive gravitational softenings. The code is descended from P-GADGET, itself descended from GADGET-2 (ascl:0003.001), and many of the naming conventions remain (for the sake of compatibility with the large library of GADGET work and analysis software).

[ascl:1410.002] MEPSA: Multiple Excess Peak Search Algorithm

MEPSA (Multiple Excess Peak Search Algorithm) identifies peaks within a uniformly sampled time series affected by uncorrelated Gaussian noise. MEPSA scans the time series at different timescales by comparing a given peak candidate with a variable number of adjacent bins. While this has originally been conceived for the analysis of gamma-ray burst light (GRB) curves, its usage can be readily extended to other astrophysical transient phenomena whose activity is recorded through different surveys. MEPSA's high flexibility permits the mask of excess patterns it uses to be tailored and optimized without modifying the code.

[ascl:1410.001] DIAMONDS: high-DImensional And multi-MOdal NesteD Sampling

DIAMONDS (high-DImensional And multi-MOdal NesteD Sampling) provides Bayesian parameter estimation and model comparison by means of the nested sampling Monte Carlo (NSMC) algorithm, an efficient and powerful method very suitable for high-dimensional and multi-modal problems; it can be used for any application involving Bayesian parameter estimation and/or model selection in general. Developed in C++11, DIAMONDS is structured in classes for flexibility and configurability. Any new model, likelihood and prior PDFs can be defined and implemented upon a basic template.

[ascl:1409.013] IM3SHAPE: Maximum likelihood galaxy shear measurement code for cosmic gravitational lensing

Im3shape forward-fits a galaxy model to each data image it is supplied with and reports the parameters of the best fitting model, including the ellipticity components. It uses the Discrete Fourier Transform (DFT) to render images of convolved galaxy profiles, calculates the maximum likelihood parameter values, and corrects for noise bias. IM3SHAPE is a modular C code with a significant amount of Python glue code to enable setting up new models and their options automatically.

[ascl:1409.012] CosmoSIS: Cosmological parameter estimation

CosmoSIS is a cosmological parameter estimation code. It structures cosmological parameter estimation to ease re-usability, debugging, verifiability, and code sharing in the form of calculation modules. Witten in python, CosmoSIS consolidates and connects existing code for predicting cosmic observables and maps out experimental likelihoods with a range of different techniques.

[ascl:1409.011] rmfit: Forward-folding spectral analysis software

Rmfit uses a forward-folding technique to obtain the best-fit parameters for a chosen model given user-selected source and background time intervals from data files containing observed count rates and a corresponding detector response matrix. rmfit displays lightcurves and spectra using a graphical interface that enables user-defined integrated or time-resolved spectral fits and binning in either time or energy. Originally developed for the analysis of BATSE Gamma-Ray Burst (GRB) spectroscopy, rmfit is a tool for the spectroscopy of transient sources; it accommodates the Fermi GBM and LAT data and Swift BAT.

[ascl:1409.010] Slim: Numerical data compression for scientific data sets

Slim performs lossless compression on binary data files. Written in C++, it operates very rapidly and achieves better compression on noisy physics data than general-purpose tools designed primarily for text.

[ascl:1409.009] Nahoon: Time-dependent gas-phase chemical model

Nahoon is a gas-phase chemical model that computes the chemical evolution in a 1D temperature and density structure. It uses chemical networks downloaded from the KInetic Database for Astrochemistry (KIDA) but the model can be adapted to any network. The program is written in Fortran 90 and uses the DLSODES (double precision) solver from the ODEPACK package (ascl:1905.021) to solve the coupled stiff differential equations. The solver computes the chemical evolution of gas-phase species at a fixed temperature and density and can be used in one dimension (1D) if a grid of temperature, density, and visual extinction is provided. Grains, both neutral and negatively charged, and electrons are considered as chemical species and their concentrations are computed at the same time as those of the other species. Nahoon contains a test to check the temperature range of the validity of the rate coefficients and avoid extrapolations outside this range. A test is also included to check for duplication of chemical reactions, defined over complementary ranges of temperature.

[ascl:1409.008] CHLOE: A tool for automatic detection of peculiar galaxies

CHLOE is an image analysis unsupervised learning algorithm that detects peculiar galaxies in datasets of galaxy images. The algorithm first computes a large set of numerical descriptors reflecting different aspects of the visual content, and then weighs them based on the standard deviation of the values computed from the galaxy images. The weighted Euclidean distance of each galaxy image from the median is measured, and the peculiarity of each galaxy is determined based on that distance.

[ascl:1409.007] ORBS: A reduction software for SITELLE and SpiOMM data

ORBS merges, corrects, transforms and calibrates interferometric data cubes and produces a spectral cube of the observed region for analysis. It is a fully automatic data reduction software for use with SITELLE (installed at the Canada-France-Hawaii Telescope) and SpIOMM (a prototype attached to the Observatoire du Mont Mégantic); these imaging Fourier transform spectrometers obtain a hyperspectral data cube which samples a 12 arc-minutes field of view into 4 millions of visible spectra. ORBS is highly parallelized; its core classes (ORB) have been designed to be used in a suite of softwares for data analysis (ORCS and OACS), data simulation (ORUS) and data acquisition (IRIS).

[ascl:1409.006] iSpec: Stellar atmospheric parameters and chemical abundances

iSpec is an integrated software framework written in Python for the treatment and analysis of stellar spectra and abundances. Spectra treatment functions include cosmic rays removal, continuum normalization, resolution degradation, and telluric lines identification. It can also perform radial velocity determination and correction and resampling. iSpec can also determine atmospheric parameters (i.e effective temperature, surface gravity, metallicity, micro/macroturbulence, rotation) and individual chemical abundances by using either the synthetic spectra fitting technique or equivalent widths method. The synthesis is performed with SPECTRUM (ascl:9910.002).

[ascl:1409.005] IFSFIT: Spectral Fitting for Integral Field Spectrographs

IFSFIT is a general-purpose IDL library for fitting the continuum, emission lines, and absorption lines in integral field spectra. It uses PPXF (ascl:1210.002) to find the best fit stellar continuum (using a user-defined library of stellar templates and including additive polynomials), or optionally a user-defined method to find the best fit continuum. It uses MPFIT (ascl:1208.019) to simultaneously fit Gaussians to any number of emission lines and emission line velocity components. It will also fit the NaI D feature using analytic absorption and/or emission-line profiles.

[ascl:1409.004] IFSRED: Data Reduction for Integral Field Spectrographs

IFSRED is a general-purpose library for reducing data from integral field spectrographs (IFSs). For a general IFS data cube, it contains IDL routines to: (1) find and apply a zero-point shift in a wavelength solution on a spaxel-by-spaxel basis, using sky lines; (2) find the spatial coordinates of a flux peak; (3) empirically correct for differential atmospheric refraction; (4) mosaic dithered exposures; (5) (integer) rebin; and (6) apply a telluric correction. A sky-subtraction routine for data from the Gemini Multi-Object Spectrograph and Imager (GMOS) that can be easily modified for any instrument is also included. IFSRED also contains additional software specific to reducing data from GMOS and the Gemini Near-Infrared Integral Field Spectrograph (NIFS).

[ascl:1409.003] LANL*: Radiation belt drift shell modeling

LANL* calculates the magnetic drift invariant L*, used for modeling radiation belt dynamics and other space weather applications, six orders of magnitude (~ one million times) faster than convectional approaches that require global numerical field lines tracing and integration. It is based on a modern machine learning technique (feed-forward artificial neural network) by supervising a large data pool obtained from the IRBEM library, which is the traditional source for numerically calculating the L* values. The pool consists of about 100,000 samples randomly distributed within the magnetosphere (r: [1.03, 11.5] Re) and within a whole solar cycle from 1/1/1994 to 1/1/2005. There are seven LANL* models, each corresponding to its underlying magnetic field configuration that is used to create the data sample pool. This model has applications to real-time radiation belt forecasting, analysis of data sets involving tens of satellite-years of observations, and other problems in space weather.

[ascl:1409.002] TGFM: Tsyganenko Geomagnetic Field Models

The Tsyganenko models are semi-empirical best-fit representations for the magnetic field, based on a large number of satellite observations (IMP, HEOS, ISEE, POLAR, Geotail, GOES, etc). The models include the contributions from major external magnetospheric sources: ring current, magnetotail current system, magnetopause currents, and large-scale system of field-aligned currents.

[ascl:1409.001] mixT: single-temperature fit for a multi-component thermal plasma

mixT accurately predicts T derived from a single-temperature fit for a multi-component thermal plasma. It can be applied in the deprojection analysis of objects with the temperature and metallicity gradients, for correction of the PSF effects, for consistent comparison of numerical simulations of galaxy clusters and groups with the X-ray observations, and for estimating how emission from undetected components can bias the global X-ray spectral analysis.

[ascl:1408.023] WSClean: Widefield interferometric imager

WSClean (w-stacking clean) is a fast generic widefield imager. It uses the w-stacking algorithm and can make use of the w-snapshot algorithm. It supports full-sky imaging and proper beam correction for homogeneous dipole arrays such as the MWA. WSClean allows Hogbom and Cotton-Schwab cleaning, and can clean polarizations joinedly. All operations are performed on the CPU; it is not specialized for GPUs.

[ascl:1408.022] PhotoRApToR: PHOTOmetric Research APplication TO Redshifts

PhotoRApToR (PHOTOmetric Research APplication TO Redshifts) solves regression and classification problems and is specialized for photo-z estimation. PhotoRApToR offers data table manipulation capabilities and 2D and 3D graphics tools for data visualization; it also provides a statistical report for both classification and regression experiments. The code is written in Java; the machine learning model is in C++ to increase the core execution speed.

[ascl:1408.021] APS: Active Parameter Searching

APS finds Frequentist confidence limits on high-dimensional parameter spaces by using Gaussian Process interpolation to identify regions of parameter space for which chisquared is less than or equal to some specified limit. The code is written in C++, is robust against multi-modal chisquared functions and converges comparably fast to Monte Carlo methods. Code is also provided to draw Bayesian credible limits using the outputs of APS, though this code does not converge as well. APS requires the linear algebra libraries LAPACK, BLAS, and ARPACK (ascl:1311.010) to run.

[ascl:1408.020] bamr: Bayesian analysis of mass and radius observations

bamr is an MPI implementation of a Bayesian analysis of neutron star mass and radius data that determines the mass versus radius curve and the equation of state of dense matter. Written in C++, bamr provides some EOS models. This code requires O2scl (ascl:1408.019) be installed before compilation.

[ascl:1408.019] O2scl: Object-oriented scientific computing library

O2scl is an object-oriented library for scientific computing in C++ useful for solving, minimizing, differentiating, integrating, interpolating, optimizing, approximating, analyzing, fitting, and more. Many classes operate on generic function and vector types; it includes classes based on GSL and CERNLIB. O2scl also contains code for computing the basic thermodynamic integrals for fermions and bosons, for generating almost all of the most common equations of state of nuclear and neutron star matter, and for solving the TOV equations. O2scl can be used on Linux, Mac and Windows (Cygwin) platforms and has extensive documentation.

[ascl:1408.018] CosmoPhotoz: Photometric redshift estimation using generalized linear models

CosmoPhotoz determines photometric redshifts from galaxies utilizing their magnitudes. The method uses generalized linear models which reproduce the physical aspects of the output distribution. The code can adopt gamma or inverse gaussian families, either from a frequentist or a Bayesian perspective. A set of publicly available libraries and a web application are available. This software allows users to apply a set of GLMs to their own photometric catalogs and generates publication quality plots with no involvement from the user. The code additionally provides a Shiny application providing a simple user interface.

[ascl:1408.017] RDGEN: Routines for data handling, display, and adjusting

RDGEN is a collection of routines for data handling, display, and adjusting, with a facility which helps to set up files for using with VPFIT (ascl:1408.015); it is included in the VPFIT distribution file. It is useful for setting region boundaries and initial guesses for VPFIT, for displaying the accumulated results, for examining by eye particular redshift systems and fits to them, testing that the error array is a true reflection of the rms scatter in the data, comparing spectra and generally examining and even modifying the data.

[ascl:1408.016] vpguess: Fitting multiple Voigt profiles to spectroscopic data

vpguess facilitates the fitting of multiple Voigt profiles to spectroscopic data. It is a graphical interface to VPFIT (ascl:1408.015). Originally meant to simplify the process of setting up first guesses for a subsequent fit with VPFIT, it has developed into a full interface to VPFIT. It may also be used independently of VPFIT for displaying data, playing around with data and models, "chi-by-eye" fits, displaying the result of a proper fit, pretty plots, etc. vpguess is written in C, and the graphics are based on PGPLOT (ascl:1103.002).

[ascl:1408.015] VPFIT: Voigt profile fitting program

The VPFIT program fits multiple Voigt profiles (convolved with the instrument profiles) to spectroscopic data that is in FITS or an ASCII file. It requires CFITSIO (ascl:1010.001) and PGPLOT (ascl:1103.002); the tarball includes RDGEN (ascl:1408.017), which can be used with VPFIT to set up the fits, fit the profiles, and examine the result in interactive mode for setting up initial guesses; vpguess (ascl:1408.016) can also be used to set up an initial file.

[ascl:1408.014] pieflag: CASA task to efficiently flag bad data

pieflag compares bandpass-calibrated data to a clean reference channel and identifies and flags essentially all bad data. pieflag compares visibility amplitudes in each frequency channel to a 'reference' channel that is rfi-free (or manually ensured to be rfi-free). pieflag performs this comparison independently for each correlation on each baseline, but will flag all correlations if threshold conditions are met. To operate effectively, pieflag must be supplied with bandpass-calibrated data. pieflag has two core modes of operation (static and dynamic flagging) with an additional extend mode; the type of data largely determines which mode to choose. Instructions for pre-processing data and selecting the mode of operation are provided in the help file. Once pre-processing and selecting the mode of operation are done, pieflag should work well 'out of the box' with its default parameters.

[ascl:1408.013] NumCosmo: Numerical Cosmology

NumCosmo is a free software C library whose main purposes are to test cosmological models using observational data and to provide a set of tools to perform cosmological calculations. The software implements three different probes: cosmic microwave background (CMB), supernovae type Ia (SNeIa) and large scale structure (LSS) information, such as baryonic acoustic oscillations (BAO) and galaxy cluster abundance. The code supports a joint analysis of these data and the parameter space can include cosmological and phenomenological parameters. NumCosmo matter power spectrum and CMB codes were written independent of other implementations such as CMBFAST (ascl:9909.004), CAMB (ascl:1102.026), etc.

The library structure simplifies the inclusion of non-standard cosmological models. Besides the functions related to cosmological quantities, this library also implements mathematical and statistical tools. The former were developed to enable the inclusion of other probes and/or theoretical models and to optimize the codes. The statistical framework comprises algorithms which define likelihood functions, minimization, Monte Carlo, Fisher Matrix and profile likelihood methods.

[ascl:1408.012] LightcurveMC: An extensible lightcurve simulation program

LightcurveMC is a versatile and easily extended simulation suite for testing the performance of time series analysis tools under controlled conditions. It is designed to be highly modular, allowing new lightcurve types or new analysis tools to be introduced without excessive development overhead. The statistical tools are completely agnostic to how the lightcurve data is generated, and the lightcurve generators are completely agnostic to how the data will be analyzed. The use of fixed random seeds throughout guarantees that the program generates consistent results from run to run.

LightcurveMC can generate periodic light curves having a variety of shapes and stochastic light curves having a variety of correlation properties. It features two error models (Gaussian measurement and signal injection using a randomized sample of base light curves), testing of C1 shape statistic, periodograms, ΔmΔt plots, autocorrelation function plots, peak-finding plots, and Gaussian process regression. The code is written in C++ and R.

[ascl:1408.011] GALAPAGOS-C: Galaxy Analysis over Large Areas

GALAPAGOS-C is a C implementation of the IDL code GALAPAGOS (ascl:1203.002). It processes a complete set of survey images through automation of source detection via SExtractor (ascl:1010.064), postage stamp cutting, object mask preparation, sky background estimation and complex two-dimensional light profile Sérsic modelling via GALFIT (ascl:1104.010). GALAPAGOS-C uses MPI-parallelization, thus allowing quick processing of large data sets. The code can fit multiple Sérsic profiles to each galaxy, each representing distinct galaxy components (e.g. bulge, disc, bar), and optionally can fit asymmetric Fourier mode distortions.

[ascl:1408.010] VisiOmatic: Celestial image viewer

VisiOmatic is a web client for IIPImage (ascl:1408.009) and is used to visualize and navigate through large science images from remote locations. It requires STIFF (ascl:1110.006), is based on the Leaflet Javascript library, and works on both touch-based and mouse-based devices.

[ascl:1408.009] IIPImage: Large-image visualization

IIPImage is an advanced high-performance feature-rich image server system that enables online access to full resolution floating point (as well as other bit depth) images at terabyte scales. Paired with the VisiOmatic (ascl:1408.010) celestial image viewer, the system can comfortably handle gigapixel size images as well as advanced image features such as both 8, 16 and 32 bit depths, CIELAB colorimetric images and scientific imagery such as multispectral images. Streaming is tile-based, which enables viewing, navigating and zooming in real-time around gigapixel size images. Source images can be in either TIFF or JPEG2000 format. Whole images or regions within images can also be rapidly and dynamically resized and exported by the server from a single source image without the need to store multiple files in various sizes.

[ascl:1408.008] GALIC: Galaxy initial conditions construction

GalIC (GALaxy Initial Conditions) is an implementation of an iterative method to construct steady state composite halo-disk-bulge galaxy models with prescribed density distribution and velocity anisotropy that can be used as initial conditions for N-body simulations. The code is parallelized for distributed memory based on MPI. While running, GalIC produces "snapshot files" that can be used as initial conditions files. GalIC supports the three file formats ('type1' format, the slightly improved 'type2' format, and an HDF5 format) of the GADGET (ascl:0003.001) code for its output snapshot files.

[ascl:1408.007] Skycorr: Sky emission subtraction for observations without plain sky information

Skycorr is an instrument-independent sky subtraction code that uses physically motivated line group scaling in the reference sky spectrum by a fitting approach for an improved sky line removal in the object spectrum. Possible wavelength shifts between both spectra are corrected by fitting Chebyshev polynomials and advanced rebinning without resolution decrease. For the correction, the optimized sky line spectrum and the automatically separated sky continuum (without scaling) is subtracted from the input object spectrum. Tests show that Skycorr performs well (per cent level residuals) for data in different wavelength regimes and of different resolution, even in the cases of relatively long time lags between the object and the reference sky spectrum. Lower quality results are mainly restricted to wavelengths not dominated by airglow lines or pseudo continua by unresolved strong emission bands.

[ascl:1408.006] SPAM: Source Peeling and Atmospheric Modeling

SPAM is a extension to AIPS for reducing high-resolution, low-frequency radio interferometric observations. Direction-dependent ionospheric calibration and image-plane ripple suppression are among the features that help to make high-quality sub-GHz images. Data reductions are captured in well-tested Python scripts that execute AIPS tasks directly (mostly during initial data reduction steps), call high-level functions that make multiple AIPS or ParselTongue calls, and require few manual operations.

[ascl:1408.005] POET: Planetary Orbital Evolution due to Tides

POET (Planetary Orbital Evolution due to Tides) calculates the orbital evolution of a system consisting of a single star with a single planet in orbit under the influence of tides. The following effects are The evolutions of the semimajor axis of the orbit due to the tidal dissipation in the star and the angular momentum of the stellar convective envelope by the tidal coupling are taken into account. In addition, the evolution includes the transfer of angular momentum between the stellar convective and radiative zones, effect of the stellar evolution on the tidal dissipation efficiency, and stellar core and envelope spins and loss of stellar convective zone angular momentum to a magnetically launched wind. POET can be used out of the box, and can also be extended and modified.

[ascl:1408.004] HEAsoft: Unified Release of FTOOLS and XANADU

HEASOFT combines XANADU, high-level, multi-mission software for X-ray astronomical spectral, timing, and imaging data analysis tasks, and FTOOLS (ascl:9912.002), general and mission-specific software to manipulate FITS files, into one package. It also contains contains the NuSTAR subpackage of tasks, NuSTAR Data Analysis Software (NuSTARDAS). The source code for the software can be downloaded; precompiled executables for the most widely used computer platforms are also available for download. As an additional service, HEAsoft tasks can be directly from a web browser via WebHera.

[ascl:1408.003] PIA: ISOPHOT Interactive Analysis

ISOPHOT is one of the instruments on board the Infrared Space Observatory (ISO). ISOPHOT Interactive Analysis (PIA) is a scientific and calibration interactive data analysis tool for ISOPHOT data reduction. Written in IDL under Xwindows, PIA offers a full context sensitive graphical interface for retrieving, accessing and analyzing ISOPHOT data. It is available in two nearly identical versions; a general observers version omits the calibration sequences.

[ascl:1408.002] LIA: LWS Interactive Analysis

The Long Wavelength Spectrometer (LWS) was one of two complementary spectrometers on the Infrared Space Observatory (ISO). LIA (LWS Interactive Analysis) is used for processing data from the LWS. It provides access to the different processing steps, including visualization of intermediate products and interactive manipulation of the data at each stage.

[ascl:1408.001] Imfit: A Fast, Flexible Program for Astronomical Image Fitting

Imfit is an open-source astronomical image-fitting program specialized for galaxies but potentially useful for other sources, which is fast, flexible, and highly extensible. Its object-oriented design allows new types of image components (2D surface-brightness functions) to be easily written and added to the program. Image functions provided with Imfit include Sersic, exponential, and Gaussian galaxy decompositions along with Core-Sersic and broken-exponential profiles, elliptical rings, and three components that perform line-of-sight integration through 3D luminosity-density models of disks and rings seen at arbitrary inclinations.

Available minimization algorithms include Levenberg-Marquardt, Nelder-Mead simplex, and Differential Evolution, allowing trade-offs between speed and decreased sensitivity to local minima in the fit landscape. Minimization can be done using the standard chi^2 statistic (using either data or model values to estimate per-pixel Gaussian errors, or else user-supplied error images) or the Cash statistic; the latter is particularly appropriate for cases of Poisson data in the low-count regime.

The C++ source code for Imfit is available under the GNU Public License.

[ascl:1407.020] Halogen: Multimass spherical structure models for N-body simulations

Halogen, written in C, generates multimass spherically symmetric initial conditions for N-body simulations. A large family of radial density profiles is supported. The initial conditions are sampled from the full distribution function.

[ascl:1407.019] EZ_Ages: Stellar population age calculator

EZ_Ages is an IDL code package that computes the mean, light-weighted stellar population age, [Fe/H], and abundance enhancements [Mg/Fe], [C/Fe], [N/Fe], and [Ca/Fe] for unresolved stellar populations. This is accomplished by comparing Lick index line strengths between the data and the stellar population models of Schiavon (2007), using a method described in Graves & Schiavon (2008). The algorithm uses the inversion of index-index model grids to determine ages and abundances, and exploits the sensitivities of the various Lick indices to measure Mg, C, N, and Ca enhancements over their solar abundances with respect to Fe.

[ascl:1407.018] AstroML: Machine learning and data mining in astronomy

Written in Python, AstroML is a library of statistical and machine learning routines for analyzing astronomical data in python, loaders for several open astronomical datasets, and a large suite of examples of analyzing and visualizing astronomical datasets. An optional companion library, astroML_addons, is available; it requires a C compiler and contains faster and more efficient implementations of certain algorithms in compiled code.

[ascl:1407.017] e-MERLIN data reduction pipeline

Written in Python and utilizing ParselTongue (ascl:1208.020) to interface with AIPS (ascl:9911.003), the e-MERLIN data reduction pipeline processes, calibrates and images data from the UK's radio interferometric array (Multi-Element Remote-Linked Interferometer Network). Driven by a plain text input file, the pipeline is modular and can be run in stages. The software includes options to load raw data, average in time and/or frequency, flag known sources of interference, flag more comprehensively with SERPent (ascl:1312.001), carry out some or all of the calibration procedures (including self-calibration), and image in either normal or wide-field mode. It also optionally produces a number of useful diagnostic plots at various stages so data quality can be assessed.

[ascl:1407.016] Brut: Automatic bubble classifier

Brut, written in Python, identifies bubbles in infrared images of the Galactic midplane; it uses a database of known bubbles from the Milky Way Project and Spitzer images to build an automatic bubble classifier. The classifier is based on the Random Forest algorithm, and uses the WiseRF implementation of this algorithm.

[ascl:1407.015] BayesFlare: Bayesian method for detecting stellar flares

BayesFlare identifies flaring events in light curves released by the Kepler mission; it identifies even weak events by making use of the flare signal shape. The package contains functions to perform Bayesian hypothesis testing comparing the probability of light curves containing flares to that of them containing noise (or non-flare-like) artifacts. BayesFlare includes functions in its amplitude-marginalizer suite to account for underlying sinusoidal variations in light curve data; it includes such variations in the signal model, and then analytically marginalizes over them.

[ascl:1407.014] VIDE: The Void IDentification and Examination toolkit

The Void IDentification and Examination toolkit (VIDE) identifies voids using a modified version of the parameter-free void finder ZOBOV (ascl:1304.005); a Voronoi tessellation of the tracer particles is used to estimate the density field followed by a watershed algorithm to group Voronoi cells into zones and subsequently voids. Output is a summary of void properties in plain ASCII; a Python API is provided for analysis tasks, including loading and manipulating void catalogs and particle members, filtering, plotting, computing clustering statistics, stacking, comparing catalogs, and fitting density profiles.

[ascl:1407.013] VStar: Variable star data visualization and analysis tool

VStar is a multi-platform, easy-to-use variable star data visualization and analysis tool. Data for a star can be read from the AAVSO (American Association of Variable Star Observers) database or from CSV and TSV files. VStar displays light curves and phase plots, can produce a mean curve, and analyzes time-frequency with Weighted Wavelet Z-Transform. It offers tools for period analysis, filtering, and other functions.

[ascl:1407.012] PINGSoft2: Integral Field Spectroscopy Software

PINGSoft2 visualizes, manipulates and analyzes integral field spectroscopy (IFS) data based on either 3D cubes or Raw Stacked Spectra (RSS) format. Any IFS data can be adapted to work with PINGSoft2, regardless of the original data format and the size/shape of the spaxel. Written in IDL, PINGSoft2 is optimized for fast visualization rendering; it also includes various routines useful for generic astronomy and spectroscopy tasks.

[ascl:1407.011] kungifu: Calibration and reduction of fiber-fed IFU astronomical spectroscopy

kungifu is a set of IDL software routines designed for the calibration and reduction of fiber-fed integral-field unit (IFU) astronomical spectroscopy. These routines can perform optimal extraction of IFU data and allow relative and absolute wavelength calibration to within a few hundredths of a pixel (for unbinned data) across 1200-2000 fibers. kungifu does nearly Poisson-limited sky subtraction, even in the I band, and can rebin in wavelength. The Princeton IDLUTILS and IDLSPEC2D packages must be installed for kungifu to run.

[ascl:1407.010] CLE: Coronal line synthesis

CLE, written in Fortran 77, synthesizes Stokes profiles of forbidden lines such as Fe XIII 1074.7nm, formed in magnetic dipole transitions under coronal conditions. The lines are assumed to be optically thin, excited by (anisotropic) photospheric radiation and thermal particle collisions.

[ascl:1407.009] Period04: Statistical analysis of large astronomical time series

Period04 statistically analyzes large astronomical time series containing gaps. It calculates formal uncertainties, can extract the individual frequencies from the multiperiodic content of time series, and provides a flexible interface to perform multiple-frequency fits with a combination of least-squares fitting and the discrete Fourier transform algorithm. Period04, written in Java/C++, supports the SAMP communication protocol to provide interoperability with other applications of the Virtual Observatory. It is a reworked and extended version of Period98 (Sperl 1998) and PERIOD/PERDET (Breger 1990).

[ascl:1407.008] Exopop: Exoplanet population inference

Exopop is a general hierarchical probabilistic framework for making justified inferences about the population of exoplanets. Written in python, it requires that the occurrence rate density be a smooth function of period and radius (employing a Gaussian process) and takes survey completeness and observational uncertainties into account. Exopop produces more accurate estimates of the whole population than standard procedures based on weighting by inverse detection efficiency.

[ascl:1407.007] ASTRORAY: General relativistic polarized radiative transfer code

ASTRORAY employs a method of ray tracing and performs polarized radiative transfer of (cyclo-)synchrotron radiation. The radiative transfer is conducted in curved space-time near rotating black holes described by Kerr-Schild metric. Three-dimensional general relativistic magneto hydrodynamic (3D GRMHD) simulations, in particular performed with variations of the HARM code, serve as an input to ASTRORAY. The code has been applied to reproduce the sub-mm synchrotron bump in the spectrum of Sgr A*, and to test the detectability of quasi-periodic oscillations in its light curve. ASTRORAY can be readily applied to model radio/sub-mm polarized spectra of jets and cores of other low-luminosity active galactic nuclei. For example, ASTRORAY is uniquely suitable to self-consistently model Faraday rotation measure and circular polarization fraction in jets.

[ascl:1407.006] SAMI: Sydney-AAO Multi-object Integral field spectrograph pipeline

The SAMI (Sydney-AAO Multi-object Integral field spectrograph) pipeline reduces data from the Sydney-AAO Multi-object Integral field spectrograph (SAMI) for the SAMI Galaxy Survey. The python code organizes SAMI data and, along with the AAO 2dfdr package, carries out all steps in the data reduction, from raw data to fully calibrated datacubes. The principal steps are: data management, use of 2dfdr to produce row-stacked spectra, flux calibration, correction for telluric absorption, removal of atmospheric dispersion, alignment of dithered exposures, and drizzling onto a regular output grid. Variance and covariance information is tracked throughout the pipeline. Some quality control routines are also included.

[ascl:1407.005] MAAT: MATLAB Astronomy and Astrophysics Toolbox

The MATLAB Astronomy and Astrophysics Toolbox (MAAT) is a collection of software tools and modular functions for astronomy and astrophysics written in the MATLAB environment. It includes over 700 MATLAB functions and a few tens of data files and astronomical catalogs. The scripts cover a wide range of subjects including: astronomical image processing, ds9 control, astronomical spectra, optics and diffraction phenomena, catalog retrieval and searches, celestial maps and projections, Solar System ephemerides, planar and spherical geometry, time and coordinates conversion and manipulation, cosmology, gravitational lensing, function fitting, general utilities, plotting utilities, statistics, and time series analysis.

[ascl:1407.004] MCMAC: Monte Carlo Merger Analysis Code

Monte Carlo Merger Analysis Code (MCMAC) aids in the study of merging clusters. It takes observed priors on each subcluster's mass, radial velocity, and projected separation, draws randomly from those priors, and uses them in a analytic model to get posterior PDF's for merger dynamic properties of interest (e.g. collision velocity, time since collision).

[ascl:1407.003] SPECDRE: Spectroscopy Data Reduction

Specdre performs spectroscopy data reduction and analysis. General features of the package include data cube manipulation, arc line calibration, resampling and spectral fitting. Particular care is taken with error propagation, including tracking covariance. SPECDRE is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1407.002] TWODSPEC: Long-slit and optical fiber array spectra extensions for FIGARO

TWODSPEC offers programs for the reduction and analysis of long-slit and optical fiber array spectra, implemented as extensions to the FIGARO package (ascl:1203.013). The software are currently distributed as part of the Starlink software collection (ascl:1110.012). These programs are designed to do as much as possible for the user, to assist quick reduction and analysis of data; for example, LONGSLIT can fit multiple Gaussians to line profiles in batch and decides how many components to fit.

[ascl:1407.001] The Starfish Diagram: Statistical visualization tool

The Starfish Diagram is a statistical visualization tool that simultaneously displays the properties of an individual and its parent sample through a series of histograms. The code is useful for large datasets for which one needs to understand the standing or significance of a single entry.

[ascl:1406.020] STARMAN: Stellar photometry and image/table handling

STARMAN is a stellar photometry package designed for the reduction of data from imaging systems. Its main components are crowded-field photometry programs, aperture photometry programs, a star finding program, and a CCD reduction program.

Image and table handling are served by a large number of programs which have a general use in photometry and other types of work. The package is a coherent whole, for use in the entire process of stellar photometry from raw images to the final standard-system magnitudes and their plotting as color-magnitude and color-color diagrams. It was distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.019] JCMTDR: Applications for reducing JCMT continuum data in GSD format

JCMTDR reduces continuum on-the-fly mapping data obtained with UKT14 or the heterodyne instruments using the IFD on the James Clerk Maxwell Telescope. This program reduces archive data and heterodyne beam maps and was distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.018] GAUSSCLUMPS: Gaussian-shaped clumping from a spectral map

GAUSSCLUMPS decomposes a spectral map into Gaussian-shape clumps. The clump-finding algorithm decomposes a spectral data cube by iteratively removing 3-D Gaussians as representative clumps. GAUSSCLUMPS was originally a separate code distribution but is now a contributed package in GILDAS (ascl:1305.010). A reimplementation can also be found in CUPID (ascl:1311.007).

[ascl:1406.017] COCO: Conversion of Celestial Coordinates

The COCO program converts star coordinates from one system to another. Both the improved IAU system, post-1976, and the old pre-1976 system are supported. COCO can perform accurate transformations between multiple coordinate systems. COCO’s user-interface is spartan but efficient and the program offers control over report resolution. All input is free-format, and defaults are provided where this is meaningful. COCO uses SLALIB (ascl:1403.025) and is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.016] IUEDR: IUE Data Reduction package

IUEDR reduces IUE data. It addresses the problem of working from the IUE Guest Observer tape or disk file through to a calibrated spectrum that can be used in scientific analysis and is a complete system for IUE data reduction. IUEDR was distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.015] IRCAMDR: IRCAM3 Data Reduction Software

The UKIRT IRCAM3 data reduction and analysis software package, IRCAMDR (formerly ircam_clred) analyzes and displays any 2D data image stored in the standard Starlink (ascl:1110.012) NDF data format. It reduces and analyzes IRCAM1/2 data images of 62x58 pixels and IRCAM3 images of 256x256 size. Most of the applications will work on NDF images of any physical (pixel) dimensions, for example, 1024x1024 CCD images can be processed.

[ascl:1406.014] IRAS90: IRAS Data Processing

IRAS90 is a suite of programs for processing IRAS data. It takes advantage of Starlink's (ascl:1110.012) ADAM environment, which provides multi-platform availability of both data and the programs to process it, and the user friendly interface of the parameter entry system. The suite can determine positions in astrometric coordinates, draw grids, and offers other functions for standard astronomical measurement and standard projections.

[ascl:1406.013] CGS4DR: Automated reduction of data from CGS4

CGS4DR is data reduction software for the CGS4 instrument at UKIRT. The software can be used offline to reprocess CGS4 data. CGS4DR allows a wide variety of data reduction configurations, and can interlace oversampled data frames; reduce known bias, dark, flat, arc, object and sky frames; remove the sky, residual sky OH-lines (λ < 2.3 μm) and thermal emission (λ ≥ 2.3 μm) from data; and add data into groups for improved signal-to-noise. It can also extract and de-ripple a spectrum and offers a variety of ways to plot data, in addition to other useful features. CGS4DR is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.012] POLMAP: Interactive data analysis package for linear spectropolarimetry

POLMAP provides routines for displaying and analyzing spectropolarimetry data that are not available in the complementary TSP package. Commands are provided to read and write TSP (ascl:1406.011) polarization spectrum format files from within POLMAP. This code is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.011] TSP: Time-Series/Polarimetry Package

TSP is an astronomical data reduction package that handles time series data and polarimetric data from a variety of different instruments, and is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.010] MATCH: A program for matching star lists

MATCH matches up items in two different lists, which can have two different systems of coordinates. The program allows the two sets of coordinates to be related by a linear, quadratic, or cubic transformation. MATCH was designed and written to work on lists of stars and other astronomical objects but can be applied to other types of data. In order to match two lists of N points, the main algorithm calls for O(N^6) operations; though not the most efficient choice, it does allow for arbitrary translation, rotation, and scaling.

[ascl:1406.009] VADER: Viscous Accretion Disk Evolution Resource

VADER is a flexible, general code that simulates the time evolution of thin axisymmetric accretion disks in time-steady potentials. VADER handles arbitrary viscosities, equations of state, boundary conditions, and source and sink terms for both mass and energy.

[ascl:1406.008] ASTROM: Basic astrometry program

ASTROM performs "plate reductions" by taking user-provided star positions and the (x,y) coordinates of the corresponding star images and establishes the relationship between (x,y) and (ra,dec), thus enabling the coordinates of unknown stars to be determined. ASTROM is distributed with the Starlink software (ascl:1110.012) and uses SLALIB (ascl:1403.025).

[ascl:1406.007] RV: Radial Components of Observer's Velocity

The RV program produces a report listing the components, in a given direction, of the observer's velocity on a given date. This allows an observed radial velocity to be referred to an appropriate standard of rest -- typically either the Sun or an LSR.

As a secondary function, RV computes light time components to the Sun, thus allowing the times of phenomena observed from a terrestrial observatory to be referred to a heliocentric frame of reference. n.b. It will of course, in addition, be necessary to express the observations in the appropriate timescale as well as applying light time corrections. In particular, it is likely that an observed UTC will need to be converted to TDB as well as being corrected to the Sun.)

RV is distributed with the Starlink software collection (ascl:1110.012) and uses SLALIB (ascl:1403.025).

[ascl:1406.006] FROG: Time-series analysis

FROG performs time series analysis and display. It provides a simple user interface for astronomers wanting to do time-domain astrophysics but still offers the powerful features found in packages such as PERIOD (ascl:1406.005). FROG includes a number of tools for manipulation of time series. Among other things, the user can combine individual time series, detrend series (multiple methods) and perform basic arithmetic functions. The data can also be exported directly into the TOPCAT (ascl:1101.010) application for further manipulation if needed.

[ascl:1406.005] PERIOD: Time-series analysis package

PERIOD searches for periodicities in data. It is distributed within the Starlink software collection (ascl:1110.012).

[ascl:1406.004] Autoastrom: Autoastrometry for Mosaics

Autoastrom performs automated astrometric corrections on an astronomical image by automatically detecting objects in the frame, retrieving a reference catalogue, cross correlating the catalog with CCDPACK (ascl:1403.021) or MATCH, and using the ASTROM (ascl:1406.008) application to calculate a correction. It is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.003] CoREAS: CORSIKA-based Radio Emission from Air Showers simulator

CoREAS is a Monte Carlo code for the simulation of radio emission from extensive air showers; it is an update of and successor code to REAS3 (ascl:1107.009). It implements the endpoint formalism for the calculation of electromagnetic radiation directly in CORSIKA (ascl:1202.006). As such, it is parameter-free, makes no assumptions on the emission mechanism for the radio signals, and takes into account the complete complexity of the electron and positron distributions as simulated by CORSIKA.

[ascl:1406.002] PAMELA: Optimal extraction code for long-slit CCD spectroscopy

PAMELA is an implementation of the optimal extraction algorithm for long-slit CCD spectroscopy and is well suited for time-series spectroscopy. It properly implements the optimal extraction algorithm for curved spectra, including on-the-fly cosmic ray rejection as well as proper calculation and propagation of the errors. The software is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1406.001] ASURV: Astronomical SURVival Statistics

ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.

[ascl:1405.018] ECHOMOP: Echelle data reduction package

ECHOMOP extracts spectra from 2-D data frames. These data can be single-order spectra or multi-order echelle spectra. A substantial degree of automation is provided, particularly in the traditionally manual functions for cosmic-ray detection and wavelength calibration; manual overrides are available. Features include robust and flexible order tracing, optimal extraction, support for variance arrays, and 2-D distortion fitting and extraction. ECHOMOP is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1405.017] ESP: Extended Surface Photometry

ESP (Extended Surface Photometry) determines the photometric properties of galaxies and other extended objects. It has applications that detect flatfielding faults, remove cosmic rays, median filter images, determine image statistics and local background values, perform galaxy profiling, fit 2-D Gaussian profiles to galaxies, generate pie slice cross-sections of galaxies, and display profiling results. It is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1405.016] DIPSO: Spectrum analysis code

DIPSO plots spectroscopic data rapidly and combines analysis and high-quality graphical output in a simple command-line driven interactive environment. It can be used, for example, to fit emission lines, measure equivalent widths and fluxes, do Fourier analysis, and fit models to spectra. A macro facility allows convenient execution of regularly used sequences of commands, and a simple Fortran interface permits "personal" software to be integrated with the program. DIPSO is part of the Starlink software collection (ascl:1110.012).

[ascl:1405.015] CURSA: Catalog and Table Manipulation Applications

The CURSA package manipulates astronomical catalogs and similar tabular datasets. It provides facilities for browsing or examining catalogs; selecting subsets from a catalog; sorting and copying catalogs; pairing two catalogs; converting catalog coordinates between some celestial coordinate systems; and plotting finding charts and photometric calibration. It can also extract subsets from a catalog in a format suitable for plotting using other Starlink packages such as PONGO. CURSA can access catalogs held in the popular FITS table format, the Tab-Separated Table (TST) format or the Small Text List (STL) format. Catalogs in the STL and TST formats are simple ASCII text files. CURSA also includes some facilities for accessing remote on-line catalogs via the Internet. It is part of the Starlink software collection (ascl:1110.012).

[ascl:1405.014] POLPACK: Imaging polarimetry reduction package

POLPACK maps the linear or circular polarization of extended astronomical objects, either in a single waveband, or in multiple wavebands (spectropolarimetry). Data from both single and dual beam polarimeters can be processed. It is part of the Starlink software collection (ascl:1110.012).

[ascl:1405.013] PHOTOM: Photometry of digitized images

PHOTOM performs photometry of digitized images. It has two basic modes of operation: using an interactive display to specify the positions for the measurements, or obtaining those positions from a file. In both modes of operation PHOTOM performs photometry using either the traditional aperture method or via optimal extraction. When using the traditional aperture extraction method the target aperture can be circular or elliptical and its size and shape can be varied interactively on the display, or by entering values from the keyboard. Both methods allow the background sky level to be either sampled interactively by the manual positioning of an aperture, or automatically from an annulus surrounding the target object. PHOTOM is the photometry backend for the GAIA tool (ascl:1403.024) and is part of the Starlink software collection (ascl:1110.012).

[ascl:1405.012] PISA: Position Intensity and Shape Analysis

PISA (Position, Intensity and Shape Analysis) routines deal with the location and parameterization of objects on an image frame. The core of this package is the routine PISAFIND which performs image analysis on a 2-dimensional data frame. The program searches the data array for objects that have a minimum number of connected pixels above a given threshold and extracts the image parameters (position, intensity, shape) for each object. The image parameters can be determined using thresholding techniques or an analytical stellar profile can be used to fit the objects. In crowded regions deblending of overlapping sources can be performed. PISA is distributed as part of the Starlink software collection (ascl:1110.012).

[ascl:1405.011] DATACUBE: A datacube manipulation package

DATACUBE is a command-line package for manipulating and visualizing data cubes. It was designed for integral field spectroscopy but has been extended to be a generic data cube tool, used in particular for sub-millimeter data cubes from the James Clerk Maxwell Telescope. It is part of the Starlink software collection (ascl:1110.012).

[ascl:1405.010] FLUXES: Position and flux density of planets

FLUXES calculates approximate topocentric positions of the planets and also integrated flux densities of five of them at several wavelengths. These provide calibration information at the effective frequencies and beam-sizes employed by the UKT14, SCUBA and SCUBA-2 receivers on the JCMT telescope based on Mauna Kea, Hawaii. FLUXES is part of the bundle that comprises the Starlink multi-purpose astronomy software package (ascl:1110.012).

[ascl:1405.009] ATV: Image display tool

ATV displays and analyses astronomical images using the IDL image-processing language. It allows interactive control of the image scaling, color table, color stretch, and zoom, with support for world coordinate systems. It also does point-and-click aperture photometry, simple spectral extractions, and can produce publication-quality postscript output images.

[ascl:1405.008] TRIPP: Time Resolved Imaging Photometry Package

Written in IDL, TRIPP performs CCD time series reduction and analysis. It provides an on-line check of the incoming frames, performs relative aperture photometry and provides a set of time series tools, such as calculation of periodograms including false alarm probability determination, epoc folding, sinus fitting, and light curve simulations.

[ascl:1405.007] FORWARD: Forward modeling of coronal observables

FORWARD forward models various coronal observables and can access and compare existing data. Given a coronal model, it can produce many different synthetic observables (including Stokes polarimetry), as well as plots of model plasma properties (density, magnetic field, etc.). It uses the CHIANTI database (ascl:9911.004) and CLE polarimetry synthesis code, works with numerical model datacubes, interfaces with the PFSS module of SolarSoft (ascl:1208.013), includes several analytic models, and connects to the Virtual Solar Observatory for downloading data in a format directly comparable to model predictions.

[ascl:1405.006] PROPER: Optical propagation routines

PROPER simulates the propagation of light through an optical system using Fourier transform algorithms (Fresnel, angular spectrum methods). Available in IDL, Python, and Matlab, it includes routines to create complex apertures, aberrated wavefronts, and deformable mirrors. It is especially useful for the simulation of high contrast imaging telescopes (extrasolar planet imagers like TPF).

[ascl:1405.005] HIIPHOT: Automated Photometry of H II Regions

HIIPHOT enables accurate photometric characterization of H II regions while permitting genuine adaptivity to irregular source morphology. It makes a first guess at the shapes of all sources through object recognition techniques; it then allows for departure from such idealized "seeds" through an iterative growing procedure and derives photometric corrections for spatially coincident diffuse emission from a low-order surface fit to the background after exclusion of all detected sources.

[ascl:1405.004] Defringeflat: Fringe pattern removal

The IDL package Defringeflat identifies and removes fringe patterns from images such as spectrograph flat fields. It uses a wavelet transform to calculate the frequency spectrum in a region around each point of a one-dimensional array. The wavelet transform amplitude is reconstructed from (smoothed) parameters obtaining the fringe's wavelet transform, after which an inverse wavelet transform is performed to obtain the computed fringe pattern which is then removed from the flat.

[ascl:1405.003] The Hammer: An IDL Spectral Typing Suite

The Hammer can classify spectra in a variety of formats with targets spanning the MK spectral sequence. It processes a list of input spectra by automatically estimating each object's spectral type and measuring activity and metallicity tracers in late type stars. Once automatic processing is complete, an interactive interface allows the user to manually tweak the final assigned spectral type through visual comparison with a set of templates.

[ascl:1405.002] TelFit: Fitting the telluric absorption spectrum

TelFit calculates the best-fit telluric absorption spectrum in high-resolution optical and near-IR spectra. The best-fit model can then be divided out to remove the telluric contamination. Written in Python, TelFit is essentially a wrapper to LBLRTM (ascl:1405.001), the Line-By-Line Radiative Transfer Model, and simplifies the process of generating a telluric model.

[ascl:1405.001] LBLRTM: Line-By-Line Radiative Transfer Model

LBLRTM (Line-By-Line Radiative Transfer Model) is an accurate line-by-line model that is efficient and highly flexible. LBLRTM attributes provide spectral radiance calculations with accuracies consistent with the measurements against which they are validated and with computational times that greatly facilitate the application of the line-by-line approach to current radiative transfer applications. LBLRTM has been extensively validated against atmospheric radiance spectra from the ultra-violet to the sub-millimeter.

LBLRTM's heritage is in FASCODE [Clough et al., 1981, 1992].

[ascl:1404.017] Spextool: Spectral EXtraction tool

Spextool (Spectral EXtraction tool) is an IDL-based data reduction package for SpeX, a medium resolution near-infrared spectrograph on the NASA IRTF. It performs all of the steps necessary to produce spectra ready for analysis and publication including non-linearity corrections, flat fielding, wavelength calibration, telluric correction, flux calibration, and order merging.

[ascl:1404.016] AST: World Coordinate Systems in Astronomy

The AST library provides a comprehensive range of facilities for attaching world coordinate systems to astronomical data, for retrieving and interpreting that information in a variety of formats, including FITS-WCS, and for generating graphical output based on it. Core projection algorithms are provided by WCSLIB (ascl:1108.003) and astrometry is provided by the PAL (ascl:1606.002) and SOFA (ascl:1403.026) libraries. AST bindings are available in Python (pyast), Java (JNIAST) and Perl (Starlink::AST). AST is used as the plotting and astrometry library in DS9 and GAIA, and is distributed separately and as part of the Starlink software collection.

[ascl:1404.015] TTVFast: Transit timing inversion

TTVFast efficiently calculates transit times for n-planet systems and the corresponding radial velocities. The code uses a symplectic integrator with a Keplerian interpolator for the calculation of transit times (Nesvorny et al. 2013); it is available in both C and Fortran.

[ascl:1404.014] SpecPro: Astronomical spectra viewer and analyzer

SpecPro is an interactive program for viewing and analyzing spectra, particularly in the context of modern imaging surveys. In addition to displaying the 1D and 2D spectrum, SpecPro can simultaneously display available stamp images as well as the spectral energy distribution of a source. This extra information can help significantly in assessing a spectrum.

[ascl:1404.013] WFC3UV_GC: WFC3 UVIS geometric-distortion correction

WFC3UV_GC is an improved geometric-distortion solution for the Hubble Space Telescope UVIS channel of Wide Field Camera 3 for ten broad-band filters. The solution is made up of three parts:

1.) a 3rd-order polynomial to deal with the general optical distortion;
2.) a table of residuals that accounts for both chip-related anomalies and fine-structure introduced by the filter; and,
3.) a linear transformation to put the two chips into a convenient master frame.

[ascl:1404.012] RegPT: Regularized cosmological power spectrum

RegPT computes the power spectrum in flat wCDM class models based on the RegPT treatment when provided with either of transfer function or matter power spectrum. It then gives the multiple-redshift outputs for power spectrum, and optionally provides correlation function data. The Fortran code has two major options for power spectrum calculations; -fast, which quickly computes the power spectrum at two-loop level (typically a few seconds) using the pre-computed data set of PT kernels for fiducial cosmological models, and -direct, in which the code first applies the fast method, and then follows the regularized expression for power spectrum to directly evaluate the multi-dimensional integrals. The output results are the power spectrum of direct calculation and difference of the results between fast and direct method. The code also gives the data set of PT diagrams necessary for power spectrum calculations from which the power spectrum can be constructed.

[ascl:1404.011] CAP_LOESS_1D & CAP_LOESS_2D: Recover mean trends from noisy data

CAP_LOESS_1D and CAP_LOESS_2D provide improved implementations of the one-dimensional (Clevelend 1979) and two-dimensional (Cleveland & Devlin 1988) Locally Weighted Regression (LOESS) methods to recover the mean trends of the population from noisy data in one or two dimensions. They include a robust approach to deal with outliers (bad data). The software is available in both IDL and Python versions.

[ascl:1404.010] VictoriaReginaModels: Stellar evolutionary tracks

The Victoria–Regina stellar models are comprised of seventy-two grids of stellar evolutionary tracks accompanied by complementary zero-age horizontal branches and are presented in “equivalent evolutionary phase” (.eep) files. This Fortran 77 software interpolates isochrones, isochrone population functions, luminosity functions, and color functions of stellar evolutionary tracks.

[ascl:1404.009] carma_pack: MCMC sampler for Bayesian inference

carma_pack is an MCMC sampler for performing Bayesian inference on continuous time autoregressive moving average models. These models may be used to model time series with irregular sampling. The MCMC sampler utilizes an adaptive Metropolis algorithm combined with parallel tempering.

[ascl:1404.008] Comet: Multifunction VOEvent broker

Comet is a Python implementation of the VOEvent Transport Protocol (VTP). VOEvent is the IVOA system for describing transient celestial events. Details of transients detected by many projects, including Fermi, Swift, and the Catalina Sky Survey, are currently made available as VOEvents, which is also the standard alert format by future facilities such as LSST and SKA. The core of Comet is a multifunction VOEvent broker, capable of receiving events either by subscribing to one or more remote brokers or by direct connection from authors; it can then both process those events locally and forward them to its own subscribers. In addition, Comet provides a tool for publishing VOEvents to the global VOEvent backbone.

[ascl:1404.007] AMBIG: Automated Ambiguity-Resolution Code

AMBIG is a fast, automated algorithm for resolving the 180° ambiguity in vector magnetic field data, including those data from Hinode/Spectropolarimeter. The Fortran-based code is loosely based on the Minimum Energy Algorithm, and is distributed to provide ambiguity-resolved data for the general user community.

[ascl:1404.006] TORUS: Radiation transport and hydrodynamics code

TORUS is a flexible radiation transfer and radiation-hydrodynamics code. The code has a basic infrastructure that includes the AMR mesh scheme that is used by several physics modules including atomic line transfer in a moving medium, molecular line transfer, photoionization, radiation hydrodynamics and radiative equilibrium. TORUS is useful for a variety of problems, including magnetospheric accretion onto T Tauri stars, spiral nebulae around Wolf-Rayet stars, discs around Herbig AeBe stars, structured winds of O supergiants and Raman-scattered line formation in symbiotic binaries, and dust emission and molecular line formation in star forming clusters. The code is written in Fortran 2003 and is compiled using a standard Gnu makefile. The code is parallelized using both MPI and OMP, and can use these parallel sections either separately or in a hybrid mode.

[ascl:1404.005] SER: Subpixel Event Repositioning Algorithms

Subpixel Event Repositioning (SER) techniques significantly improve the already unprecedented spatial resolution of Chandra X-ray imaging with the Advanced CCD Imaging Spectrometer (ACIS). Chandra CCD SER techniques are based on the premise that the impact position of events can be refined, based on the distribution of charge among affected CCD pixels. Unlike ACIS SER models that are restricted to corner split (3- and 4-pixel) events and assume that such events take place at the split pixel corners, this IDL code uses two-pixel splits as well, and incorporates more realistic estimates of photon impact positions.

[ascl:1404.004] SAS: Science Analysis System for XMM-Newton observatory

The Science Analysis System (SAS) is an extensive suite of software tasks developed to process the data collected by the XMM-Newton Observatory. The SAS extracts standard (spectra, light curves) and/or customized science products, and allows reproductions of the reduction pipelines run to get the PPS products from the ODFs files. SAS includes a powerful and extensive suite of FITS file manipulation packages based on the Data Access Layer library.

[ascl:1404.002] ZDCF: Z-Transformed Discrete Correlation Function

The cross-correlation function (CCF) is commonly employed in the study of AGN, where it is used to probe the structure of the broad line region by line reverberation, to study the continuum emission mechanism by correlating multi-waveband light curves and to seek correlations between the variability and other AGN properties. The z -transformed discrete correlation function (ZDCF) is a method for estimating the CCF of sparse, unevenly sampled light curves. Unlike the commonly used interpolation method, it does not assume that the light curves are smooth and it does provide errors on its estimates.

[ascl:1404.001] LTS_LINEFIT & LTS_PLANEFIT: LTS fit of lines or planes

LTS_LINEFIT and LTS_PLANEFIT are IDL programs to robustly fit lines and planes to data with intrinsic scatter. The code combines the Least Trimmed Squares (LTS) robust technique, proposed by Rousseeuw (1984) and optimized in Rousseeuw & Driessen (2006), into a least-squares fitting algorithm which allows for intrinsic scatter. This method makes the fit converge to the correct solution even in the presence of a large number of catastrophic outliers, where the much simpler σ-clipping approach can converge to the wrong solution. The code is also available in Python as ltsfit.

[ascl:1403.026] SOFA: Standards of Fundamental Astronomy

SOFA (Standards Of Fundamental Astronomy) is a collection of subprograms, in source-code form, that implement official IAU algorithms for fundamental astronomy computations. SOFA offers more than 160 routines for fundamental astronomy, including time scales (including dealing with leap seconds), Earth rotation, sidereal time, precession, nutation, polar motion, astrometry and transforms between various reference systems (e.g. BCRS, ICRS, GCRS, CIRS, TIRS, ITRS). The subprograms are supported by 55 vector/matrix routines, and are available in both Fortran77 and C implementations.

[ascl:1403.025] SLALIB: A Positional Astronomy Library

SLALIB is a library of routines that make accurate and reliable positional-astronomy applications easier to write. Most SLALIB routines are concerned with astronomical position and time, but a number have wider trigonometrical, numerical or general applications. A Fortran implementation of SLALIB under GPL licensing is available as part of Starlink (ascl:1110.012).

[ascl:1403.024] GAIA: Graphical Astronomy and Image Analysis Tool

GAIA is an image and data-cube display and analysis tool for astronomy. It provides the usual facilities of image display tools, plus more astronomically useful ones such as aperture and optimal photometry, contouring, source detection, surface photometry, arbitrary region analysis, celestial coordinate readout, calibration and modification, grid overlays, blink comparison, defect patching and the ability to query on-line catalogues and image servers. It can also display slices from data-cubes, extract and visualize spectra as well as perform full 3D rendering. GAIA uses the Starlink software environment (ascl:1110.012) and is derived from the ESO SkyCat tool (ascl:1109.019).

[ascl:1403.023] ASTERIX: X-ray Data Processing System

ASTERIX is a general purpose X-ray data reduction package optimized for ROSAT data reduction. ASTERIX uses the Starlink software environment (ascl:1110.012).

[ascl:1403.022] KAPPA: Kernel Applications Package

KAPPA comprising about 180 general-purpose commands for image processing, data visualization, and manipulation of the standard Starlink data format--the NDF. It works with Starlink's various specialized packages; in addition to the NDF, KAPPA can also process data in other formats by using the "on-the-fly" conversion scheme. Many commands can process data arrays of arbitrary dimension, and others work on both spectra and images. KAPPA operates from both the UNIX C-shell and the ICL command language. KAPPA uses the Starlink environment (ascl:1110.012).

[ascl:1403.021] CCDPACK: CCD Data Reduction Package

CCDPACK contains programs to debias, remove dark current, flatfield, register, resample and normalize data from single- or multiple-CCD instruments. The basic reduction stages can be set up using an X based GUI that controls an automated reduction system so one can to start working without any detailed knowledge of the package (or indeed of CCD reduction). Registration is performed using graphical, script based or automated techniques that keep the amount of work to a minimum. CCDPACK uses the Starlink environment (ascl:1110.012).

[ascl:1403.020] disc2vel: Tangential and radial velocity components derivation

Disc2vel derives tangential and radial velocity components in the equatorial plane of a barred stellar disc from the observed line-of-sight velocity, assuming geometry of a thin disc. The code is written in IDL, and the method assumes that the bar is close to steady state (i.e. does not evolve fast) and that both morphology and kinematics are symmetrical with respect to the major axis of the bar.

[ascl:1403.019] KINEMETRY: Analysis of 2D maps of kinematic moments of LOSVD

KINEMETRY, written in IDL, analyzes 2D maps of the moments of the line-of-sight velocity distribution (LOSVD). It generalizes the surface photometry to all moments of the LOSVD. It performs harmonic expansion of 2D maps of observed moments (surface brightness, velocity, velocity dispersion, h3, h4, etc.) along the best fitting ellipses (either fixed or free to change along the radii) to robustly quantify maps of the LOSVD moments, describe trends in structures, and detect morphological and kinematic sub-components.

[ascl:1403.018] JAM: Jeans Anisotropic MGE modeling method

The Jeans Anisotropic MGE (JAM) modeling method uses the Multi-Gaussian Expansion parameterization for the galaxy surface brightness. The code allows for orbital anisotropy (three-integrals distribution function) and also provides the full second moment tensor, including proper motions and radial velocities.

[ascl:1403.017] MGE_FIT_SECTORS: Multi-Gaussian Expansion fits to galaxy images

MGE_FIT_SECTORS performs Multi-Gaussian Expansion (MGE) fits to galaxy images. The MGE parameterizations are useful in the construction of realistic dynamical models of galaxies, PSF deconvolution of images, the correction and estimation of dust absorption effects, and galaxy photometry. The algorithm is well suited for use with multiple-resolution images (e.g. Hubble Space Telescope (HST) and ground-based images).

[ascl:1403.016] Viewpoints: Fast interactive linked plotting of large multivariate data sets

Viewpoints is an interactive tool for exploratory visual analysis of large high-dimensional (multivariate) data. It uses linked scatterplots to find relations in a few seconds that can take much longer with other plotting tools. Its features include linked scatter plots with brushing, dynamic histograms, normalization, and outlier detection/removal.

[ascl:1403.015] computePk: Power spectrum computation

ComputePk computes the power spectrum in cosmological simulations. It is MPI parallel and has been tested up to a 4096^3 mesh. It uses the FFTW library. It can read Gadget-3 and GOTPM outputs, and computes the dark matter component. The user may choose between NGP, CIC, and TSC for the mass assignment scheme.

[ascl:1403.014] T(dust) as a function of sSFR

This IDL code returns the dust temperature of a galaxy from its redshift, SFR and stellar mass; it can also predict the observed monochromatic fluxes of the galaxy. These monochromatic fluxes correspond to those of a DH SED template with the appropriate dust temperature and the appropriate normalization. Dust temperatures and fluxes predictions are only valid and provided in the redshift, stellar mass, SSFR and wavelength ranges 0 < z < 2.5, Mstar> 10^10 Msun, 10^-11 < SSFR[yr-1]< 10^-7 and 30um < lambda_rest < 2mm.

[ascl:1403.013] BAOlab: Image processing program

BAOlab is an image processing package written in C that should run on nearly any UNIX system with just the standard C libraries. It reads and writes images in standard FITS format; 16- and 32-bit integer as well as 32-bit floating-point formats are supported. Multi-extension FITS files are currently not supported. Among its tools are ishape for size measurements of compact sources, mksynth for generating synthetic images consisting of a background signal including Poisson noise and a number of pointlike sources, imconvol for convolving two images (a “source” and a “kernel”) with each other using fast fourier transforms (FFTs) and storing the output as a new image, and kfit2d for fitting a two-dimensional King model to an image.

[ascl:1403.012] YNOGKM: Time-like geodesics in the Kerr-Newmann Spacetime calculations

YNOGKM (Yun-Nan observatories geodesic in a Kerr-Newman spacetime for massive particles) performs fast calculation of time-like geodesics in the Kerr-Newman (K-N) spacetime; it is a direct extension of YNOGK (Yun-Nan observatories geodesic Kerr) calculating null geodesics in a Kerr spacetime. The four Boyer-Lindquis coordinates and proper time are expressed as functions of a parameter p semi-analytically by using the Weierstrass' and Jacobi's elliptic functions and integrals. The elliptic integrals are computed by Carlson's elliptic integral method, which guarantees the fast speed of the code. The source Fortran file ynogkm.f90 contains three modules: constants, rootfind, ellfunction, and blcoordinates.

[ascl:1403.011] RMHB: Hierarchical Reverberation Mapping

RMHB is a hierarchical Bayesian code for reverberation mapping (RM) that combines results of a sparsely sampled broad line region (BLR) light curve and a large sample of active galactic nuclei (AGN) to infer properties of the sample of the AGN. The key idea of RM is to measure the time lag τ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of τ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass MBH. A major difficulty with RM campaigns is the large amount of data needed to measure τ. RMHB allows a clear interpretation of a posterior distribution for hyperparameters describing the sample of AGN.

[ascl:1403.010] Inverse Beta: Inverse cumulative density function (CDF) of a Beta distribution

The Beta Inverse code solves the inverse cumulative density function (CDF) of a Beta distribution, allowing one to sample from the Beta prior directly. The Beta distribution is well suited as a prior for the distribution of the orbital eccentricities of extrasolar planets; imposing a Beta prior on orbital eccentricity is valuable for any type of observation of an exoplanet where eccentricity can affect the model parameters (e.g. transits, radial velocities, microlensing, direct imaging). The Beta prior is an excellent description of the current, empirically determined distribution of orbital eccentricities and thus employing it naturally incorporates an observer’s prior experience of what types of orbits are probable or improbable. The default parameters in the code are currently set to the Beta distribution which best describes the entire population of exoplanets with well-constrained orbits.

[ascl:1403.009] ISAP: ISO Spectral Analysis Package

ISAP, written in IDL, simplifies the process of visualizing, subsetting, shifting, rebinning, masking, combining scans with weighted means or medians, filtering, and smoothing Auto Analysis Results (AARs) from post-pipeline processing of the Infrared Space Observatory's (ISO) Short Wavelength Spectrometer (SWS) and Long Wavelength Spectrometer (LWS) data. It can also be applied to PHOT-S and CAM-CVF data, and data from practically any spectrometer. The result of a typical ISAP session is expected to be a "simple spectrum" (single-valued spectrum which may be resampled to a uniform wavelength separation if desired) that can be further analyzed and measured either with other ISAP functions, native IDL functions, or exported to other analysis package (e.g., IRAF, MIDAS) if desired. ISAP provides many tools for further analysis, line-fitting, and continuum measurements, such as routines for unit conversions, conversions from wavelength space to frequency space, line and continuum fitting, flux measurement, synthetic photometry and models such as a zodiacal light model to predict and subtract the dominant foreground at some wavelengths.

[ascl:1403.008] SURF: Submm User Reduction Facility

SURF reduces data from the SCUBA instrument from the James Clerk Maxwell Telescope. Facilities are provided for reducing all the SCUBA observing modes including jiggle, scan and photometry modes. SURF uses the Starlink environment (ascl:1110.012).

[ascl:1403.007] PC: Unified EOS for neutron stars

The equation of state (EOS) of dense matter is a crucial input for the neutron-star structure calculations. This Fortran code can obtain a "unified EOS" in the many-body calculations based on a single effective nuclear Hamiltonian, and is valid in all regions of the neutron star interior. For unified EOSs, the transitions between the outer crust and the inner crust and between the inner crust and the core are obtained as a result of many-body calculations.

[ascl:1403.006] CHIMERA: Core-collapse supernovae simulation code

CHIMERA simulates core collapse supernovas; it is three-dimensional and accounts for the differing energies of neutrinos. This massively parallel multiphysics code conserves total energy (gravitational, internal, kinetic, and neutrino) to within 0.5 B, given a conservative gravitational potential. CHIMERA has three main components: a hydro component, a neutrino transport component, and a nuclear reaction network component. It also includes a Poisson solver for the gravitational potential and a sophisticated equation of state.

[ascl:1403.005] GRay: Massive parallel ODE integrator

GRay is a massive parallel ordinary differential equation integrator that employs the "stream processing paradigm." It is designed to efficiently integrate billions of photons in curved spacetime according to Einstein's general theory of relativity. The code is implemented in CUDA C/C++.

[ascl:1403.004] Lightcone: Light-cone generating script

Lightcone works with simulated galaxy data stored in a relational database to rearrange the data in a shape of a light-cone; simulated galaxy data is expected to be in a box volume. The light-cone constructing script works with output from the SAGE semi-analytic model (ascl:1601.006), but will work with any other model that has galaxy positions (and other properties) saved per snapshots of the simulation volume distributed in time. The database configuration file is set up for PostgreSQL RDBMS, but can be modified for use with any other SQL database.

[ascl:1403.003] MLZ: Machine Learning for photo-Z

The parallel Python framework MLZ (Machine Learning and photo-Z) computes fast and robust photometric redshift PDFs using Machine Learning algorithms. It uses a supervised technique with prediction trees and random forest through TPZ that can be used for a regression or a classification problem, or a unsupervised methods with self organizing maps and random atlas called SOMz. These machine learning implementations can be efficiently combined into a more powerful one resulting in robust and accurate probability distributions for photometric redshifts.

[ascl:1403.002] pyExtinction: Atmospheric extinction

The Python script/package pyExtinction computes and plots total atmospheric extinction from decomposition into physical components (Rayleigh attenuation, ozone absorption, aerosol extinction). Its default extinction parameters are adapted to mean Mauna Kea summit conditions.

[ascl:1403.001] GPU-D: Generating cosmological microlensing magnification maps

GPU-D is a GPU-accelerated implementation of the inverse ray-shooting technique used to generate cosmological microlensing magnification maps. These maps approximate the source plane magnification patterns created by an ensemble of stellar-mass compact objects within a foreground macrolens galaxy. Unlike other implementations, GPU-D solves the gravitational lens equation without any approximation. Due to the high computational intensity and high degree of parallelization inherent in the algorithm, it is ideal for brute-force implementation on GPUs. GPU-D uses CUDA for GPU acceleration and require NVIDIA devices to run.

[ascl:1402.035] MGHalofit: Modified Gravity extension of Halofit

MGHalofit is a modified gravity extension of the fitting formula for the matter power spectrum of HALOFIT and its improvement by Takahashi et al. MGHalofit is implemented in MGCAMB, which is based on CAMB. MGHalofit calculates the nonlinear matter power spectrum P(k) for the Hu-Sawicki model. Comparing MGHalofit predictions at various redshifts (z<=1) to the f(R) simulations, the accuracy on P(k) is 6% at k<1 h/Mpc and 12% at 1<k<10 h/Mpc respectively.

[ascl:1402.034] PyWiFeS: Wide Field Spectrograph data reduction pipeline

PyWiFeS is a Python-based data reduction pipeline for the Wide Field Spectrograph (WiFeS). Its core data processing routines are built on standard scientific Python packages commonly used in astronomical applications. It includes an implementation of a global optical model of the spectrograph which provides wavelengths solutions accurate to ˜0.05 Å (RMS) across the entire detector. Through scripting, PyWiFeS can enable batch processing of large quantities of data.

[ascl:1402.033] libsharp: Library for spherical harmonic transforms

Libsharp is a collection of algorithms for efficient conversion between maps on the sphere and their spherical harmonic coefficients. It supports a wide range of pixelisations (including HEALPix, GLESP, and ECP). This library is a successor of libpsht (ascl:1010.020); it adds MPI support for distributed memory systems and SHTs of fields with arbitrary spin, and also supports new developments in CPU instruction sets like the Advanced Vector Extensions (AVX) or fused multiply-accumulate (FMA) instructions. libsharp is written in portable C99; it provides an interface accessible to other programming languages such as C++, Fortran, and Python.

[ascl:1402.032] HALOFIT: Nonlinear distribution of cosmological mass and galaxies

HALOFIT provides an explanatory framework for galaxy bias and clustering and has been incorporated into CMB packages such as CMBFAST (ascl:9909.004) and CAMB (ascl:1102.026). It attains a reasonable level of precision, though the halo model does not match N-body data perfectly. The code is written in Fortran 77. HALOFIT tends to underpredict the power on the smallest scales in standard LCDM universes (although HALOFIT was designed to work for a much wider range of power spectra); its accuracy can be improved by using a supplied correction.

[ascl:1402.031] gyrfalcON: N-body code

gyrfalcON (GalaxY simulatoR using falcON) is a full-fledged N-body code using Dehnen’s force algorithm of complexity O(N) (falcON); this algorithm is approximately 10 times faster than an optimally coded tree code. The code features individual adaptive time steps and individual (but fixed) softening lengths. gyrfalcON is included in and requires NEMO to run.

[ascl:1402.030] P2SAD: Particle Phase Space Average Density

P2SAD computes the Particle Phase Space Average Density (P2SAD) in galactic haloes. The model for the calculation is based on the stable clustering hypothesis in phase space, the spherical collapse model, and tidal disruption of substructures. The multiscale prediction for P2SAD computed by this IDL code can be used to estimate signals sensitive to the small scale structure of dark matter distributions (e.g. dark matter annihilation). The code computes P2SAD averaged over the whole virialized region of a Milky-Way-size halo at redshift zero.

[ascl:1402.029] wssa_utils: WSSA 12 micron dust map utilities

wssa_utils contains utilities for accessing the full-sky, high-resolution maps of the WSSA 12 micron data release. Implementations in both Python and IDL are included. The code allows users to sample values at (longitude, latitude) coordinates of interest with ease, transparently mapping coordinates to WSSA tiles and performing interpolation. The wssa_utils software also serves to define a unique WSSA 12 micron flux at every location on the sky.

[ascl:1402.028] Commander 2: Bayesian CMB component separation and analysis

Commander 2 is a Gibbs sampling code for joint CMB estimation and component separation. The Commander framework uses a parametrized physical model of the sky to perform statistically-rigorous analyses of multi-frequency, multi-resolution CMB data on the full and partial (flat) sky, as well as cross-correlation analyses with large-scale structure datasets.

[ascl:1402.027] Darth Fader: Galaxy catalog cleaning method for redshift estimation

Darth Fader is a wavelet-based method for extracting spectral features from very noisy spectra. Spectra for which a reliable redshift cannot be measured are identified and removed from the input data set automatically, resulting in a clean catalogue that gives an extremely low rate of catastrophic failures even when the spectra have a very low S/N. This technique may offer a significant boost in the number of faint galaxies with accurately determined redshifts.

[ascl:1402.026] athena: Tree code for second-order correlation functions

athena is a 2d-tree code that estimates second-order correlation functions from input galaxy catalogues. These include shear-shear correlations (cosmic shear), position-shear (galaxy-galaxy lensing) and position-position (spatial angular correlation). Written in C, it includes a power-spectrum estimator implemented in Python; this script also calculates the aperture-mass dispersion. A test data set is available.

[ascl:1402.025] BAOlab: Baryon Acoustic Oscillations software

Using the 2-point correlation function, BAOlab aids the study of Baryon Acoustic Oscillations (BAO). The code generates a model-dependent covariance matrix which can change the results both for BAO detection and for parameter constraints.

[ascl:1402.024] QuickReduce: Data reduction pipeline for the WIYN One Degree Imager

QuickReduce quickly reduces data for ODI and is optimized for a first data inspection during acquisition at the the telescope. When installed on the ODI observer's interface, QuickReduce, coded in Python, performs all basic reduction steps as well as more advanced corrections for pupil-ghost removal, fringe correction and masking of persistent pixels and is capable enough for science-quality data reductions. It can also add an accurate astrometric WCS solution based on the 2MASS reference system as well as photometric zeropoint calibration for frames covered by the SDSS foot-print. The pipeline makes use of multiple CPU-cores wherever possible, resulting in an execution time of only a few seconds per frame, thus offering the ODI observer a convenient way to closely monitor data quality.

[ascl:1402.023] HydraLens: Gravitational lens model generator

HydraLens generates gravitational lens model files for Lenstool (ascl:1102.004), PixeLens (ascl:1102.007), glafic (ascl:1010.012) and Lensmodel and can also translate lens model files among these four lens model codes. Through a GUI, the user enters a new model by specifying the type of model and is then led through screens to collect the data. Written in MS Visual Basic, the code can also translate an existing model from any of the four supported codes to any of the other three.

[ascl:1402.001] Vissage: ALMA VO Desktop Viewer

Vissage (VISualisation Software for Astronomical Gigantic data cubEs) is a FITS browser primarily targeting FITS data cubes obtained from ALMA. Vissage offers basic functionality for viewing three-dimensional data cubes, integrated intensity map, flipbook, channel map, and P-V diagram. It has several color sets and color scales available, offers panning and zooming, and can connect with the ALMA WebQL system and the JVO Subaru Image Cutout Service.

[ascl:1402.002] Glue: Linked data visualizations across multiple files

Glue, written in Python, links visualizations of scientific datasets across many files, allowing for interactive, linked statistical graphics of multiple files. It supports many file formats including common image formats (jpg, tiff, png), ASCII tables, astronomical image and table formats (FITS, VOT, IPAC), and HDF5. Custom data loaders can also be easily added. Glue is highly scriptable and extendable.

[ascl:1402.003] astroplotlib: Astronomical library of plots

Astropoltlib is a multi-language astronomical library of plots, a collection of templates useful for creating paper-quality figures. Most of the codes for producing the plots are written in IDL and/or Python; a very few are written in Mathematica. Any plot can be downloaded and customized to one's own needs.

[ascl:1402.004] PyVO: Python access to the Virtual Observatory

PyVO provides access to remote data and services of the Virtual observatory (VO) using Python. It allows archive searches for data of a particular type or related to a particular topic and query submissions to obtain data to a particular archive to download selected data products. PyVO supports querying the VAO registry; simple data access services (DAL) to access images (SIA), source catalog records (Cone Search), spectra (SSA), and spectral line emission/absorption data (SLAP); and object name resolution (for converting names of objects in the sky into positions). PyVO requires both AstroPy (ascl:1304.002) and NumPy.

[ascl:1402.005] Aladin Lite: Lightweight sky atlas for browsers

Aladin Lite is a lightweight version of the Aladin tool, running in the browser and geared towards simple visualization of a sky region. It allows visualization of image surveys (JPEG multi-resolution HEALPix all-sky surveys) and permits superimposing tabular (VOTable) and footprints (STC-S) data. Aladin Lite is powered by HTML5 canvas technology and is easily embeddable on any web page and can also be controlled through a Javacript API.

[ascl:1402.006] Munipack: General astronomical image processing software

Munipack provides easy-to-use tools for all astronomical astrometry and photometry, access to Virtual Observatory as well as FITS files operations and a simple user interface along with a powerful processing engine. Its many features include a FITS images viewer that allows for basic (astronomical) operations with frames, advanced image processor supporting an infinite dynamic range and advanced color management, and astrometric calibration of images. The astrometry module uses robust statistical estimators and algorithms. The photometry module provides the classical method detection of stars and implements the aperture photometry, calibrated on the basis of photon statistics, and allows for the automatic detection and aperture photometry of stars; calibration on absolute fluxes is possible. The software also provides a standard way to correct for all the bias, dark and flat-field frames, and many other features.

[ascl:1402.007] SPLAT: Spectral Analysis Tool

SPLAT is a graphical tool for displaying, comparing, modifying and analyzing astronomical spectra stored in NDF, FITS and TEXT files as well as in NDX format. It can read in many spectra at the same time and then display these as line plots. Display windows can show one or several spectra at the same time and can be interactively zoomed and scrolled, centered on specific wavelengths, provide continuous coordinate readout, produce printable hardcopy and be configured in many ways. Analysis facilities include the fitting of a polynomial to selected parts of a spectrum, the fitting of Gaussian, Lorentzian and Voigt profiles to emission and absorption lines and the filtering of spectra using average, median and line-shape window functions as well as wavelet denoising. SPLAT also supports a full range of coordinate systems for spectra, which allows coordinates to be displayed and aligned in many different coordinate systems (wavelength, frequency, energy, velocity) and transformed between these and different standards of rest (topocentric, heliocentric, dynamic and kinematic local standards of rest, etc). SPLAT is distributed as part of the Starlink (ascl:1110.012) software collection.

[ascl:1402.008] SPLAT-VO: Spectral Analysis Tool for the Virtual Observatory

SPLAT-VO is an extension of the SPLAT (Spectral Analysis Tool, ascl:1402.007) graphical tool for displaying, comparing, modifying and analyzing astronomical spectra; it includes facilities that allow it to work as part of the Virtual Observatory (VO). SPLAT-VO comes in two different forms, one for querying and downloading spectra from SSAP servers and one for interoperating with VO tools, such as TOPCAT (ascl:1101.010).

[ascl:1402.009] GalSim: Modular galaxy image simulation toolkit

GalSim is a fast, modular software package for simulation of astronomical images. Though its primary purpose is for tests of weak lensing analysis methods, it can be used for other purposes. GalSim allows galaxies and PSFs to be represented in a variety of ways, and can apply shear, magnification, dilation, or rotation to a galaxy profile including lensing-based models from a power spectrum or NFW halo profile. It can write images in regular FITS files, FITS data cubes, or multi-extension FITS files. It can also compress the output files using various compressions including gzip, bzip2, and rice. The user interface is in python or via configuration scripts, and the computations are done in C++ for speed.

[ascl:1402.010] CPL: Common Pipeline Library

The Common Pipeline Library (CPL) is a set of ISO-C libraries that provide a comprehensive, efficient and robust software toolkit to create automated astronomical data reduction pipelines. Though initially developed as a standardized way to build VLT instrument pipelines, the CPL may be more generally applied to any similar application. The code also provides a variety of general purpose image- and signal-processing functions, making it an excellent framework for the creation of more generic data handling packages. The CPL handles low-level data types (images, tables, matrices, strings, property lists, etc.) and medium-level data access methods (a simple data abstraction layer for FITS files). It also provides table organization and manipulation, keyword/value handling and management, and support for dynamic loading of recipe modules using programs such as EsoRex (ascl:1504.003).

[ascl:1402.011] KROME: Chemistry package for astrophysical simulations

KROME, given a chemical network (in CSV format), automatically generates all the routines needed to solve the kinetics of the system modeled as a system of coupled Ordinary Differential Equations. It provides a large set of physical processes connected to chemistry, including photochemistry, cooling, heating, dust treatment, and reverse kinetics. KROME is flexible and can be used for a wide range of astrophysical simulations. The package contains a network for primordial chemistry, a small metal network appropriate for the modeling of low metallicities environments, a detailed network for the modeling of molecular clouds, and a network for planetary atmospheres as well as a framework for the modelling of the dust grain population.

[ascl:1402.012] QUICKCV: Cosmic variance calculator

QUICKCV is an IDL sample variance/cosmic variance calculator for some geometry for galaxies in given stellar mass bins as a function of mean redshift and redshift bin size.

[ascl:1402.013] CASSIS: Interactive spectrum analysis

CASSIS (Centre d'Analyse Scientifique de Spectres Infrarouges et Submillimetriques), written in Java, is suited for broad-band spectral surveys to speed up the scientific analysis of high spectral resolution observations. It uses a local spectroscopic database made of the two molecular spectroscopic databases JPL and CDMS, as well as the atomic spectroscopic database NIST. Its tools include a LTE model and the RADEX (ascl:1010.075) model connected to the LAMDA (ascl:1010.077) molecular collisional database. CASSIS can build a line list fitting the various transitions of a given species and to directly produce rotational diagrams from these lists. CASSIS is fully integrated into HIPE (ascl:1111.001), the Herschel Interactive Processing Environment, as a plug-in.

[ascl:1402.014] ARTIST: Adaptable Radiative Transfer Innovations for Submillimeter Telescopes

ARTIST is a suite of tools for comprehensive multi-dimensional radiative transfer calculations of dust and line emission, as well as their polarization, to help interpret observations from submillimeter telescopes. The ARTIST package consists of LIME, a radiative transfer code that uses adaptive gridding allowing simulations of sources with arbitrary multi-dimensional (1D, 2D, 3D) and time-dependent structures, thus ensuring rapid convergence; the DustPol and LinePol tools for modeling the polarization of the line and dust emission; and an interface run from Python scripts that manages the interaction between a general model library and LIME, and a graphical interface to simulate images.

[ascl:1402.015] BF_dist: Busy Function fitting

The "busy function" accurately describes the characteristic double-horn HI profile of many galaxies. Implemented in a C/C++ library and Python module called BF_dist, it is a continuous, differentiable function that consists of only two basic functions, the error function, erf(x), and a polynomial, |x|^n, of degree n >= 2. BF_dist offers great flexibility in fitting a wide range of HI profiles from the Gaussian profiles of dwarf galaxies to the broad, asymmetric double-horn profiles of spiral galaxies, and can be used to parametrize observed HI spectra of galaxies and the construction of spectral templates for simulations and matched filtering algorithms accurately and efficiently.

[ascl:1402.016] FAMA: Fast Automatic MOOG Analysis

FAMA (Fast Automatic MOOG Analysis), written in Perl, computes the atmospheric parameters and abundances of a large number of stars using measurements of equivalent widths (EWs) automatically and independently of any subjective approach. Based on the widely-used MOOG code, it simultaneously searches for three equilibria, excitation equilibrium, ionization balance, and the relationship between logn(FeI) and the reduced EWs. FAMA also evaluates the statistical errors on individual element abundances and errors due to the uncertainties in the stellar parameters. Convergence criteria are not fixed "a priori" but instead are based on the quality of the spectra.

[ascl:1402.017] UVMULTIFIT: Fitting astronomical radio interferometric data

UVMULTIFIT, written in Python, is a versatile library for fitting models directly to visibility data. These models can depend on frequency and fitting parameters in an arbitrary algebraic way. The results from the fit to the visibilities of sources with sizes smaller than the diffraction limit of the interferometer are superior to the output obtained from a mere analysis of the deconvolved images. Though UVMULTIFIT is based on the CASA package, it can be easily adapted to other analysis packages that have a Python API.

[ascl:1402.018] TARDIS: Temperature And Radiative Diffusion In Supernovae

TARDIS creates synthetic spectra for supernova ejecta and is sufficiently fast to allow exploration of the complex parameter spaces of models for SN ejecta. TARDIS uses Monte Carlo methods to obtain a self-consistent description of the plasma state and to compute a synthetic spectrum. It is written in Python with a modular design that facilitates the implementation of a range of physical approximations that can be compared to assess both accuracy and computational expediency; this allows users to choose a level of sophistication appropriate for their application.

[ascl:1402.019] ANAigm: Analytic model for attenuation by the intergalactic medium

ANAigm offers an updated version of the Madau model for the attenuation by the intergalactic neutral hydrogen against the radiation from distant objects. This new model is written in Fortran90 and predicts, for some redshifts, more than 0.5--1 mag different attenuation magnitudes through usual broad-band filters relative to the original Madau model.

[ascl:1402.020] XNS: Axisymmetric equilibrium configuration of neutron stars

XNS solves for the axisymmetric equilibrium configuration of neutron stars in general relativity. It can model differentially rotating and magnetic fields that are either purely toroidal, purely poloidal or in the mixed twisted torus configuration. Einsten's equations are solved using the XCFC approximation for the metric in spherical coordinates.

[ascl:1402.021] PyGFit: Python Galaxy Fitter

PyGFit measures PSF-matched photometry from images with disparate pixel scales and PSF sizes; its primary purpose is to extract robust spectral energy distributions (SEDs) from crowded images. It fits blended sources in crowded, low resolution images with models generated from a higher resolution image, thus minimizing the impact of crowding and also yielding consistently measured fluxes in different filters which minimizes systematic uncertainty in the final SEDs.

[ascl:1402.022] DexM: Semi-numerical simulations for very large scales

DexM (Deus ex Machina) efficiently generates density, halo, and ionization fields on very large scales and with a large dynamic range through seminumeric simulation. These properties are essential for reionization studies, especially those involving rare, massive QSOs, since one must be able to statistically capture the ionization field. DexM can also generate ionization fields directly from the evolved density field to account for the ionizing contribution of small halos. Semi-numerical simulations use more approximate physics than numerical simulations, but independently generate 3D cosmological realizations. DexM is portable and fast, and allows for explorations of wide swaths of astrophysical parameter space and an unprecedented dynamic range.

[ascl:1401.001] Kirin: N-body simulation library for GPUs

The use of graphics processing units offers an attractive alternative to specialized hardware, like GRAPE. The Kirin library mimics the behavior of the GRAPE hardware and uses the GPU to execute the force calculations. It is compatible with the GRAPE6 library; existing code that uses the GRAPE6 library can be recompiled and relinked to use the GPU equivalents of the GRAPE6 functions. All functions in the GRAPE6 library have an equivalent GPU implementation. Kirin can be used for direct N-body simulations as well as for treecodes; it can be run with shared-time steps or with block time-steps and allows non-softened potentials. As Kirin makes use of CUDA, it works only on NVIDIA GPUs.

[ascl:1401.002] SpacePy: Python-Based Tools for the Space Science Community

SpacePy provides data analysis and visualization tools for the space science community. Written in Python, it builds on the capabilities of the NumPy and MatPlotLib packages to make basic data analysis, modeling and visualization easier. It contains modules for handling many complex time formats, obtaining data from the OMNI database, and accessing the powerful Onera library. It contains a library of commonly used empirical relationships, performs association analysis, coordinate transformations, radiation belt modeling, and CDF reading, and creates publication quality plots.

[ascl:1401.003] PyMidas: Interface from Python to Midas

PyMidas is an interface between Python and MIDAS, the major ESO legacy general purpose data processing system. PyMidas allows a user to exploit both the rich legacy of MIDAS software and the power of Python scripting in a unified interactive environment. PyMidas also allows the usage of other Python-based astronomical analysis systems such as PyRAF.

[ascl:1401.004] Reflex: Graphical workflow engine for data reduction

Reflex provides an easy and flexible way to reduce VLT/VLTI science data using the ESO pipelines. It allows graphically specifying the sequence in which the data reduction steps are executed, including conditional stops, loops and conditional branches. It eases inspection of the intermediate and final data products and allows repetition of selected processing steps to optimize the data reduction. The data organization necessary to reduce the data is built into the system and is fully automatic; advanced users can plug their own modules and steps into the data reduction sequence. Reflex supports the development of data reduction workflows based on the ESO Common Pipeline Library. Reflex is based on the concept of a scientific workflow, whereby the data reduction cascade is rendered graphically and data seamlessly flow from one processing step to the next. It is distributed with a number of complete test datasets so users can immediately start experimenting and familiarize themselves with the system.

[ascl:1401.005] PyDrizzle: Python version of Drizzle

PyDrizzle provides a semi-automated interface for computing the parameters necessary for running Drizzle (ascl:1212.011). PyDrizzle performs the task of determining the parameters necessary for aligning images based on the WCS information in the input image headers, as well as any supplemental alignment information provided in shift files, and combines the images onto the same WCS. Though it does not identify cosmic rays, it has the ability to ignore pixels flagged as bad, such as pixels identified by other programs as affected by cosmic rays.

[ascl:1401.006] convolve_image.pro: Common-Resolution Convolution Kernels for Space- and Ground-Based Telescopes

The IDL package convolve_image.pro transforms images between different instrumental point spread functions (PSFs). It can load an image file and corresponding kernel and return the convolved image, thus preserving the colors of the astronomical sources. Convolution kernels are available for images from Spitzer (IRAC MIPS), Herschel (PACS SPIRE), GALEX (FUV NUV), WISE (W1 - W4), Optical PSFs (multi- Gaussian and Moffat functions), and Gaussian PSFs; they allow the study of the Spectral Energy Distribution (SED) of extended objects and preserve the characteristic SED in each pixel.

[ascl:1401.007] abundance: High Redshift Cluster Abundance

abundance, written in Fortran, provides driver and fitting routines to compute the predicted number of clusters in a ΛCDM cosmology that agrees with CMB, SN, BAO, and H0 measurements (up to 2010) at some specified parameter confidence and the mass that would rule out that cosmology at some specified sample confidence. It also computes the expected number of such clusters in the light cone and the Eddington bias factor that must be applied to observed masses.

[ascl:1401.008] massconvert: Halo Mass Conversion

massconvert, written in Fortran, provides driver and fitting routines for converting halo mass definitions from one spherical overdensity to another assuming an NFW density profile. In surveys that probe ever lower cluster masses and temperatures, sample variance is generally comparable to or greater than shot noise and thus cannot be neglected in deriving precision cosmological constraints; massconvert offers an accurate fitting formula for the conversion between different definitions of halo mass.

[ascl:1401.009] PPF module for CAMB

The main CAMB code supports smooth dark energy models with constant equation of state and sound speed of one, or a quintessence model based on a potential. This modified code generalizes it to support a time-dependent equation of state w(a) that is allowed to cross the phantom divide, i.e. w=-1 multiple times by implementing a Parameterized Post-Friedmann(PPF) prescription for the dark energy perturbations.

[ascl:1401.010] SunPy: Python for Solar Physicists

SunPy is a community-developed free and open-source software package for solar physics and is an alternative to the SolarSoft (ascl:1208.013) data analysis environment. SunPy provides data structures for representing the most common solar data types (images, lightcurves, and spectra) and integration with the Virtual Solar Observatory (VSO) and the Heliophysics Event Knowledgebase (HEK) for data acquisition.

[ascl:1312.001] SERPent: Scripted E-merlin Rfi-mitigation PipelinE for iNTerferometry

SERPent is an automated reduction and RFI-mitigation procedure that uses the SumThreshold methodology. It was originally developed for the LOFAR pipeline. SERPent is written in Parseltongue, enabling interaction with the Astronomical Image Processing Software (AIPS) program. Moreover, SERPent is a simple "out of the box" Python script, which is easy to set up and is free of compilers.

[ascl:1312.002] WND-CHARM: Multi-purpose image classifier

WND-CHARM quantitatively analyzes morphologies of galaxy mergers and associate galaxies by their morphology. It computes a large set (up to ~2700) of image features for each image based on the WND-CHARM algorithm. It can then split the images into training and test sets and classify them. The software extracts the image content descriptor from raw images, image transforms, and compound image transforms. The most informative features are then selected, and the feature vector of each image is used for classification and similarity measurement using Fisher discriminant scores and a variation of Weighted Nearest Neighbor analysis. WND-CHARM's results comparable favorably to the performance of task-specific algorithms developed for tested datasets. The simple user interface allows researchers who are not knowledgeable in computer vision methods and have no background in computer programming to apply image analysis to their data.

[ascl:1312.003] IMCOM: IMage COMbination

IMCOM allows for careful treatment of aliasing in undersampled imaging data and can be used to test the feasibility of multi-exposure observing strategies for space-based survey missions. IMCOM can also been used to explore focal plane undersampling for an optical space mission such as Euclid.

[ascl:1312.004] BIE: Bayesian Inference Engine

The Bayesian Inference Engine (BIE) is an object-oriented library of tools written in C++ designed explicitly to enable Bayesian update and model comparison for astronomical problems. To facilitate "what if" exploration, BIE provides a command line interface (written with Bison and Flex) to run input scripts. The output of the code is a simulation of the Bayesian posterior distribution from which summary statistics e.g. by taking moments, or determine confidence intervals and so forth, can be determined. All of these quantities are fundamentally integrals and the Markov Chain approach produces variates $ heta$ distributed according to $P( heta|D)$ so moments are trivially obtained by summing of the ensemble of variates.

[ascl:1312.005] XAssist: Automatic analysis of X-ray astrophysics data

XAssist provides automation of X-ray astrophysics, specifically data reprocessing, source detection, and preliminary spatial, temporal and spectral analysis for each source with sufficient counts, with an emphasis on galaxies. It has been used for data from Chandra, ROSAT, XMM-Newton, and other various projects.

[ascl:1312.006] LTL: The Little Template Library

LTL provides dynamic arrays of up to 7-dimensions, subarrays and slicing, support for fixed-size vectors and matrices including basic linear algebra operations, expression templates-based evaluation, and I/O facilities for ascii and FITS format files. Utility classes for command-line processing and configuration-file processing are provided as well.

[ascl:1312.007] SkyNet: Neural network training tool for machine learning in astronomy

SkyNet is an efficient and robust neural network training code for machine learning. It is able to train large and deep feed-forward neural networks, including autoencoders, for use in a wide range of supervised and unsupervised learning applications, such as regression, classification, density estimation, clustering and dimensionality reduction. SkyNet is implemented in C/C++ and fully parallelized using MPI.

[ascl:1312.008] BAMBI: Blind Accelerated Multimodal Bayesian Inference

BAMBI (Blind Accelerated Multimodal Bayesian Inference) is a Bayesian inference engine that combines the benefits of SkyNet (ascl:1312.007) with MultiNest (ascl:1109.006). It operated by simultaneously performing Bayesian inference using MultiNest and learning the likelihood function using SkyNet. Once SkyNet has learnt the likelihood to sufficient accuracy, inference finishes almost instantaneously.

[ascl:1312.009] YODA: Yet another Object Detection Application

YODA, implemented in C++, performs object detection, photometry and star-galaxy classification on astronomical images. Developed specifically to cope with the multi-band imaging data common in modern extragalactic imaging surveys, it is modular and therefore easily adaptable to specific needs. YODA works under conditions of inhomogeneous background noise across the detection frame, and performs accurate aperture photometry in image sets not sharing a common coordinate system or pixel scale as is often the case in present-day extragalactic survey work.

[ascl:1312.010] GalaxyCount: Galaxy counts and variance calculator

GalaxyCount calculates the number and standard deviation of galaxies in a magnitude limited observation of a given area. The methods to calculate both the number and standard deviation may be selected from different options. Variances may be computed for circular, elliptical and rectangular window functions.

[ascl:1312.011] A_phot: Photon Asymmetry

Photon asymmetry is a novel robust substructure statistic for X-ray cluster observations with only a few thousand counts; it exhibits better stability than power ratios and centroid shifts and has a smaller statistical uncertainty than competing substructure parameters, allowing for low levels of substructure to be measured with confidence. A_phot computes the photon asymmetry (A_phot) parameter for morphological classification of clusters and allows quantifying substructure in samples of distant clusters covering a wide range of observational signal-to-noise ratios. The python scripts are completely automatic and can be used to rapidly classify galaxy cluster morphology for large numbers of clusters without human intervention.

[ascl:1312.012] BINGO: BI-spectra and Non-Gaussianity Operator

The BI-spectra and Non-Gaussianity Operator (BINGO) code, written in Fortran, computes the scalar bi-spectrum and the non-Gaussianity parameter fNL in single field inflationary models involving the canonical scalar field. BINGO can calculate all the different contributions to the bi-spectrum and the parameter fNL for an arbitrary triangular configuration of the wavevectors.

[ascl:1312.013] CJAM: First and second velocity moments calculations

CJAM calculates first and second velocity moments using the Jeans Anisotropic MGE (JAM) models of Cappellari (2008) and Cappellari (2012). These models have been extended to calculate all three (x, y, z) first moments and all six (xx, yy, zz, xy, xz, yz) second moments. CJAM, written in C, is based on the IDL implementation of the line-of-sight calculations by Michele Cappellari.

[ascl:1312.014] SL1M: Synthesis through L1 Minimization

SL1M deconvolves radio synthesis images based on direct inversion of the measured visibilities that can deal with the non-coplanar base line effect and can be applied to telescopes with direction dependent gains. The code is more computationally demanding than some existing methods, but is highly parallelizable and scale well to clusters of CPUs and GPUs. The algorithm is also extremely flexible, allowing the solution of the deconvolution problem on arbitrarily placed pixels.

[ascl:1311.001] SciDB: Open Source DMAS for Scientific Research

SciDB is a DMAS (Data Management and Analytics Software System) optimized for data management of big data and for big analytics. SciDB is organized around multidimensional array storage, a generalization of relational tables, and is designed to be scalable up to petabytes and beyond. Complex analytics are simplified with SciDB because arrays and vectors are first-class objects with built-in optimized operations. Spatial operators and time-series analysis are easy to express. Interfaces to common scientific tools like R as well as programming languages like C++ and Python are provided.

[ascl:1311.002] PyCOOL: Cosmological Object-Oriented Lattice code

PyCOOL is a Python + CUDA program that solves the evolution of interacting scalar fields in an expanding universe. PyCOOL uses modern GPUs to solve this evolution and to make the computation much faster. The code includes numerous post-processing functions that provide useful information about the cosmological model, including various spectra and statistics of the fields.

[ascl:1311.003] AstroAsciiData: ASCII table Python module

ASCII tables continue to be one of the most popular and widely used data exchange formats in astronomy. AstroAsciiData, written in Python, imports all reasonably well-formed ASCII tables. It retains formatting of data values, allows column-first access, supports SExtractor style headings, performs column sorting, and exports data to other formats, including FITS, Numpy/Numarray, and LaTeX table format. It also offers interchangeable comment character, column delimiter and null value.

[ascl:1311.004] PlanetPack: Radial-velocity time-series analysis tool

PlanetPack facilitates and standardizes the advanced analysis of radial velocity (RV) data for the goal of exoplanets detection, characterization, and basic dynamical N-body simulations. PlanetPack is a command-line interpreter that can run either in an interactive mode or in a batch mode of automatic script interpretation.

[ascl:1311.005] Spheroid: Electromagnetic Scattering by Spheroids

Spheroid determines the size distribution of polarizing interstellar dust grains based on electromagnetic scattering by spheroidal particles. It contains subroutines to treat the case of complex refractive indices, and also includes checks for some limiting cases.

[ascl:1311.006] CIAO: Chandra Interactive Analysis of Observations

CIAO is a data analysis system written for the needs of users of the Chandra X-ray Observatory. Because Chandra data is 4-dimensional (2 spatial, time, energy) and each dimension has many independent elements, CIAO was built to handle N-dimensional data without concern about which particular axes were being analyzed. Apart from a few Chandra instrument tools, CIAO is mission independent. CIAO tools read and write several formats, including FITS images and tables (which includes event files) and IRAF imh files. CIAO is a powerful system for the analysis of many types of data.

[ascl:1311.007] CUPID: Clump Identification and Analysis Package

The CUPID package allows the identification and analysis of clumps of emission within 1, 2 or 3 dimensional data arrays. Whilst targeted primarily at sub-mm cubes, it can be used on any regularly gridded 1, 2 or 3D data. A variety of clump finding algorithms are implemented within CUPID, including the established ClumpFind (ascl:1107.014) and GAUSSCLUMPS (ascl:1406.018) algorithms. In addition, two new algorithms called FellWalker and Reinhold are also provided. CUPID allows easy inter-comparison between the results of different algorithms; the catalogues produced by each algorithm contains a standard set of columns containing clump peak position, clump centroid position, the integrated data value within the clump, clump volume, and the dimensions of the clump. In addition, pixel masks are produced identifying which input pixels contribute to each clump. CUPID is distributed as part of the Starlink (ascl:1110.012) software collection.

[ascl:1311.008] CUPID: Customizable User Pipeline for IRS Data

Written in c, the Customizable User Pipeline for IRS Data (CUPID) allows users to run the Spitzer IRS Pipelines to re-create Basic Calibrated Data and extract calibrated spectra from the archived raw files. CUPID provides full access to all the parameters of the BCD, COADD, BKSUB, BKSUBX, and COADDX pipelines, as well as the opportunity for users to provide their own calibration files (e.g., flats or darks). CUPID is available for Mac, Linux, and Solaris operating systems.

[ascl:1311.009] CosmoTherm: Thermalization code

CosmoTherm allows precise computation of CMB spectral distortions caused by energy release in the early Universe. Different energy-release scenarios (e.g., decaying or annihilating particles) are implemented using the Green's function of the cosmological thermalization problem, allowing fast computation of the distortion signal. The full thermalization problem can be solved on a case-by-case basis for a wide range of energy-release scenarios using the full PDE solver of CosmoTherm. A simple Monte-Carlo toolkit is included for parameter estimation and forecasts using the Green's function method.

[ascl:1311.010] ARPACK: Solving large scale eigenvalue problems

ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. The package is designed to compute a few eigenvalues and corresponding eigenvectors of a general n by n matrix A. It is most appropriate for large sparse or structured matrices A where structured means that a matrix-vector product w <- Av requires order n rather than the usual order n2 floating point operations. This software is based upon an algorithmic variant of the Arnoldi process called the Implicitly Restarted Arnoldi Method (IRAM). When the matrix A is symmetric it reduces to a variant of the Lanczos process called the Implicitly Restarted Lanczos Method (IRLM). These variants may be viewed as a synthesis of the Arnoldi/Lanczos process with the Implicitly Shifted QR technique that is suitable for large scale problems. For many standard problems, a matrix factorization is not required; only the action of the matrix on a vector is needed. ARPACK is capable of solving large scale symmetric, nonsymmetric, and generalized eigenproblems from significant application areas.

A common community-maintained repository for this software, ARPACK-NG (ascl:2306.049), is available.

[ascl:1311.011] MUSIC: MUlti-Scale Initial Conditions

MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10−4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.

[ascl:1311.012] ETC: Exposure Time Calculator

Written for the Wide-Field Infrared Survey Telescope (WFIRST) high-latitude survey, the exposure time calculator (ETC) works in both imaging and spectroscopic modes. In addition to the standard ETC functions (e.g. background and S/N determination), the calculator integrates over the galaxy population and forecasts the density and redshift distribution of galaxy shapes usable for weak lensing (in imaging mode) and the detected emission lines (in spectroscopic mode). The program may be useful outside of WFIRST but no warranties are made regarding its suitability for general purposes. The software is available for download; IPAC maintains a web interface for those who wish to run a small number of cases without having to download the package.

[ascl:1310.001] ORAC-DR: Astronomy data reduction pipeline

ORAC-DR is a generic data reduction pipeline infrastructure; it includes specific data processing recipes for a number of instruments. It is used at the James Clerk Maxwell Telescope, United Kingdom Infrared Telescope, AAT, and LCOGT. This pipeline runs at the JCMT Science Archive hosted by CADC to generate near-publication quality data products; the code has been in use since 1998.

[ascl:1310.002] PyMSES: Python modules for RAMSES

PyMSES provides a python solution for getting data out of RAMSES (ascl:1011.007) astrophysical fluid dynamics simulations. It permits transparent manipulation of large simulations and interfaces with common Python libraries and existing code, and can serve as a post-processing toolbox for data analysis. It also does three-dimensional volume rendering with a specific algorithm optimized to work on RAMSES distributed data (Guillet et al. 2011 and Jones et a. 2011).

[ascl:1310.003] AIDA: Adaptive Image Deconvolution Algorithm

AIDA is an implementation and extension of the MISTRAL myopic deconvolution method developed by Mugnier et al. (2004) (see J. Opt. Soc. Am. A 21:1841-1854). The MISTRAL approach has been shown to yield object reconstructions with excellent edge preservation and photometric precision when used to process astronomical images. AIDA improves upon the original MISTRAL implementation. AIDA, written in Python, can deconvolve multiple frame data and three-dimensional image stacks encountered in adaptive optics and light microscopic imaging.

[ascl:1310.004] AIRY: Astronomical Image Restoration in interferometrY

AIRY simulates optical and near-infrared interferometric observations; it can also perform subsequent image restoration or deconvolution. It is based on the CAOS (ascl:1106.017) Problem Solving Environment. Written in IDL, it consists of a set of specific modules, each handling a particular task.

[ascl:1310.005] ASPRO 2: Astronomical Software to PRepare Observations

ASPRO 2 (Astronomical Software to PRepare Observations) is an observation preparation tool for interferometric observations with the VLTI or other interferometers such as CHARA and SUSI. It is a Java standalone program that provides a dynamic graphical interface to simulate the projected baseline evolution during observations (super-synthesis) and derive visibilities for targets (i.e., single star, binaries, user defined FITS image). It offers other useful functions such as the ability to load and save your observation settings and generate Observing Blocks.

[ascl:1310.006] AIPSLite: ParselTongue extension for distributed AIPS processing

AIPSLite is an extension for ParselTongue (ascl:1208.020) that allows machines without an AIPS (ascl:9911.003) distribution to bootstrap themselves with a minimal AIPS environment. This allows deployment of AIPS routines on distributed systems, which is useful when data can be easily be split into smaller chunks and handled independently.

[ascl:1310.007] SMURF: SubMillimeter User Reduction Facility

SMURF reduces submillimeter single-dish continuum and heterodyne data. It is mainly targeted at data produced by the James Clerk Maxwell Telescope but data from other telescopes have been reduced using the package. SMURF is released as part of the bundle that comprises Starlink (ascl:1110.012) and most of the packages that use it. The two key commands are MAKEMAP for the creation of maps from sub millimeter continuum data and MAKECUBE for the creation of data cubes from heterodyne array instruments. The software can also convert data from legacy JCMT file formats to the modern form to allow it to be processed by MAKECUBE. SMURF is a core component of the ORAC-DR (ascl:1310.001) data reduction pipeline for JCMT.

[ascl:1310.008] SPECX: Spectral Line Data Reduction Package

SPECX is a general purpose line data reduction system. It can read and write FITS data cubes but has specialist support for the GSD format data from the James Clerk Maxwell Telescope. It includes commands to store and retrieve intermediate spectra in storage registers and perform the fitting and removal of polynomial, harmonic and Gaussian baselines.

SPECX can filter and edit spectra and list and display spectra on a graphics terminal. It is able to perform Fourier transform and power spectrum calculations, process up to eight spectra (quadrants) simultaneously with either the same or different center, and assemble a number of reduced individual spectra into a map file and contour or greyscale any plane or planes of the resulting cube.

Two versions of SPECX are distributed. Version 6.x is the VMS and Unix version and is distributed as part of the Starlink software collection. Version 7.x is a complete rewrite of SPECX distributed for Windows.

[ascl:1309.001] AstroImageJ: ImageJ for Astronomy

AstroImageJ is generic ImageJ (ascl:1206.013) with customizations to the base code and a packaged set of astronomy specific plugins. It reads and writes FITS images with standard headers, displays astronomical coordinates for images with WCS, supports photometry for developing color-magnitude data, offers flat field, scaled dark, and non-linearity processing, and includes tools for precision photometry that can be used during real-time data acquisition.

[ascl:1309.002] VAPHOT: Precision differential aperture photometry package

VAPHOT is an aperture photometry package for precise time−series photometry of uncrowded fields, geared towards the extraction of target lightcurves of eclipsing or transiting systems. Its photometric main routine works within the IRAF (ascl:9911.002) environment and is built upon the standard aperture photometry task 'phot' from IRAF, using optimized aperture sizes. The associated analysis program 'VANALIZ' works in the IDL environment. It performs differential photometry with graphical and numerical output. VANALIZ produces plots indicative of photometric stability and permits the interactive evaluation and weighting of comparison stars. Also possible is the automatic or manual suppression of data-points and the output of statistical analyses. Several methods for the calculation of the reference brightness are offered. Specific routines for the analysis of transit 'on'-'off' photometry, comparing the target brightness inside against outside a transit are also available.

[ascl:1309.003] LOSP: Liège Orbital Solution Package

LOSP is a FORTRAN77 numerical package that computes the orbital parameters of spectroscopic binaries. The package deals with SB1 and SB2 systems and is able to adjust either circular or eccentric orbits through a weighted fit.

[ascl:1309.004] Spherical: Geometry operations and searches on spherical surfaces

The Spherical Library provides an efficient and accurate mathematical representation of shapes on the celestial sphere, such as sky coverage and footprints. Shapes of arbitrary complexity and size can be dynamically created from simple building blocks, whose exact area is also analytically computed. This methodology is also perfectly suited for censoring problematic parts of datasets, e.g., bad seeing, satellite trails or diffraction spikes of bright stars.

[ascl:1309.005] SATMC: SED Analysis Through Monte Carlo

SATMC is a general purpose, MCMC-based SED fitting code written for IDL and Python. Following Bayesian statistics and Monte Carlo Markov Chain algorithms, SATMC derives the best fit parameter values and returns the sampling of parameter space used to construct confidence intervals and parameter-parameter confidence contours. The fitting may cover any range of wavelengths. The code is designed to incorporate any models (and potential priors) of the user's choice. The user guide lists all the relevant details for including observations, models and usage under both IDL and Python.

[ascl:1309.006] VOPlot: Toolkit for Scientific Discovery using VOTables

VOPlot is a tool for visualizing astronomical data. It was developed in Java and acts on data available in VOTABLE, ASCII and FITS formats. VOPlot is available as a stand alone version, which is to be installed on the user's machine, or as a web-based version fully integrated with the VizieR database.

[ascl:1309.007] VOMegaPlot: Plotting millions of points

VOMegaPlot, a Java based tool, has been developed for visualizing astronomical data that is available in VOTable format. It has been specifically optimized for handling large number of points (in the range of millions). It has the same look and feel as VOPlot (ascl:1309.006) and both these tools have certain common functionality.

[ascl:1309.008] VOStat: Statistical analysis of astronomical data

VOStat allows astronomers to use both simple and sophisticated statistical routines on large datasets. This tool uses the large public-domain statistical computing package R. Datasets can be uploaded in either ASCII or VOTABLE (preferred) format. The statistical computations are performed by the VOStat and results are returned to the user.

[ascl:1308.001] SMILE: Orbital analysis and Schwarzschild modeling of triaxial stellar systems

SMILE is interactive software for studying a variety of 2D and 3D models, including arbitrary potentials represented by a basis-set expansion, a spherical-harmonic expansion with coefficients being smooth functions of radius (splines), or a set of fixed point masses. Its main features include:

  • orbit integration in various 2d and 3d potentials (including N-body and basis-set representations of an arbitrary potential);
  • methods for analysis of orbital class, fundamental frequencies, regular or chaotic nature of an orbit, computation of Lyapunov exponents;
  • Poincaré sections (in 2d) and frequency maps (in 3d) for analyzing orbital structure of potential;
  • construction of self-consistent Schwarzschild models; and
  • convenient visualization and integrated GUI environment, and a console scriptable version.
SMILE is portable to different platforms including MS Windows, Linux and Mac.

[ascl:1308.002] LOSSCONE: Capture rates of stars by a supermassive black hole

LOSSCONE computes the rates of capture of stars by supermassive black holes. It uses a stationary and time-dependent solutions for the Fokker-Planck equation describing the evolution of the distribution function of stars due to two-body relaxation, and works for arbitrary spherical and axisymmetric galactic models that are provided by the user in the form of M(r), the cumulative mass as a function of radius.

[ascl:1308.003] MapCurvature: Map Projections

MapCurvature, written in IDL, can create map projections with Goldberg-Gott indicatrices. These indicatrices measure the flexion and skewness of a map, and are useful for determining whether features are faithfully reproduced on a particular projection.

[ascl:1308.004] LensEnt2: Maximum-entropy weak lens reconstruction

LensEnt2 is a maximum entropy reconstructor of weak lensing mass maps. The method takes each galaxy shape as an independent estimator of the reduced shear field and incorporates an intrinsic smoothness, determined by Bayesian methods, into the reconstruction. The uncertainties from both the intrinsic distribution of galaxy shapes and galaxy shape estimation are carried through to the final mass reconstruction, and the mass within arbitrarily shaped apertures are calculated with corresponding uncertainties. The input is a galaxy ellipticity catalog with each measured galaxy shape treated as a noisy tracer of the reduced shear field, which is inferred on a fine pixel grid assuming positivity, and smoothness on scales of w arcsec where w is an input parameter. The ICF width w can be chosen by computing the evidence for it.

[ascl:1308.005] APPSPACK: Asynchronous Parallel Pattern Search

APPSPACK is serial or parallel, derivative-free optimization software for solving nonlinear unconstrained, bound-constrained, and linearly-constrained optimization problems, with possibly noisy and expensive objective functions.

[ascl:1308.006] BASIN: Beowulf Analysis Symbolic INterface

BASIN (Beowulf Analysis Symbolic INterface) is a flexible, integrated suite of tools for multiuser parallel data analysis and visualization that allows researchers to harness the power of Beowulf PC clusters and multi-processor machines without necessarily being experts in parallel programming. It also includes general tools for data distribution and parallel operations on distributed data for developing libraries for specific tasks.

[ascl:1308.007] SYNAPPS: Forward-modeling of supernova spectroscopy data sets

SYNAPPS is a spectrum fitter embedding a highly parameterized synthetic SN spectrum calculation within a parallel asynchronous optimizer. This open-source code is aimed primarily at the problem of systematically interpreting large sets of SN spectroscopy data.

[ascl:1308.008] SYN++: Standalone SN spectrum synthesis

SYN++ is a standalone SN spectrum synthesis program. It is a rewrite of the original SYNOW (ascl:1010.055) code in modern C++. It offers further enhancements, a new structured input control file format, and the atomic data files have been repackaged and are more complete than those of SYNOW.

[ascl:1308.009] CReSyPS: Stellar population synthesis code

CReSyPS (Code Rennais de Synthèse de Populations Stellaires) is a stellar population synthesis code that determines core overshooting amount for Magellanic clouds main sequence stars.

[ascl:1308.010] GYRE: Stellar oscillation code

GYRE is an oscillation code that solves the stellar pulsation equations (both adiabatic and non-adiabatic) using a novel Magnus Multiple Shooting numerical scheme devised to overcome certain weaknesses of the usual relaxation and shooting schemes. The code is accurate (up to 6th order in the number of grid points), robust, and makes efficient use of multiple processor cores and/or nodes.

[ascl:1308.011] CRUSH: Comprehensive Reduction Utility for SHARC-2 (and more...)

CRUSH is an astronomical data reduction/imaging tool for certain imaging cameras, especially at the millimeter, sub-millimeter, and far-infrared wavelengths. It supports the SHARC-2, LABOCA, SABOCA, ASZCA, p-ArTeMiS, PolKa, GISMO, MAKO and SCUBA-2 instruments. The code is written entirely in Java, allowing it to run on virtually any platform. It is normally run from the command-line with several arguments.

[ascl:1308.012] RADLite: Raytracer for infrared line spectra

RADLite is a raytracer that is optimized for producing infrared line spectra and images from axisymmetric density structures, originally developed to function on top of the dust radiative transfer code RADMC. RADLite can consistently deal with a wide range of velocity gradients, such as those typical for the inner regions of protoplanetary disks. The code is intended as a back-end for chemical and excitation codes, and can rapidly produce spectra of thousands of lines for grids of models for comparison with observations. It includes functionality for simulating telescopic images for optical/IR/midIR/farIR telescopes. It takes advantage of multi-threaded CPUs and includes an escape-probability non-LTE module.

[ascl:1308.013] THELI GUI: Optical, near- & mid-infrared imaging data reduction

THELI is an easy-to-use, end-to-end pipeline for the reduction of any optical, near-IR and mid-IR imaging data. It combines a variety of processing algorithms and third party software into a single, homogeneous tool. Over 90 optical and infrared instruments at observatories world-wide are pre-configured; more can be added by the user. The code's online appendix contains three walk-through examples using public data (optical, near-IR and mid-IR) and additional online documentation is available for training and troubleshooting.

[ascl:1308.014] SPEX: High-resolution cosmic X-ray spectra analysis

SPEX is optimized for the analysis and interpretation of high-resolution cosmic X-ray spectra. The software is especially suited for fitting spectra obtained by current X-ray observatories like XMM-Newton, Chandra, and Suzaku. SPEX can fit multiple spectra with different model components simultaneously and handles highly complex models with many free parameters.

[ascl:1308.015] Ceph_code: Cepheid light-curves fitting

Ceph_code fits multi-band Cepheid light-curves using templates derived from OGLE observations. The templates include short period stars (<10 day) and overtone stars.

[ascl:1308.016] JHelioviewer: Visualization software for solar physics data

JHelioview is open source visualization software for solar physics data. The JHelioviewer client application enables users to browse petabyte-scale image archives; the JHelioviewer server integrates a JPIP server, metadata catalog, and an event server. JHelioview uses the JPEG 2000 image compression standard, which provides efficient access to petabyte-scale image archives; JHelioviewer also allows users to locate and manipulate specific data sets.

[ascl:1308.017] ChiantiPy: Python package for the CHIANTI atomic database

ChiantiPy is an object-orient Python package for calculating astrophysical spectra using the CHIANTI atomic database for astrophysical spectroscopy. It provides access to the database and the ability to calculate various physical quantities for the interpretation of astrophysical spectra.

[ascl:1308.018] MoogStokes: Zeeman polarized radiative transfer

MOOGStokes is a version of the MOOG one-dimensional local thermodynamic equilibrium radiative transfer code that incorporates a Stokes vector treatment of polarized radiation through a magnetic medium. It consists of three complementary programs that together can synthesize the disk-averaged emergent spectrum of a star with a magnetic field. The MOOGStokes package synthesizes emergent spectra of stars with magnetic fields in a familiar computational framework and produces disk-averaged spectra for all Stokes vectors ( I, Q, U, V ), normalized by the continuum.

[ascl:1307.001] DustEM: Dust extinction and emission modelling

DustEM computes the extinction and the emission of interstellar dust grains heated by photons. It is written in Fortran 95 and is jointly developed by IAS and CESR. The dust emission is calculated in the optically thin limit (no radiative transfer) and the default spectral range is 40 to 108 nm. The code is designed so dust properties can easily be changed and mixed and to allow for the inclusion of new grain physics.

[ascl:1307.002] Monte Python: Monte Carlo code for CLASS in Python

Monte Python is a parameter inference code which combines the flexibility of the python language and the robustness of the cosmological code CLASS (ascl:1106.020) into a simple and easy to manipulate Monte Carlo Markov Chain code.

This version has been archived and replaced by MontePython 3 (ascl:1805.027).

[ascl:1307.003] K3Match: Point matching in 3D space

K3Match is a C library with Python bindings for fast matching of points in 3D space. It uses an implementation of three dimensional binary trees to efficiently find matches between points in 3D space. Two lists of points are compared and match indices as well as distances are given. K3Match can find either the nearest neighbour or all matches within a given search distance in 3D Cartesian space or on the surface of the 2D unit sphere in standard spherical or celestial coordinates.

[ascl:1307.004] FieldInf: Field Inflation exact integration routines

FieldInf is a collection of fast modern Fortran routines for computing exactly the background evolution and primordial power spectra of any single field inflationary models. It implements reheating without any assumptions through the "reheating parameter" R allowing robust inflationary parameter estimations and inference on the reheating energy scale. The underlying perturbation code actually deals with N fields minimally-coupled and/or non-minimally coupled to gravity and works for flat FLRW only.

[ascl:1307.005] LENSVIEW: Resolved gravitational lens images modeling

Lensview models resolved gravitational lens systems based on LensMEM but using the Skilling & Bryan MEM algorithm. Though its primary purpose is to find statistically acceptable lens models for lensed images and to reconstruct the surface brightness profile of the source, LENSVIEW can also be used for more simple tasks such as projecting a given source through a lens model to generate a “true” image by conserving surface brightness. The user can specify complicated lens models based on one or more components, such as softened isothermal ellipsoids, point masses, exponential discs, and external shears; LENSVIEW generates a best-fitting source matching the observed data for each specific combination of model parameters.

[ascl:1307.006] im2shape: Bayesian Galaxy Shape Estimation

im2shape is a Bayesian approach to the problem of accurate measurement of galaxy ellipticities for weak lensing studies, in particular cosmic shear. im2shape parameterizes galaxies as sums of Gaussians, convolved with a psf which is also a sum of Gaussians. The uncertainties in the output parameters are calculated using a Markov Chain Monte Carlo approach.

[ascl:1307.007] AstroTaverna: Tool for Scientific Workflows in Astronomy

AstroTaverna is a plugin for Taverna Workbench that provides the means to build astronomy workflows using Virtual Observatory services discovery and efficient manipulation of VOTables (based on STIL tool set). It integrates SAMP-enabled software, allowing data exchange and communication among local VO tools, as well as the ability to execute Aladin scripts and macros.

[ascl:1307.008] Obit: Radio Astronomy Data Handling

Obit is a group of software packages for handling radio astronomy data, especially interferometric and single dish OTF imaging. Obit is primarily an environment in which new data processing algorithms can be developed and tested but which can also be used for production processing of a certain range of scientific problems. The package supports both prepackaged, compiled tasks and a python interface to the major class functionality to allow rapid prototyping using python scripts; it allows access to multiple disk--resident data formats, in particular access to either AIPS disk data or FITS files. Obit applications are interoperable with Classic AIPS and the ObitTalk python interface gives access to AIPS tasks as well as Obit libraries and tasks.

[ascl:1307.009] MAH: Minimum Atmospheric Height

MAH calculates the posterior distribution of the "minimum atmospheric height" (MAH) of an exoplanet by inputting the joint posterior distribution of the mass and radius. The code collapses the two dimensions of mass and radius into a one dimensional term that most directly speaks to whether the planet has an atmosphere or not. The joint mass-radius posteriors derived from a fit of some exoplanet data (likely using MCMC) can be used by MAH to evaluate the posterior distribution of R_MAH, from which the significance of a non-zero R_MAH (i.e. an atmosphere is present) is calculated.

[ascl:1307.010] cosmoxi2d: Two-point galaxy correlation function calculation

Cosmoxi2d is written in C and computes the theoretical two-point galaxy correlation function as a function of cosmological and galaxy nuisance parameters. It numerically evaluates the model described in detail in Reid and White 2011 (arxiv:1105.4165) and Reid et al. 2012 (arxiv:1203.6641) for the multipole moments (up to ell = 4) for the observed redshift space correlation function of biased tracers as a function of cosmological (though an input linear matter power spectrum, growth rate f, and Alcock-Paczynski geometric factors alphaperp and alphapar) as well as nuisance parameters describing the tracers (bias and small scale additive velocity dispersion, isotropicdisp1d).

This model works best for highly biased tracers where the 2nd order bias term is small. On scales larger than 100 Mpc, the code relies on 2nd order Lagrangian Perturbation theory as detailed in Matsubara 2008 (PRD 78, 083519), and uses the analytic version of Reid and White 2011 on smaller scales.

[ascl:1307.011] PhoSim: Photon Simulator

The Photon Simulator (PhoSim) is a set of fast photon Monte Carlo codes used to calculate the physics of the atmosphere, telescope, and detector by using modern numerical techniques applied to comprehensive physical models. PhoSim generates images by collecting photons into pixels. The code takes the description of what astronomical objects are in the sky at a particular time (the instance catalog) as well as the description of the observing configuration (the operational parameters) and produces a realistic data stream of images that are similar to what a real telescope would produce. PhoSim was developed for large aperture wide field optical telescopes, such as the planned design of LSST. The initial version of the simulator also targeted the LSST telescope and camera design, but the code has since been broadened to include existing telescopes of a related nature. The atmospheric model, in particular, includes physical approximations that are limited to this general context.

[ascl:1307.012] ITERA: IDL Tool for Emission-line Ratio Analysis

ITERA, the IDL Tool for Emission-line Ratio Analysis, is an IDL widget tool that allows you to plot ratios of any strong atomic and ionized emission lines as determined by standard photoionization and shock models. These "line ratio diagrams" can then be used to determine diagnostics for nebulae excitation mechanisms or nebulae parameters such as density, temperature, metallicity, etc. ITERA can also be used to determine line sensitivities to such parameters, compare observations with the models, or even estimate unobserved line fluxes.

[ascl:1307.013] SIMX: Event simulator

SIMX simulates a photon-counting detector's response to an input source, including a simplified model of any telescope. The code is not a full ray-trace, but a convolution tool that uses standard descriptions of telescope PSF (via either a simple Gaussian parameter, an energy-dependent encircled-energy function, or an image of the PSF) and the detector response (using the OGIP response function) to model how sources will appear. simx uses a predefined set of PSFs, vignetting information, and instrumental responses and outputs to make the simulation. It is designed to be a 'approximation' tool to estimate issues such as source confusion, background effects, pileup, and other similar issues.

[ascl:1307.014] Shapelets: Image Modelling

Shapelets are a complete, orthonormal set of 2D basis functions constructed from Laguerre or Hermite polynomials weighted by a Gaussian. A linear combination of these functions can be used to model any image, in a similar way to Fourier or wavelet synthesis. The shapelet decomposition is particularly efficient for images localized in space, and provide a high level of compression for individual galaxies in astronomical data. The basis has many elegant mathematical properties that make it convenient for image analysis and processing.

[ascl:1307.015] CTI Correction Code

Charge Transfer Inefficiency (CTI) due to radiation damage above the Earth's atmosphere creates spurious trailing in images from Charge-Coupled Device (CCD) imaging detectors. Radiation damage also creates unrelated warm pixels, which can be used to measure CTI. This code provides pixel-based correction for CTI and has proven effective in Hubble Space Telescope Advanced Camera for Surveys raw images, successfully reducing the CTI trails by a factor of ~30 everywhere in the CCD and at all flux levels. The core is written in java for speed, and a front-end user interface is provided in IDL. The code operates on raw data by returning individual electrons to pixels from which they were unintentionally dragged during readout. Correction takes about 25 minutes per ACS exposure, but is trivially parallelisable to multiple processors.

[ascl:1307.016] orbfit: Orbit fitting software

Orbfit determines positions and orbital elements, and associated uncertainties, of outer solar system planets. The orbit-fitting procedure is greatly streamlined compared with traditional methods because acceleration can be treated as a perturbation to the inertial motion of the body. Orbfit quickly and accurately calculates orbital elements and ephemerides and their associated uncertainties for targets ≳ 10 AU from the Sun and produces positional estimates and uncertainty ellipses even in the face of the substantial degeneracies of short-arc orbit fits; the sole a priori assumption is that the orbit should be bound or nearly so.

[ascl:1307.017] NEST: Noble Element Simulation Technique

NEST (Noble Element Simulation Technique) offers comprehensive, accurate, and precise simulation of the excitation, ionization, and corresponding scintillation and electroluminescence processes in liquid noble elements, useful for direct dark matter detectors, double beta decay searches, PET scans, and general radiation detection technology. Written in C++, NEST is an add-on module for the Geant4 simulation package that incorporates more detailed physics than is currently available into the simulation of scintillation. NEST is of particular use for low-energy nuclear recoils. All available liquid xenon data on nuclear recoils and electron recoils to date have been taken into consideration in arriving at the current models. NEST also handles the magnitude of the light and charge yields of nuclear recoils, including their electric field dependence, thereby shedding light on the possibility of detection or exclusion of a low-mass dark matter WIMP by liquid xenon detectors.

[ascl:1307.018] ETC++: Advanced Exposure-Time Calculations

ETC++ is a exposure-time calculator that considers the effect of cosmic rays, undersampling, dithering, and imperfect pixel response functions. Errors on astrometry and galaxy shape measurements can be predicted as well as photometric errors.

[ascl:1307.019] PURIFY: Tools for radio-interferometric imaging

PURIFY is a collection of routines written in C that implements different tools for radio-interferometric imaging including file handling (for both visibilities and fits files), implementation of the measurement operator and set-up of the different optimization problems used for image deconvolution. The code calls the generic Sparse OPTimization (SOPT) (ascl:1307.020) package to solve the imaging optimization problems.

[ascl:1307.020] SOPT: Sparse OPTimisation

SOPT (Sparse OPTimisation) is a C implementation of the Sparsity Averaging Reweighted Analysis (SARA) algorithm. The approach relies on the observation that natural images exhibit strong average sparsity; average sparsity outperforms state-of-the-art priors that promote sparsity in a single orthonormal basis or redundant frame, or that promote gradient sparsity.

[ascl:1306.001] SAC: Sheffield Advanced Code

The Sheffield Advanced Code (SAC) is a fully non-linear MHD code designed for simulations of linear and non-linear wave propagation in gravitationally strongly stratified magnetized plasma. It was developed primarily for the forward modelling of helioseismological processes and for the coupling processes in the solar interior, photosphere, and corona; it is built on the well-known VAC platform that allows robust simulation of the macroscopic processes in gravitationally stratified (non-)magnetized plasmas. The code has no limitations of simulation length in time imposed by complications originating from the upper boundary, nor does it require implementation of special procedures to treat the upper boundaries. SAC inherited its modular structure from VAC, thereby allowing modification to easily add new physics.

[ascl:1306.002] grmonty: Relativistic radiative transport Monte Carlo code

grmonty is a Monte Carlo radiative transport code intended for calculating spectra of hot, optically thin plasmas in full general relativity. The code models hot accretion flows in the Kerr metric, it incorporates synchrotron emission and absorption and Compton scattering. grmonty can be readily generalized to account for other radiative processes and an arbitrary spacetime.

[ascl:1306.003] Harmony: Synchrotron Emission Coefficients

Harmony is a general numerical scheme for evaluating MBS emission and absorption coefficients for both polarized and unpolarized light in a plasma with a general distribution function.

[ascl:1306.004] PROM4: 1D isothermal and isobaric modeler for solar prominences

PROM4 computes simple models of solar prominences which consist of plane-parallel slabs standing vertically above the solar surface. Each model is defined by 5 parameters: temperature, density, geometrical thickness, microturbulent velocity and height above the solar surface. PROM4 solves the equations of radiative transfer, statistical equilibrium, ionization and pressure equilibria, and computes electron and hydrogen level populations and hydrogen line profiles. Written in Fortran 90 and with two versions available (one with text in English, one with text in French), the code needs 64-bit arithmetic for real numbers.

PROM7 (ascl:1805.023) is a more recent version of this code.

[ascl:1306.005] PROS: Multi-mission X-ray analysis software system

PROS is a multi-mission x-ray analysis software system designed to run under IRAF. The PROS software includes spatial, spectral, timing, data I/O and conversion routines, plotting applications, and general algorithms for performing arithmetic operations with imaging data.

[ascl:1306.006] BEHR: Bayesian Estimation of Hardness Ratios

BEHR is a standalone command-line C program designed to quickly estimate the hardness ratios and their uncertainties for astrophysical sources. It is especially useful in the Poisson regime of low counts, and computes the proper uncertainty regardless of whether the source is detected in both passbands or not.

[ascl:1306.007] Tapir: A web interface for transit/eclipse observability

Tapir is a set of tools, written in Perl, that provides a web interface for showing the observability of periodic astronomical events, such as exoplanet transits or eclipsing binaries. The package provides tools for creating finding charts for each target and airmass plots for each event. The code can access target lists that are stored on-line in a Google spreadsheet or in a local text file.

[ascl:1306.008] MAPPINGS III: Modelling And Prediction in PhotoIonized Nebulae and Gasdynamical Shocks

MAPPINGS III is a general purpose astrophysical plasma modelling code. It is principally intended to predict emission line spectra of medium and low density plasmas subjected to different levels of photoionization and ionization by shockwaves. MAPPINGS III tracks up to 16 atomic species in all stages of ionization, over a useful range of 102 to 108 K. It treats spherical and plane parallel geometries in equilibrium and time-dependent models. MAPPINGS III is useful for computing models of HI and HII regions, planetary nebulae, novae, supernova remnants, Herbig-Haro shocks, active galaxies, the intergalactic medium and the interstellar medium in general. The present version of MAPPINGS III is a large FORTRAN program that runs with a simple TTY interface for historical and portability reasons. A newer version of this software, MAPPINGS V (ascl:1807.005), is available.

[ascl:1306.009] STF: Structure Finder

STF is a general structure finder designed to find halos, subhaloes, and tidal debris in N-body simulations. The current version is designed to read in "particle data" (that is SPH N-body data), but a simple modification of the I/O can have it read grid data from Grid based codes.

This code has been updated and renamed to VELOCIraptor-STF (ascl:1911.020).

[ascl:1306.010] MADCOW: Microwave Anisotropy Dataset Computational softWare

MADCOW is a set of parallelized programs written in ANSI C and Fortran 77 that perform a maximum likelihood analysis of visibility data from interferometers observing the cosmic microwave background (CMB) radiation. This software has been used to produce power spectra of the CMB with the Very Small Array (VSA) telescope.

[ascl:1306.011] Pico: Parameters for the Impatient Cosmologist

Pico is an algorithm that quickly computes the CMB scalar, tensor and lensed power spectra, the matter transfer function and the WMAP 5 year likelihood. It is intended to accelerate parameter estimation codes; Pico can compute the CMB power spectrum and matter transfer function, as well as any computationally expensive likelihoods, in a few milliseconds. It is extremely fast and accurate over a large volume of parameter space and its accuracy can be improved by using a larger training set. More generally, Pico allows using massively parallel computing resources, including distributed computing projects such as Cosmology@Home, to speed up the slow steps in inherently sequential calculations.

[ascl:1306.012] LRG DR7 Likelihood Software

This software computes likelihoods for the Luminous Red Galaxies (LRG) data from the Sloan Digital Sky Survey (SDSS). It includes a patch to the existing CAMB software (ascl:1102.026; the February 2009 release) to calculate the theoretical LRG halo power spectrum for various models. The code is written in Fortran 90 and has been tested with the Intel Fortran 90 and GFortran compilers.

[ascl:1306.013] Bessel: Fast Bessel Function Jn(z) Routine for Large n,z

Bessel, written in the C programming language, uses an accurate scheme for evaluating Bessel functions of high order. It has been extensively tested against a number of other routines, demonstrating its accuracy and efficiency.

[ascl:1306.014] ZEUS-2D: Simulation of fluid dynamical flows

ZEUS-2D is a hydrodynamics code based on ZEUS which adds a covariant differencing formalism and algorithms for compressible hydrodynamics, MHD, and radiation hydrodynamics (using flux-limited diffusion) in Cartesian, cylindrical, or spherical polar coordinates.

[ascl:1306.015] VHD: Viscous pseudo-Newtonian accretion

VHD is a numerical study of viscous fluid accretion onto a black hole. The flow is axisymmetric and uses a pseudo-Newtonian potential to model relativistic effects near the event horizon. VHD is based on ZEUS-2D (Stone & Norman 1992) with the addition of an explicit scheme for the viscosity.

[ascl:1306.016] Yaxx: Yet another X-ray extractor

Yaxx is a Perl script that facilitates batch data processing using Perl open source software and commonly available software such as CIAO/Sherpa, S-lang, SAS, and FTOOLS. For Chandra and XMM analysis it includes automated spectral extraction, fitting, and report generation. Yaxx can be run without climbing an extensive learning curve; even so, yaxx is highly configurable and can be customized to support complex analysis. yaxx uses template files and takes full advantage of the unique Sherpa / S-lang environment to make much of the processing user configurable. Although originally developed with an emphasis on X-ray data analysis, yaxx evolved to be a general-purpose pipeline scripting package.

[ascl:1305.001] ESTER: Evolution STEllaire en Rotation

The ESTER code computes the steady state of an isolated star of mass larger than two solar masses. The only convective region computed as such is the core where isentropy is assumed. ESTER provides solutions of the partial differential equations, for the pressure, density, temperature, angular velocity and meridional velocity for the whole volume. The angular velocity (differential rotation) and meridional circulation are computed consistently with the structure and are driven by the baroclinic torque. The code uses spectral methods, both radially and horizontally, with spherical harmonics and Chebyshev polynomials. The iterations follow Newton's algorithm. The code is object-oriented and is written in C++; a python suite allows an easy visualization of the results. While running, PGPLOT graphs are displayed to show evolution of the iterations.

[ascl:1305.002] pynbody: N-Body/SPH analysis for python

Pynbody is a lightweight, portable, format-transparent analysis package for astrophysical N-body and smooth particle hydrodynamic simulations supporting PKDGRAV/Gasoline, Gadget, N-Chilada, and RAMSES AMR outputs. Written in python, the core tools are accompanied by a library of publication-level analysis routines.

[ascl:1305.003] TPM: Tree-Particle-Mesh code

TPM carries out collisionless (dark matter) cosmological N-body simulations, evolving a system of N particles as they move under their mutual gravitational interaction. It combines aspects of both Tree and Particle-Mesh algorithms. After the global PM forces are calculated, spatially distinct regions above a given density contrast are located; the tree code calculates the gravitational interactions inside these denser objects at higher spatial and temporal resolution. The code is parallel and uses MPI for message passing.

[ascl:1305.004] AdaptaHOP: Subclump finder

AdaptaHOP is a structure and substructure detector. It reads an input particle distribution file and can compute the mean square distance between each particle and its nearest neighbors or the SPH density associated to each particle + the list of its nearest neighbors. It can also read an input particle distribution and a neighbors file (output from a previous run) and output the tree of the structures in structures.

[ascl:1305.005] PkdGRAV2: Parallel fast-multipole cosmological code

PkdGRAV2 is a high performance N-body treecode for self-gravitating astrophysical simulations. It is designed to run efficiently in serial and on a wide variety of parallel computers including both shared memory and message passing architectures. It can spatially adapt to large ranges in particle densities, and temporally adapt to large ranges in dynamical timescales. The code uses a non-standard data structure for efficiently calculating the gravitational forces, a variant on the k-D tree, and a novel method for treating periodic boundary conditions.

[ascl:1305.006] Pressure-Entropy SPH: Pressure-entropy smooth-particle hydrodynamics

Pressure-Entropy SPH, a modified version of GADGET-2, uses the Lagrangian “Pressure-Entropy” formulation of the SPH equations. This removes the spurious “surface tension” force substantially improving the treatment of fluid mixing and contact discontinuities. Pressure-Entropy SPH shows good performance in mixing experiments (e.g. Kelvin-Helmholtz & blob tests), with conservation maintained even in strong shock/blastwave tests, where formulations without manifest conservation produce large errors. This improves the treatment of sub-sonic turbulence and lessens the need for large kernel particle numbers.

[ascl:1305.007] PINOCCHIO: PINpointing Orbit-Crossing Collapsed HIerarchical Objects

PINOCCHIO generates catalogues of cosmological dark matter halos with known mass, position, velocity and merger history. It is able to reproduce, with very good accuracy, the hierarchical formation of dark matter halos from a realization of an initial (linear) density perturbation field, given on a 3D grid. Its setup is similar to that of a conventional N-body simulation, but it is based on the powerful Lagrangian Perturbation Theory. It runs in just a small fraction of the computing time taken by an equivalent N-body simulation, producing promptly the merging histories of all halos in the catalog.

[ascl:1305.008] YNOGK: Calculating null geodesics in the Kerr spacetime

YNOGK, written in Fortran, calculates the null geodesics in the Kerr spacetime. It uses Weierstrass' and Jacobi's elliptic functions to express all coordinates and affine parameters as analytical and numerical functions of a parameter $p$, which is an integral value along the geodesic. The information about the turning points do not need to be specified in advance by the user, allowing applications such as imaging, the calculation of line profiles or the observer-emitter problem to become root finding problems. Elliptic integrations are computed by Carlson's elliptic integral method, which allows fast computation.

[ascl:1305.009] GaussFit: Solving least squares and robust estimation problems

GaussFit solves least squares and robust estimation problems; written originally for reduction of NASA Hubble Space Telescope data, it includes a complete programming language designed especially to formulate estimation problems, a built-in compiler and interpreter to support the programming language, and a built-in algebraic manipulator for calculating the required partial derivatives analytically. The code can handle nonlinear models, exact constraints, correlated observations, and models where the equations of condition contain more than one observed quantity. Written in C, GaussFit includes an experimental robust estimation capability so data sets contaminated by outliers can be handled simply and efficiently.

[ascl:1305.010] GILDAS: Grenoble Image and Line Data Analysis Software

GILDAS is a collection of software oriented toward (sub-)millimeter radioastronomical applications (either single-dish or interferometer). It has been adopted as the IRAM standard data reduction package and is jointly maintained by IRAM & CNRS. GILDAS contains many facilities, most of which are oriented towards spectral line mapping and many kinds of 3-dimensional data. The code, written in Fortran-90 with a few parts in C/C++ (mainly keyboard interaction, plotting, widgets), is easily extensible.

[ascl:1305.011] FITDisk: Cataclysmic Variable Accretion Disk Demonstration Tool

FITDisk models accretion disk phenomena using a fully three-dimensional hydrodynamics calculation, and data can either be visualized as they are computed or stored to hard drive for later playback at a fast frame rate. Simulations are visualized using OpenGL graphics and the viewing angle can be changed interactively. Pseudo light curves of simulated systems can be plotted along with the associated Fourier amplitude spectrum. It provides an easy to use graphical user interface as well as 3-D interactive graphics. The code computes the evolution of a CV accretion disk, visualizes results in real time, records and plays back simulations, and generates and plots pseudo light curves and associated power spectra. FITDisk is the Windows executable form of this software; its Fortran source code is also available as DiskSim (ascl:1811.013).

[ascl:1305.012] MapCUMBA: Multi-grid map-making algorithm for CMB experiments

The MapCUMBA package applies a multigrid fast iterative Jacobi algorithm for map-making in the context of CMB experiments.

[ascl:1305.013] Non-Gaussian Realisations

Non-Gaussian Realisations provides code based on a spectral distortion/quantile transformation that generates a realization of a field on a cubic grid that has a specified probability distribution function and a specified power spectrum.

[ascl:1305.014] TAU: 1D radiative transfer code for transmission spectroscopy of extrasolar planet atmospheres

TAU is a 1D line-by-line radiative transfer code for modeling transmission spectra of close-in extrasolar planets. The code calculates the optical path through the planetary atmosphere of the radiation from the host star and quantifies the absorption due to the modeled composition in a transmission spectrum of transit depth as a function of wavelength. The code is written in C++ and is parallelized using OpenMP.

[ascl:1305.015] Merger Trees: Formation history of dark matter haloes

Merger Trees uses a Monte Carlo algorithm to generate merger trees describing the formation history of dark matter haloes; the algorithm is implemented in Fortran. The algorithm is a modification of the algorithm of Cole et al. used in the GALFORM semi-analytic galaxy formation model (ascl:1510.005) based on the Extended Press–Schechter theory. It should be applicable to hierarchical models with a wide range of power spectra and cosmological models. It is tuned to be in accurate agreement with the conditional mass functions found in the analysis of merger trees extracted from the Λ cold dark matter Millennium N-body simulation. The code should be a useful tool for semi-analytic models of galaxy formation and for modelling hierarchical structure formation in general.

[ascl:1304.001] PEC: Period Error Calculator

The PEC (Period Error Calculator) algorithm estimates the period error for eclipsing binaries observed by the Kepler Mission. The algorithm is based on propagation of error theory and assumes that observation of every light curve peak/minimum in a long time-series observation can be unambiguously identified. A simple C implementation of the PEC algorithm is available.

[ascl:1304.002] Astropy: Community Python library for astronomy

Astropy provides a common framework, core package of code, and affiliated packages for astronomy in Python. Development is actively ongoing, with major packages such as PyFITS, PyWCS, vo, and asciitable already merged in. Astropy is intended to contain much of the core functionality and some common tools needed for performing astronomy and astrophysics with Python.

[ascl:1304.003] GALSVM: Automated Morphology Classification

GALSVM is IDL software for automated morphology classification. It was specially designed for high redshift data but can be used at low redshift as well. It analyzes morphologies of galaxies based on a particular family of learning machines called support vector machines. The method can be seen as a generalization of the classical CAS classification but with an unlimited number of dimensions and non-linear boundaries between decision regions. It is fully automated and consequently well adapted to large cosmological surveys.

[ascl:1304.004] Wqed: Lightcurve Analysis Suite

Wqed (pronounced "Wicked") is a set of tools developed by the Delaware Asteroseismic Research Center (DARC) to simplify the process of reducing time-series CCD data on variable stars. It does not provide tools to measure the brightness of stars in individual frames, focusing instead on what comes next:

    - selecting and removing data lost to cloud,
    - removing the effects of light cloud and seeing variations,
    - keeping track of what star a given data set refers to, and when that data was taken, and
    - performing barycentric corrections to data.

[ascl:1304.005] VOBOZ/ZOBOV: Halo-finding and Void-finding algorithms

VOBOZ (VOronoi BOund Zones) is an algorithm to find haloes in an N-body dark matter simulation which has little dependence on free parameters.

ZOBOV (ZOnes Bordering On Voidness) is an algorithm that finds density depressions in a set of points without any free parameters or assumptions about shape. It uses the Voronoi tessellation to estimate densities to find both voids and subvoids. It also measures probabilities that each void or subvoid arises from Poisson fluctuations.

[ascl:1304.006] CosmicEmuLog: Cosmological Power Spectra Emulator

CosmicEmuLog is a simple Python emulator for cosmological power spectra. In addition to the power spectrum of the conventional overdensity field, it emulates the power spectra of the log-density as well as the Gaussianized density. It models fluctuations in the power spectrum at each k as a linear combination of contributions from fluctuations in each cosmological parameter. The data it uses for emulation consist of ASCII files of the mean power spectrum, together with derivatives of the power spectrum with respect to the five cosmological parameters in the space spanned by the Coyote Universe suite. This data can also be used for Fisher matrix analysis. At present, CosmicEmuLog is restricted to redshift 0.

[ascl:1304.007] DESPOTIC: Derive the Energetics and SPectra of Optically Thick Interstellar Clouds

DESPOTIC (Derive the Energetics and SPectra of Optically Thick Interstellar Clouds), written in Python, represents optically thick interstellar clouds using a one-zone model and calculates line luminosities, line cooling rates, and in restricted cases line profiles using an escape probability formalism. DESPOTIC calculates clouds' equilibrium gas and dust temperatures and their time-dependent thermal evolution. The code allows rapid and interactive calculation of clouds' characteristic temperatures, identification of their dominant heating and cooling mechanisms, and prediction of their observable spectra across a wide range of interstellar environments.

[ascl:1304.008] Diffusion.f: Diffusion of elements in stars

Diffusion.f is an exportable subroutine to calculate the diffusion of elements in stars. The routine solves exactly the Burgers equations and can include any number of elements as variables. The code has been used successfully by a number of different groups; applications include diffusion in the sun and diffusion in globular cluster stars. There are many other possible applications to main sequence and to evolved stars. The associated README file explains how to use the subroutine.

[ascl:1304.009] Sérsic: Exact deprojection of Sérsic surface brightness profiles

Sérsic is an implementation of the exact deprojection of Sérsic surface brightness profiles described in Baes and Gentile (2011). This code depends on the mpmath python library for an implementation of the Meijer G function required by the Baes and Gentile (hereafter B+G) formulas for rational values of the Sérsic index. Sérsic requires rational Sérsic indices, but any irrational number can be approximated arbitrarily well by some rational number. The code also depends on scipy, but the dependence is mostly for testing. The implementation of the formulas and the formulas themselves have undergone comprehensive testing.

[ascl:1304.011] TPZ: Trees for Photo-Z

TPZ, a parallel code written in python, produces robust and accurate photometric redshift PDFs by using prediction tree and random forests. The code also produces ancillary information about the sample used, such as prior unbiased errors estimations (giving an estimation of performance) and a ranking of importance of variables as well as a map of performance indicating where extra training data is needed to improve overall performance. It is designed to be easy to use and a tutorial is available.

[ascl:1304.012] ORIGAMI: Structure-finding routine in N-body simulation

ORIGAMI is a dynamical method of determining the morphology of particles in a cosmological simulation by checking for whether, and in how many dimensions, a particle has undergone shell-crossing. The code is written in C and makes use of the Delaunay tessellation calculation routines from the VOBOZ package (which relies on the Qhull package).

[ascl:1304.013] SFH: Star Formation History

SFH is an efficient IDL tool that quickly computes accurate predictions for the baryon budget history in a galactic halo.

[ascl:1304.014] MPgrafic: A parallel MPI version of Grafic-1

MPgrafic is a parallel MPI version of Grafic-1 (ascl:9910.004) which can produce large cosmological initial conditions on a cluster without requiring shared memory. The real Fourier transforms are carried in place using fftw while minimizing the amount of used memory (at the expense of performance) in the spirit of Grafic-1. The writing of the output file is also carried in parallel. In addition to the technical parallelization, it provides three extensions over Grafic-1:

  • it can produce power spectra with baryon wiggles (DJ Eisenstein and W. Hu, Ap. J. 496);
  • it has the optional ability to load a lower resolution noise map corresponding to the low frequency component which will fix the larger scale modes of the simulation (extra flag 0/1 at the end of the input process) in the spirit of Grafic-2 (ascl:1106.008);
  • it can be used in conjunction with constrfield, which generates initial conditions phases from a list of local constraints on density, tidal field density gradient and velocity.

[ascl:1304.015] TVD: Total Variation Diminishing code

TVD solves the magnetohydrodynamic (MHD) equations by updating the fluid variables along each direction using the flux-conservative, second-order, total variation diminishing (TVD), upwind scheme of Jin & Xin. The magnetic field is updated separately in two-dimensional advection-constraint steps. The electromotive force (EMF) is computed in the advection step using the TVD scheme, and this same EMF is used immediately in the constraint step in order to preserve ∇˙B=0 without the need to store intermediate fluxes. The code is extended to three dimensions using operator splitting, and Runge-Kutta is used to get second-order accuracy in time. TVD offers high-resolution per grid cell, second-order accuracy in space and time, and enforcement of the ∇˙B=0 constraint to machine precision. Written in Fortran, It has no memory overhead and is fast. It is also available in a fully scalable message-passing parallel MPI implementation.

[ascl:1304.016] Qhull: Quickhull algorithm for computing the convex hull

Qhull computes the convex hull, Delaunay triangulation, Voronoi diagram, halfspace intersection about a point, furthest-site Delaunay triangulation, and furthest-site Voronoi diagram. The source code runs in 2-d, 3-d, 4-d, and higher dimensions. Qhull implements the Quickhull algorithm for computing the convex hull. It handles roundoff errors from floating point arithmetic. It computes volumes, surface areas, and approximations to the convex hull.

[ascl:1304.017] CosmoRec: Cosmological Recombination code

CosmoRec solves the recombination problem including recombinations to highly excited states, corrections to the 2s-1s two-photon channel, HI Lyn-feedback, n>2 two-photon profile corrections, and n≥2 Raman-processes. The code can solve the radiative transfer equation of the Lyman-series photon field to obtain the required modifications to the rate equations of the resolved levels, and handles electron scattering, the effect of HeI intercombination transitions, and absorption of helium photons by hydrogen. It also allows accounting for dark matter annihilation and optionally includes detailed helium radiative transfer effects.

[ascl:1304.018] SZpack: Computation of Sunyaev-Zeldovich (SZ) signals

SZpack is a numerical library which allows fast and precise computation of the Sunyaev-Zeldovich (SZ) signal for hot, moving clusters of galaxies. Both explicit numerical integration as well as approximate representation of the SZ signals can be obtained. Variations of the electron temperature and bulk velocity along the line-of-sight can be included. SZpack allows very fast and precise (<~0.001% at frequencies h nu <~ 30kT_g and electron temperature kTe ~ 75 keV) computation and its accuracy practically eliminates uncertainties related to more expensive numerical evaluation of the Boltzmann collision term. It furthermore cleanly separates kinematic corrections from scattering physics, effects that previously have not been clarified.

[ascl:1304.019] IFrIT: Ionization FRont Interactive Tool

IFrIT (Ionization FRont Interactive Tool) is a powerful general purpose visualization tool that can be used to visualize 3-dimensional data sets. IFrIT is written in C++ and is based on the Visualization ToolKit (VTK) and, optionally, uses a GUI toolkit Qt. IFrIT can visualize scalar, vector field, tensor, and particle data. Several visualization windows can exist at the same time, each one having a full set of visualization objects. Some visualization windows can share the data between them, while other windows can be fully independent. Images from several visualization windows can be combined into one image file on the disk, tiling some windows together, and inserting reduced versions of some windows into larger other windows. A large array of features is also available, including highly advanced animation capabilities, a complex set of lights, markers to label various points in space, and a capability to "pick" a point in the scene and retrieve information about the data at this location.

[ascl:1304.020] pyCloudy: Tools to manage astronomical Cloudy photoionization code

PyCloudy is a Python library that handles input and output files of the Cloudy photoionization code (Gary Ferland). It can also generate 3D nebula from various runs of the 1D Cloudy code. pyCloudy allows you to:
- define and write input file(s) for Cloudy code. As you can have it in a code, you may generate automatically sets of input files, changing parameters from one to the other.<
- read the Cloudy output files and play with the data: you will be able to plot line emissivity ratio vs. the radius of the nebula, the electron temperature, or any Cloudy output.
- build pseudo-3D models, a la Cloudy_3D, by running a set of models, changing parameters (e.g. inner radius, density) following angular laws, reading the outputs of the set of models and interpolating the results (Te, ne, line emissivities) in a 3D cube.

[ascl:1304.021] PyNeb: Analysis of emission lines

PyNeb (previously PyNebular) is an update and expansion of the IRAF package NEBULAR; rewritten in Python, it is designed to be more user-friendly and powerful, increasing the speed, easiness of use, and graphic visualization of emission lines analysis. In PyNeb, the atom is represented as an n-level atom. For given density and temperature, PyNeb solves the equilibrium equations and determines the level populations. PyNeb can compute physical conditions from suitable diagnostic line ratios and level populations, critical densities and line emissivities, and can compute and display emissivity grids as a function of Te and Ne. It can also deredden line intensities, read and manage observational data, and plot and compare atomic data from different publications, and compute ionic abundances from line intensities and physical conditions and elemental abundances from ionic abundances and icfs.

[ascl:1304.022] Copter: Cosmological perturbation theory

Copter is a software package for doing calculations in cosmological perturbation theory. Specifically, Copter includes code for computing statistical observables in the large-scale structure of matter using various forms of perturbation theory, including linear theory, standard perturbation theory, renormalized perturbation theory, and many others. Copter is written in C++ and makes use of the Boost C++ library headers.

[ascl:1303.001] SWIFT: A solar system integration software package

SWIFT follows the long-term dynamical evolution of a swarm of test particles in the solar system. The code efficiently and accurately handles close approaches between test particles and planets while retaining the powerful features of recently developed mixed variable symplectic integrators. Four integration techniques are included: Wisdom-Holman Mapping; Regularized Mixed Variable Symplectic (RMVS) method; fourth order T+U Symplectic (TU4) method; and Bulirsch-Stoer method. The package is designed so that the calls to each of these look identical so that it is trivial to replace one with another. Complex data manipulations and results can be analyzed with the graphics packace SwiftVis.

[ascl:1303.002] emcee: The MCMC Hammer

emcee is an extensible, pure-Python implementation of Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler. It's designed for Bayesian parameter estimation. The algorithm behind emcee has several advantages over traditional MCMC sampling methods and has excellent performance as measured by the autocorrelation time (or function calls per independent sample). One advantage of the algorithm is that it requires hand-tuning of only 1 or 2 parameters compared to $sim N^2$ for a traditional algorithm in an N-dimensional parameter space. Exploiting the parallelism of the ensemble method, emcee permits any user to take advantage of multiple CPU cores without extra effort.

[ascl:1303.003] CosmoHammer: Cosmological parameter estimation with the MCMC Hammer

CosmoHammer is a Python framework for the estimation of cosmological parameters. The software embeds the Python package emcee by Foreman-Mackey et al. (2012) and gives the user the possibility to plug in modules for the computation of any desired likelihood. The major goal of the software is to reduce the complexity when one wants to extend or replace the existing computation by modules which fit the user's needs as well as to provide the possibility to easily use large scale computing environments. CosmoHammer can efficiently distribute the MCMC sampling over thousands of cores on modern cloud computing infrastructure.

[ascl:1303.004] UCL_PDR: Time dependent photon-dissociation regions model

UCL_PDR is a time dependent photon-dissociation regions model that calculates self consistently the thermal balance. It can be used with gas phase only species as well as with surface species. It is very modular, has the possibility of accounting for density and pressure gradients and can be coupled with UCL_CHEM as well as with SMMOL. It has been used to model small scale (e.g. knots in proto-planetary nebulae) to large scale regions (high redshift galaxies).

[ascl:1303.005] SMMOL: Spherical Multi-level MOLecular line radiative transfer

SMMOL (Spherical Multi-level MOLecular line radiative transfer) is a molecular line radiative transfer code that uses Accelerated Lambda Iteration to solve the coupled level population and line transfer problem in spherical geometry. The code uses a discretized grid and a ray tracing methodology. SMMOL is designed for high optical depth regimes and can cope with maser emission as long as the spatial-velocity sampling is fine enough.

[ascl:1303.006] UCLCHEM: Time and depth dependent gas-grain chemical model

UCLCHEM is a time and depth dependent gas-grain chemical model that can be used to estimate the fractional abundances (with respect to hydrogen) of gas and surface species in every environment where molecules are present. The model includes both gas and surface reactions. The code starts from the most diffuse state where all the gas is in atomic form and evolve sthe gas to its final density. Depending on the temperature, atoms and molecules from the gas freeze on to the grains and they hydrogenate where possible. The advantage of this approach is that the ice composition is not assumed but it is derived by a time-dependent computation of the chemical evolution of the gas-dust interaction process. The code is very modular, has been used to model a variety of regions and can be coupled with the UCL_PDR and SMMOL codes.

[ascl:1303.007] micrOMEGAs: Calculation of dark matter properties

micrOMEGAs calculates the properties of cold dark matter in a generic model of particle physics. First developed to compute the relic density of dark matter, the code also computes the rates for dark matter direct and indirect detection. The code provides the mass spectrum, cross-sections, relic density and exotic fluxes of gamma rays, positrons and antiprotons. The propagation of charged particles in the Galactic halo is handled with a module that allows to easily modify the propagation parameters. The cross-sections for both spin dependent and spin independent interactions of WIMPS on protons are computed automatically as well as the rates for WIMP scattering on nuclei in a large detector. Annihilation cross-sections of the dark matter candidate at zero velocity, relevant for indirect detection of dark matter, are computed automatically, and the propagation of charged particles in the Galactic halo is also handled.

[ascl:1303.008] TYCHO: Stellar evolution code

TYCHO is a general, one dimensional (spherically symmetric) stellar evolution code written in structured Fortran 77; it is designed for hydrostatic and hydrodynamic stages including mass loss, accretion, pulsations and explosions. Mixing and convection algorithms are based on 3D time-dependent simulations. It offers extensive on-line graphics using Tim Pearson's PGPLOT (ascl:1103.002) with X-windows and runs effectively on Linux and Mac OS X laptop and desktop computers.
NOTE: This code is no longer being supported.

[ascl:1303.009] MAGIX: Modeling and Analysis Generic Interface for eXternal numerical codes

MAGIX provides an interface between existing codes and an iterating engine that minimizes deviations of the model results from available observational data; it constrains the values of the model parameters and provides corresponding error estimates. Many models (and, in principle, not only astrophysical models) can be plugged into MAGIX to explore their parameter space and find the set of parameter values that best fits observational/experimental data. MAGIX complies with the data structures and reduction tools of Atacama Large Millimeter Array (ALMA), but can be used with other astronomical and with non-astronomical data.

[ascl:1303.010] TAC-maker: Transit Analytical Curve maker

TAC-maker allows for rapid and interactive calculation of synthetic planet transits by numerical computations of the integrals, allowing the use of an arbitrary limb-darkening law of the host star. This advantage together with the practically arbitrary precision of the calculations makes the code a valuable tool for the continuously increasing photometric precision of ground-based and space observations.

[ascl:1303.011] MOPSIC: Extended Version of MOPSI

MOPSIC was created to analyze bolometer data but can be used for much more versatile tasks. It is an extension of MOPSI; this software had been merged with the command interpreter of GILDAS (ascl:1305.010). For data reduction, MOPSIC uses a special method to calculate the chopped signal. This gives much better results than the straight difference of the signals obtained at both chopper positions. In addition there are also scripts to reduce pointings, skydips, and to calculate the RCPs (Receiver Channel Parameters) from calibration maps. MOPSIC offers a much broader range of applications including advanced planning functions for mapping and onoff observations, post-reduction data analysis and processing and even reduction of non-bolometer data (optical, IR, spectroscopy).

[ascl:1303.012] TGCat: Chandra Transmission Grating Catalog and Archive

TGCat is an archive of Chandra transmission grating spectra and a suite of software for processing such data. Users can browse and categorize Chandra gratings observations quickly and easily, generate custom plots of resulting response corrected spectra on-line without the need for special software and download analysis ready products from multiple observations in one convenient operation. Data processing for the catalog is done with a suite of ISIS/S-Lang scripts; the software is available for download. These ISIS scripts wrap and call CIAO tools for reprocessing from "Level 1" (acis_process_events or hrc_process_events) through "Level 2" (binned spectra, via tg_resolve_events and tgextract), compute responses (grating "RMFs" and "ARFs", via mkgrmf and mkgarf), and make summary plots.

[ascl:1303.013] idistort: CMB spectral distortions templates and code

Spectrum created by energy release in the early Universe, before recombination, creates distortions which are a superposition of μ-type, y-type and intermediate-type distortions. The final spectrum can thus be constructed from the templates, once energy injection rate as a function of redshift is known. This package contains the templates spaced at dy=0.001 for y<1 and dy=0.01 for y>1 covering a range 0.001 < y < 10. Also included is a Mathematica code which can combine these templates for user-defined rate of energy injection as a function of redshift. Silk damping, particle decay and annihilation examples are also included.

[ascl:1303.014] BSE: Binary Star Evolution

BSE is a rapid binary star evolution code. It can model circularization of eccentric orbits and synchronization of stellar rotation with the orbital motion owing to tidal interaction in detail. Angular momentum loss mechanisms, such as gravitational radiation and magnetic braking, are also modelled. Wind accretion, where the secondary may accrete some of the material lost from the primary in a wind, is allowed with the necessary adjustments made to the orbital parameters in the event of any mass variations. Mass transfer occurs if either star fills its Roche lobe and may proceed on a nuclear, thermal or dynamical time-scale. In the latter regime, the radius of the primary increases in response to mass-loss at a faster rate than the Roche-lobe of the star. Prescriptions to determine the type and rate of mass transfer, the response of the secondary to accretion and the outcome of any merger events are in place in BSE.

[ascl:1303.015] SSE: Single Star Evolution

SSE is a rapid single-star evolution (SSE) code; these analytical formulae cover all phases of evolution from the zero-age main-sequence up to and including remnant phases. It is valid for masses in the range 0.1-100 Msun and metallicity can be varied. The SSE package contains a prescription for mass loss by stellar winds. It also follows the evolution of rotational angular momentum for the star.

[ascl:1303.016] 2MASS Kit: 2MASS Catalog Server Kit

2MASS Kit is an open source software for use in easily constructing a high performance search server for important astronomical catalogs. It is tuned for optimal coordinate search performance (Radial Search, Box Search, Rectangular Search) of huge catalogs, thus increasing the speed by more than an order of magnitude when compared to simple indexing on a single table. Optimal conditions enable more than 3,000 searches per second for radial search of 2MASS PSC. The kit is best characterized by its flexible tuning. Each table index is registered in one of six table spaces (each resides in a separate directory), thus allowing only the essential parts to be easily moved onto fast devices. Given the terrific evolution that has taken place with recent SSDs in performance, a very cost-effective way of constructing high-performance servers is moving part of or all table indices to a fast SSD.

[ascl:1303.017] CADRE: CArma Data REduction pipeline

CADRE, the Combined Array for Millimeter-wave Astronomy (CARMA) data reduction pipeline, gives investigators a first look at a fully reduced set of their data. It runs automatically on all data produced by the telescope as they arrive in the data archive. The pipeline is written in python and uses python wrappers for MIRIAD subroutines for direct access to the data. It applies passband, gain and flux calibration to the data sets and produces a set of continuum and spectral line maps in both MIRIAD and FITS format.

[ascl:1303.018] Galactus: Modeling and fitting of galaxies from neutral hydrogen (HI) cubes

Galactus, written in python, is an astronomical software tool for the modeling and fitting of galaxies from neutral hydrogen (HI) cubes. Galactus uses a uniform medium to generate a cube. Galactus can perform the full-radiative transfer for the HI, so can model self-absorption in the galaxy.

[ascl:1303.019] GBTIDL: Reduction and Analysis of GBT Spectral Line Data

GBTIDL is an interactive package for reduction and analysis of spectral line data taken with the Robert C. Byrd Green Bank Telescope (GBT). The package, written entirely in IDL, consists of straightforward yet flexible calibration, averaging, and analysis procedures (the "GUIDE layer") modeled after the UniPOPS and CLASS data reduction philosophies, a customized plotter with many built-in visualization features, and Data I/O and toolbox functionality that can be used for more advanced tasks. GBTIDL makes use of data structures which can also be used to store intermediate results. The package consumes and produces data in GBT SDFITS format. GBTIDL can be run online and have access to the most recent data coming off the telescope, or can be run offline on preprocessed SDFITS files.

[ascl:1303.020] Ginga: Flexible FITS viewer

Ginga is a viewer for astronomical data FITS (Flexible Image Transport System) files; the viewer centers around a FITS display widget which supports zooming and panning, color and intensity mapping, a choice of several automatic cut levels algorithms and canvases for plotting scalable geometric forms. In addition to this widget, the FITS viewer provides a flexible plugin framework for extending the viewer with many different features. A fairly complete set of "standard" plugins are provided for expected features of a modern viewer: panning and zooming windows, star catalog access, cuts, star pick/fwhm, thumbnails, and others. This viewer was written by software engineers at Subaru Telescope, National Astronomical Observatory of Japan, and is in use at that facility.

[ascl:1303.021] Xmatch: GPU Enhanced Astronomic Catalog Cross-Matching

Xmatch is a cross-platform, multi-GPU tool which allows for extremely fast cross-matching between two Astronomic catalogs. It is capable of asyncronously managing multiple GPUs, ideal for workstation and cluster environments.

[ascl:1303.022] ionFR: Ionospheric Faraday rotation

ionFR calculates the amount of ionospheric Faraday rotation for a specific epoch, geographic location, and line-of-sight. The code uses a number of publicly available, GPS-derived total electron content maps and the most recent release of the International Geomagnetic Reference Field. ionFR can be used for the calibration of radio polarimetric observations; its accuracy had been demonstrated using LOFAR pulsar observations.

[ascl:1303.023] pysynphot: Synthetic photometry software package

pysynphot is a synthetic photometry software package suitable for either library or interactive use. Intended as a modern-language successor to the IRAF/STSDAS synphot package, it provides improved algorithms that address known shortcomings in synphot, and its object-oriented design is more easily extensible than synphot's task-oriented approach. It runs under PyRAF (ascl:1207.011), and a backwards compatibility mode is provided that recognizes all spectral and throughput tables, obsmodes, and spectral expressions used by synphot, to facilitate the transition for legacy code.

[ascl:1303.024] ATLAS12: Opacity sampling model atmosphere program

ATLAS12 is an opacity sampling model atmosphere program to allow computation of models with individual abundances using line data. ATLAS12 is able to compute the same models as ATLAS9 which uses pretabulated opacities, plus models with arbitrary abundances. ATLAS12 sampled fluxes are quite accurate for predicting the total flux except in the intermediate or narrow bandpass intervals because the sample size is too small.

[ascl:1303.025] DPUSER: Interactive language for image analysis

DPUSER is an interactive language capable of handling numbers (both real and complex), strings, and matrices. Its main aim is to do astronomical image analysis, for which it provides a comprehensive set of functions, but it can also be used for many other applications.

[ascl:1303.026] ACORNS-ADI: Algorithms for Calibration, Optimized Registration and Nulling the Star in Angular Differential Imaging

ACORNS-ADI, written in python, is a parallelized software package which reduces high-contrast imaging data. Originally written for imaging data from Subaru/HiCIAO, it requires minimal modification to reduce data from other instruments. It is efficient, open-source, and includes several optional features which may improve performance.

[ascl:1303.027] GaPP: Gaussian Processes in Python

The algorithm Gaussian processes can reconstruct a function from a sample of data without assuming a parameterization of the function. The GaPP code can be used on any dataset to reconstruct a function. It handles individual error bars on the data and can be used to determine the derivatives of the reconstructed function. The data sample can consist of observations of the function and of its first derivative.

[ascl:1303.028] Stellarics: Inverse Compton scattering from stellar heliospheres

Cosmic ray electrons scatter on the photon fields around stars, including the sun, to create gamma rays by the inverse Compton effect. Stellarics computes the spectrum and angular distribution of this emission. The software also includes general-purpose routines for inverse Compton scattering on a given electron spectrum, for example for interstellar or astrophysical source modelling.

[ascl:1303.029] iSAP: Interactive Sparse Astronomical Data Analysis Packages

iSAP consists of three programs, written in IDL, which together are useful for spherical data analysis. MR/S (MultiResolution on the Sphere) contains routines for wavelet, ridgelet and curvelet transform on the sphere, and applications such denoising on the sphere using wavelets and/or curvelets, Gaussianity tests and Independent Component Analysis on the Sphere. MR/S has been designed for the PLANCK project, but can be used for many other applications. SparsePol (Polarized Spherical Wavelets and Curvelets) has routines for polarized wavelet, polarized ridgelet and polarized curvelet transform on the sphere, and applications such denoising on the sphere using wavelets and/or curvelets, Gaussianity tests and blind source separation on the Sphere. SparsePol has been designed for the PLANCK project. MS-VSTS (Multi-Scale Variance Stabilizing Transform on the Sphere), designed initially for the FERMI project, is useful for spherical mono-channel and multi-channel data analysis when the data are contaminated by a Poisson noise. It contains routines for wavelet/curvelet denoising, wavelet deconvolution, multichannel wavelet denoising and deconvolution.

[ascl:1303.030] Sunrise: Radiation transfer through interstellar dust

Sunrise is a Monte Carlo radiation transfer code for calculating absorption and scattering of light to study the effects of dust in hydrodynamic simulations of interacting galaxies. It uses an adaptive mesh refinement grid to describe arbitrary geometries of emitting and absorbing/scattering media, with spatial dynamical range exceeding 104; it can efficiently generate images of the emerging radiation at arbitrary points in space and spectral energy distributions of simulated galaxies run with the Gadget (ascl:0003.001), Gasoline (ascl:1710.019), Arepo (ascl:1909.010), Enzo (ascl:1010.072) or ART codes. In addition to the monochromatic radiative transfer typically used by Monte Carlo codes, Sunrise can propagate a range of wavelengths simultaneously. This "polychromatic" algorithm gives significant improvements in efficiency and accuracy when spectral features are calculated.

[ascl:1302.001] MARX: Model of AXAF Response to X-rays

MARX (Model of AXAF Response to X-rays) is a suite of programs designed to enable the user to simulate the on-orbit performance of the Chandra satellite. MARX provides a detailed ray-trace simulation of how Chandra responds to a variety of astrophysical sources and can generate standard FITS events files and images as output. It contains models for the HRMA mirror system onboard Chandra as well as the HETG and LETG gratings and all focal plane detectors.

[ascl:1302.002] ISIS: Interactive Spectral Interpretation System for High Resolution X-Ray Spectroscopy

ISIS, the Interactive Spectral Interpretation System, is designed to facilitate the interpretation and analysis of high resolution X-ray spectra. It is being developed as a programmable, interactive tool for studying the physics of X-ray spectrum formation, supporting measurement and identification of spectral features, and interaction with a database of atomic structure parameters and plasma emission models.

[ascl:1302.003] ACS: ALMA Common Software

ALMA Common Software (ACS) provides a software infrastructure common to all ALMA partners and consists of a documented collection of common patterns and components which implement those patterns. The heart of ACS is based on a distributed Component-Container model, with ACS Components implemented as CORBA objects in any of the supported programming languages. ACS provides common CORBA-based services such as logging, error and alarm management, configuration database and lifecycle management. Although designed for ALMA, ACS can and is being used in other control systems and distributed software projects, since it implements proven design patterns using state of the art, reliable technology. It also allows, through the use of well-known standard constructs and components, that other team members whom are not authors of ACS easily understand the architecture of software modules, making maintenance affordable even on a very large project.

[ascl:1302.004] pNbody: A python parallelized N-body reduction toolbox

pNbody is a parallelized python module toolbox designed to manipulate and interactively display very large N-body systems. It allows the user to perform complicated manipulations with only very few commands and to load an N-body system and explore it interactively using the python interpreter. pNbody may also be used in python scripts. pNbody contains graphical facilities for creating maps of physical values of the system, such as density, temperature, and velocities maps. Stereo capabilities are also implemented. pNbody is not limited by file format; the user may use a parameter file to redefine how to read a preferred format.

[ascl:1302.005] EPICS: Experimental Physics and Industrial Control System

EPICS is a set of software tools and applications developed collaboratively and used to create distributed soft real-time control systems for scientific instruments such as particle accelerators and telescopes. Such distributed control systems typically comprise tens or even hundreds of computers, networked together to allow communication between them and to provide control and feedback of the various parts of the device from a central control room, or even remotely over the internet. EPICS uses Client/Server and Publish/Subscribe techniques to communicate between the various computers. A Channel Access Gateway allows engineers and physicists elsewhere in the building to examine the current state of the IOCs, but prevents them from making unauthorized adjustments to the running system. In many cases the engineers can make a secure internet connection from home to diagnose and fix faults without having to travel to the site.

EPICS is used by many facilities worldwide, including the Advanced Photon Source at Argonne National Laboratory, Fermilab, Keck Observatory, Laboratori Nazionali di Legnaro, Brazilian Synchrotron Light Source, Los Alamos National Laboratory, Australian Synchrotron, and Stanford Linear Accellerator Center.

[ascl:1302.006] Minerva: Cylindrical coordinate extension for Athena

Minerva is a cylindrical coordinate extension of the Athena astrophysical MHD code of Stone, Gardiner, Teuben, and Hawley. The extension follows the approach of Athena's original developers and has been designed to alter the existing Cartesian-coordinates code as minimally and transparently as possible. The numerical equations in cylindrical coordinates are formulated to maintain consistency with constrained transport (CT), a central feature of the Athena algorithm, while making use of previously implemented code modules such as the Riemann solvers. Angular momentum transport, which is critical in astrophysical disk systems dominated by rotation, is treated carefully.

[ascl:1302.007] GRID-core: Gravitational Potential Identification of Cores

GRID-core is a core-finding method using the contours of the local gravitational potential to identify core boundaries. The GRID-core method applied to 2D surface density and 3D volume density are in good agreement for bound cores. We have implemented a version of the GRID-core algorithm in IDL, suitable for core-finding in observed maps. The required input is a two-dimensional FITS file containing a map of the column density in a region of a cloud.

[ascl:1302.008] FASTPHOT: A simple and quick IDL PSF-fitting routine

PSF fitting photometry allows a simultaneously fit of a PSF profile on the sources. Many routines use PSF fitting photometry, including IRAF/allstar, Strarfinder, and Convphot. These routines are in general complex to use and slow. FASTPHOT is optimized for prior extraction (the position of the sources is known) and is very fast and simple.

[ascl:1302.009] IAS Stacking Library in IDL

This IDL library is designed to be used on astronomical images. Its main aim is to stack data to allow a statistical detection of faint signal, using a prior. For instance, you can stack 160um data using the positions of galaxies detected at 24um or 3.6um, or use WMAP sources to stack Planck data. It can estimate error bars using bootstrap, and it can perform photometry (aperture photometry, or PSF fitting, or other that you can plug). The IAS Stacking Library works with gnomonic projections (RA---TAN), and also with HEALPIX projection.

[ascl:1302.010] ICORE: Image Co-addition with Optional Resolution Enhancement

ICORE is a command-line driven co-addition, mosaicking, and resolution enhancement (HiRes) tool for creating science quality products from image data in FITS format and with World Coordinate System information following the FITS-WCS standard. It includes preparatory steps such as image background matching, photometric gain-matching, and pixel-outlier rejection. Co-addition and/or HiRes'ing can be performed in either the inertial WCS or in the rest frame of a moving object. Three interpolation methods are supported: overlap-area weighting, drizzle, and weighting by the detector Point Response Function (PRF). The latter enables the creation of matched-filtered products for optimal point-source detection, but most importantly allows for resolution enhancement using a spatially-dependent deconvolution method. This is a variant of the classic Richardson-Lucy algorithm with the added benefit to simultaneously register and co-add multiple images to optimize signal-to-noise and sampling of the instrumental PSF. It can assume real (or otherwise "flat") image priors, mitigate "ringing" artifacts, and assess the quality of image solutions using statistically-motivated convergence criteria. Uncertainties are also estimated and internally validated for all products. The software supports multithreading that can be configured for different architectures. Numerous example scripts are included (with test data) to co-add and/or HiRes image data from Spitzer-IRAC/MIPS, WISE, and Herschel-SPIRE.

[ascl:1302.011] GALA: Stellar atmospheric parameters and chemical abundances

GALA is a freely distributed Fortran code to derive the atmospheric parameters (temperature, gravity, microturbulent velocity and overall metallicity) and abundances for individual species of stellar spectra using the classical method based on the equivalent widths of metallic lines. The abundances of individual spectral lines are derived by using the WIDTH9 code developed by R. L. Kurucz. GALA is designed to obtain the best model atmosphere, by optimizing temperature, surface gravity, microturbulent velocity and metallicity, after rejecting the discrepant lines. Finally, it computes accurate internal errors for each atmospheric parameter and abundance. The code obtains chemical abundances and atmospheric parameters for large stellar samples quickly, thus making GALA an useful tool in the epoch of the multi-object spectrographs and large surveys.

[ascl:1302.012] ME(SSY)**2: Monte Carlo Code for Star Cluster Simulations

ME(SSY)**2 stands for “Monte-carlo Experiments with Spherically SYmmetric Stellar SYstems." This code simulates the long term evolution of spherical clusters of stars; it was devised specifically to treat dense galactic nuclei. It is based on the pioneering Monte Carlo scheme proposed by Hénon in the 70's and includes all relevant physical ingredients (2-body relaxation, stellar mass spectrum, collisions, tidal disruption, ldots). It is basically a Monte Carlo resolution of the Fokker-Planck equation. It can cope with any stellar mass spectrum or velocity distribution. Being a particle-based method, it also allows one to take stellar collisions into account in a very realistic way. This unique code, featuring most important physical processes, allows million particle simulations, spanning a Hubble time, in a few CPU days on standard personal computers and provides a wealth of data only rivalized by N-body simulations. The current version of the software requires the use of routines from the "Numerical Recipes in Fortran 77" (http://www.nrbook.com/a/bookfpdf.php).

[ascl:1302.013] NIFTY: A versatile Python library for signal inference

NIFTY (Numerical Information Field TheorY) is a versatile library enables the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is written in Python, although it accesses libraries written in Cython, C++, and C for efficiency. NIFTY offers a toolkit that abstracts discretized representations of continuous spaces, fields in these spaces, and operators acting on fields into classes. Thereby, the correct normalization of operations on fields is taken care of automatically. This allows for an abstract formulation and programming of inference algorithms, including those derived within information field theory. Thus, NIFTY permits rapid prototyping of algorithms in 1D and then the application of the developed code in higher-dimensional settings of real world problems. NIFTY operates on point sets, n-dimensional regular grids, spherical spaces, their harmonic counterparts, and product spaces constructed as combinations of those.

[ascl:1302.014] SYNMAG Photometry: Catalog-level Matched Colors of Extended Sources

SYNMAG is a tool for producing synthetic aperture magnitudes to enable fast matched photometry at the catalog level without reprocessing imaging data. Aperture magnitudes are the most widely tabulated flux measurements in survey catalogs; obtaining reliable, matched photometry for galaxies imaged by different observatories represents a key challenge in the era of wide-field surveys spanning more than several hundred square degrees. Methods such as flux fitting, profile fitting, and PSF homogenization followed by matched-aperture photometry are all computationally expensive. An alternative solution called "synthetic aperture photometry" exploits galaxy profile fits in one band to efficiently model the observed, point-spread-function-convolved light profile in other bands and predict the flux in arbitrarily sized apertures.

[ascl:1302.015] DisPerSE: Discrete Persistent Structures Extractor

DisPerSE is open source software for the identification of persistent topological features such as peaks, voids, walls and in particular filamentary structures within noisy sampled distributions in 2D, 3D. Using DisPerSE, structure identification can be achieved through the computation of the discrete Morse-Smale complex. The software can deal directly with noisy datasets via the concept of persistence (a measure of the robustness of topological features). Although developed for the study of the properties of filamentary structures in the cosmic web of galaxy distribution over large scales in the Universe, the present version is quite versatile and should be useful for any application where a robust structure identification is required, such as for segmentation or for studying the topology of sampled functions (for example, computing persistent Betti numbers). Currently, it can be applied can work indifferently on many kinds of cell complex (such as structured and unstructured grids, 2D manifolds embedded within a 3D space, discrete point samples using delaunay tesselation, and Healpix tesselations of the sphere). The only constraint is that the distribution must be defined over a manifold, possibly with boundaries.

[ascl:1302.016] XDQSO: Photometic quasar probabilities and redshifts

XDQSO, written in IDL, calculates photometric quasar probabilities to mimick SDSS-III’s BOSS quasar target selection or photometric redshifts for quasars, whether in three redshift ranges (z < 2.2; 2.2 leq z leq 3.5; z > 3.5) or arbitrary redshift ranges.

[ascl:1302.017] ESO-MIDAS: General tools for image processing and data reduction

The ESO-MIDAS system provides general tools for image processing and data reduction with emphasis on astronomical applications including imaging and special reduction packages for ESO instrumentation at La Silla and the VLT at Paranal. In addition it contains applications packages for stellar and surface photometry, image sharpening and decomposition, statistics, data fitting, data presentation in graphical form, and more.

[ascl:1301.001] PSFEx: Point Spread Function Extractor

PSFEx (“PSF Extractor”) extracts models of the Point Spread Function (PSF) from FITS images processed with SExtractor and measures the quality of images. The generated PSF models can be used for model-fitting photometry or morphological analyses.

[ascl:1212.001] Bonsai: N-body GPU tree-code

Bonsai is a gravitational N-body tree-code that runs completely on the GPU. This reduces the amount of time spent on communication with the CPU. The code runs on NVIDIA GPUs and on a GTX480 it is able to integrate ~2.8M particles per second. The tree construction and traverse algorithms are portable to many-core devices which have support for CUDA or OpenCL programming languages.

[ascl:1212.002] XPHOT: Estimation of properties of weak X-ray sources

XPHOT is an IDL implementation of a non-parametric method for estimating the apparent and intrinsic broad-band fluxes and absorbing X-ray column densities of weak X-ray sources. XPHOT is intended for faint sources with greater than ∼5-7 counts but fewer than 100-300 counts where parametric spectral fitting methods will be superior. This method is similar to the long-standing use of color-magnitude diagrams in optical and infrared astronomy, with X-ray median energy replacing color index and X-ray source counts replacing magnitude. Though XPHOT was calibrated for thermal spectra characteristic of stars in young stellar clusters, recalibration should be possible for some other classes of faint X-ray sources such as extragalactic active galactic nuclei.

[ascl:1212.003] MPWide: Light-weight communication library for distributed computing

MPWide is a light-weight communication library for distributed computing. It is specifically developed to allow message passing over long-distance networks using path-specific optimizations. An early version of MPWide was used in the Gravitational Billion Body Project to allow simulations across multiple supercomputers.

[ascl:1212.004] MOLIERE-5: Forward and inversion model for sub-mm wavelengths

MOLIERE-5 (Microwave Observation LIne Estimation and REtrieval) is a versatile forward and inversion model for the millimeter and submillimeter wavelengths range and includes an inversion model. The MOLIERE-5 forward model includes modules for the calculation of absorption coefficients, radiative transfer, and instrumental characteristics. The radiative transfer model is supplemented by a sensitivity module for estimating the contribution to the spectrum of each catalog line at its center frequency enabling the model to effectively filter for small spectral lines. The instrument model consists of several independent modules, including the calculation of the convolution of spectra and weighting functions with the spectrometer response functions. The instrument module also provides several options for modeling of frequency-switched observations. The MOLIERE-5 inversion model calculates linear Optimal Estimation, a least-squares retrieval method which uses statistical apriori knowledge on the retrieved parameters for the regularization of ill-posed inversion problems and computes diagnostics such as the measurement and smoothing error covariance matrices along with contribution and averaging kernel functions.

[ascl:1212.005] General complex polynomial root solver

This general complex polynomial root solver, implemented in Fortran and further optimized for binary microlenses, uses a new algorithm to solve polynomial equations and is 1.6-3 times faster than the ZROOTS subroutine that is commercially available from Numerical Recipes, depending on application. The largest improvement, when compared to naive solvers, comes from a fail-safe procedure that permits skipping the majority of the calculations in the great majority of cases, without risking catastrophic failure in the few cases that these are actually required.

[ascl:1212.006] CosmoPMC: Cosmology sampling with Population Monte Carlo

CosmoPMC is a Monte-Carlo sampling method to explore the likelihood of various cosmological probes. The sampling engine is implemented with the package pmclib. It is called Population MonteCarlo (PMC), which is a novel technique to sample from the posterior. PMC is an adaptive importance sampling method which iteratively improves the proposal to approximate the posterior. This code has been introduced, tested and applied to various cosmology data sets.

[ascl:1212.007] WOLF: FITS file processor

WOLF processes FITS files and generates photometry files, annotated JPGs, opacity maps, background, transient detection and luminance changes detection. This software was used to process data for the Night Sky Live project.

[ascl:1212.008] SIR: Stokes Inversion based on Response functions

SIR is a general-purpose code capable of dealing with gradients of the physical quantities with height. It admits one and two-component model atmospheres. It allows the recovery of the stratification of the temperature, the magnetic field vector, and the line of sight velocity through the atmosphere, and the micro- and macroturbulence velocities - which are assumed to be constant with depth. It is based on the response functions, which enter a Marquardt nonlinear least-squares algorithm in a natural way. Response functions are calculated at the same time as the full radiative transfer equation for polarized light is integrated, which determines values of many free parameters in a reasonable computation time. SIR demonstrates high stability, accuracy, and uniqueness of results, even when simulated observations present signal-to-noise ratios of the order of the lowest acceptable values in real observations.

[ascl:1212.009] Aegean: Compact source finding in radio images

Aegean, written in python, finds compact sources within radio images by seeking out islands of pixels above a given threshold and then using the curvature of the image to determine how many Gaussian components should be used to describe the island. The Gaussian fitting is initiated with parameters determined from the curvature and intensity maps, and makes use of mpfit to perform a constrained fit. Aegean has been optimized for compact radio sources in images that have no diffuse background emission, but by pre-processing the images with a spatial filter, or by convolving an optical image with an appropriately small PSF, Aegean is able to produce excellent results in a range of applications.

[ascl:1212.010] Synth3: Non-magnetic spectrum synthesis code

Synth3 is a non-magnetic spectrum synthesis code. It works with model atmospheres in Kurucz format and VALD Sf line lists and features element stratification, molecular equilibrium and individual microturbulence for each line. Disk integration can be done with s3di which is included in the archive. Synth3 computes spectra emergent from the stellar atmospheres with a depth-dependent chemical composition if depth-dependent abundance is provided in the input model atmosphere file.

[ascl:1212.011] DrizzlePac: HST image software

DrizzlePac allows users to easily and accurately align and combine HST images taken at multiple epochs, and even with different instruments. It is a suite of supporting tasks for AstroDrizzle which includes:

- astrodrizzle to align and combine images
- tweakreg and tweakback for aligning images in different visits
- pixtopix transforms an X,Y pixel position to its pixel position after distortion corrections
- skytopix transforms sky coordinates to X,Y pixel positions. A reverse transformation can be done using the task pixtosky.

[ascl:1212.012] ddisk: Debris disk time-evolution

ddisk is an IDL script that calculates the time-evolution of a circumstellar debris disk. It calculates dust abundances over time for a debris-disk that is produced by a planetesimal disk that is grinding away due to collisional erosion.

[ascl:1212.013] EXSdetect: Extended X-ray Source Detection

EXSdetect is a python implementation of an X-ray source detection algorithm which is optimally designed to detected faint extended sources and makes use of Voronoi tessellation and Friend-of-Friend technique. It is a flexible tool capable of detecting extended sources down to the lowest flux levels attainable within instrumental limitations while maintaining robust photometry, high completeness, and low contamination, regardless of source morphology. EXSdetect was developed mainly to exploit the ever-increasing wealth of archival X-ray data, but is also ideally suited to explore the scientific capabilities of future X-ray facilities, with a strong focus on investigations of distant groups and clusters of galaxies.

[ascl:1212.014] Thrust: Productivity-Oriented Library for CUDA

Thrust is a parallel algorithms library which resembles the C++ Standard Template Library (STL). Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. Interoperability with established technologies (such as CUDA, TBB, and OpenMP) facilitates integration with existing software.

[ascl:1212.015] TMAP: Tübingen NLTE Model-Atmosphere Package

The Tübingen NLTE Model-Atmosphere Package (TMAP) is a tool to calculate stellar atmospheres in spherical or plane-parallel geometry in hydrostatic and radiative equilibrium allowing departures from local thermodynamic equilibrium (LTE) for the population of atomic levels. It is based on the Accelerated Lambda Iteration (ALI) method and is able to account for line blanketing by metals. All elements from hydrogen to nickel may be included in the calculation with model atoms which are tailored for the aims of the user.

[ascl:1211.001] S2LET: Fast wavelet analysis on the sphere

S2LET provides high performance routines for fast wavelet analysis of signals on the sphere. It uses the SSHT code (ascl:2207.034) built on the MW sampling theorem to perform exact spherical harmonic transforms on the sphere. The resulting wavelet transform implemented in S2LET is theoretically exact, i.e. a band-limited signal can be recovered from its wavelet coefficients exactly and the wavelet coefficients capture all the information. S2LET also supports the HEALPix sampling scheme, in which case the transforms are not theoretically exact but achieve good numerical accuracy. The core routines of S2LET are written in C and have interfaces in Matlab, IDL and Java. Real signals can be written to and read from FITS files and plotted as Mollweide projections.

[ascl:1211.002] FreeEOS: Equation of State for stellar interiors calculations

FreeEOS is a Fortran library for rapidly calculating the equation of state using an efficient free-energy minimization technique that is suitable for physical conditions in stellar interiors. Converged FreeEOS solutions can be reliably determined for the first time for physical conditions occurring in stellar models with masses between 0.1 M and the hydrogen-burning limit near 0.07 M and hot brown-dwarf models just below that limit. However, an initial survey of results for those conditions showed EOS discontinuities (plasma phase transitions) and other problems which will need to be addressed in future work by adjusting the interaction radii characterizing the pressure ionization used for the FreeEOS calculations.

[ascl:1211.003] WVT Binning: Spatially adaptive 2-D binning

WVT Binning is a spatially adaptive 2-dimensional binning algorithm designed to bin sparse X-ray data. It can handle background subtracted, exposure corrected data to produce intensity images, hardness ratio maps, or temperature maps. The algorithm is an extension of Cappellari & Copin's (2003) Voronoi binning code and uses Weighted Voronoi Tesselations (WVT) to produce a very compact binning structure with a constant S/N per bin. The bin size adjusts to the required resolution in single-pixel steps, which minimizes the scatter around the target S/N. The code is very versatile and can in principle be applied to any type of data. The user manual contains instructions on how to apply the WVT binning code to X-ray data and how to extend the algorithm to other problems.

[ascl:1211.004] CORRFIT: Cross-Correlation Routines

CORRFIT is a set of routines that use the cross-correlation method to extract parameters of the line-of-sight velocity distribution from galactic spectra and stellar templates observed on the same system. It works best when the broadening function is well sampled at the spectral resolution used (e.g. 200 km/s dispersion at 2 Angstrom resolution). Results become increasingly sensitive to the spectral match between galaxy and template if the broadening function is not well sampled. CORRFIT does not work well for dispersions less than the velocity sampling interval ('delta' in the code) unless the template is perfect.

[ascl:1211.005] C-m Emu: Concentration-mass relation emulator

The concentration-mass relation for dark matter-dominated halos is one of the essential results expected from a theory of structure formation. C-m Emu is a simple numerical code for the c-M relation as a function of cosmological parameters for wCDM models generates the best-fit power-law model for each redshift separately and then interpolate between the redshifts. This produces a more accurate answer at each redshift at the minimal cost of running a fast code for every c -M prediction instead of using one fitting formula. The emulator is constructed from 37 individual models, with three nested N-body gravity-only simulations carried out for each model. The mass range covered by the emulator is 2 x 10^{12} M_sun < M <10^{15} M_sun with a corresponding redshift range of z=0 -1. Over this range of mass and redshift, as well as the variation of cosmological parameters studied, the mean halo concentration varies from c ~ 2 to c ~ 8. The distribution of the concentration at fixed mass is Gaussian with a standard deviation of one-third of the mean value, almost independent of cosmology, mass, and redshift over the ranges probed by the simulations.

[ascl:1211.006] VorBin: Voronoi binning method

VorBin (Voronoi binning method) bins two-dimensional data to a constant signal-to-noise ratio per bin. It optimally solves the problem of preserving the maximum spatial resolution of general two-dimensional data, given a constraint on the minimum signal-to-noise ratio. The method is available in both IDL and Python.

[ascl:1210.001] GP2PCF: Brute-force computation of 2-point correlation functions

The two-point correlation function is a simple statistic that quantifies the clustering of a given distribution of objects. In studies of the large scale structure of the Universe, it is an important tool containing information about the matter clustering and the evolution of the Universe at different cosmological epochs. A classical application of this statistic is the galaxy-galaxy correlation function to find constraints on the parameter Omega_m or the location of the baryonic acoustic oscillation peak. This calculation, however, is very expensive in terms of computer power and Graphics Processing Units provide one solution for efficient analysis of the increasingly larger galaxy surveys that are currently taking place.

GP2PCF is a public code in CUDA for performing this computation; with a single GPU board it is possible to achieve 120-fold speedups with respect to a standard implementation in C running on a single CPU. With respect to other solutions such as k-trees the improvement is of a factor of a few retaining full precision. The speedup is comparable to running in parallel in a cluster of O(100) cores.

[ascl:1210.002] pPXF: Penalized Pixel-Fitting stellar kinematics extraction

pPXF extracts the stellar kinematics or stellar population from absorption-line spectra of galaxies using the Penalized Pixel-Fitting method (pPXF) developed by Cappellari & Emsellem (2004, PASP, 116, 138). Additional features implemented in the pPXF routine include:

  • Optimal template: Fitted together with the kinematics to minimize template-mismatch errors. Also useful to extract gas kinematics or derive emission-corrected line-strengths indexes. One can use synthetic templates to study the stellar population of galaxies via "Full Spectral Fitting" instead of using traditional line-strengths.
  • Regularization of templates weights: To reduce the noise in the recovery of the stellar population parameters and attach a physical meaning to the output weights assigned to the templates in term of the star formation history (SFH) or metallicity distribution of an individual galaxy.
  • Iterative sigma clipping: To clean the spectra from residual bad pixels or cosmic rays.
  • Additive/multiplicative polynomials: To correct low frequency continuum variations. Also useful for calibration purposes.

The code is available in IDL and in Python versions.

[ascl:1210.003] GOSSIP: SED fitting code

GOSSIP fits the electro-magnetic emission of an object (the SED, Spectral Energy Distribution) against synthetic models to find the simulated one that best reproduces the observed data. It builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a chi-square minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions.

[ascl:1210.004] EZ: A Tool For Automatic Redshift Measurement

EZ (Easy-Z) estimates redshifts for extragalactic objects. It compares the observed spectrum with a set of (user given) spectral templates to find out the best value for the redshift. To accomplish this task, it uses a highly configurable set of algorithms. EZ is easily extendible with new algorithms. It is implemented as a set of C programs and a number of python classes. It can be used as a standalone program, or the python classes can be directly imported by other applications.

[ascl:1210.005] SGNAPS: Software for Graphical Navigation, Analysis and Plotting of Spectra

SGNAPS allows the user to plot a one-dimensional spectrum, together with the corresponding two-dimensional and a reference spectrum (for example the sky spectrum). This makes it possible to check on the reality of spectral features that are present in the one-dimensional spectrum, which could be due to bad sky subtraction or fringing residuals. It is also possible to zoom in and out all three spectra, edit the one-dimensional spectrum, smooth it with a simple square window function, measure the signal to noise over a selected wavelength interval, and fit the position of a selected spectral line. SGNAPS also allows the astronomer to obtain quick redshift estimates by providing a tool to fit or mark the position of a spectral line, and a function that will compute a list of possible redshifts based on a list of known lines in galaxy spectra. SGNAPS is derived from the plotting tools of VIPGI and contains almost all of their capabilities.

NOTE: SGNAPS functionality has been transitioned to EZ.

[ascl:1210.006] TA-DA: A Tool for Astrophysical Data Analysis

TA-DA is a pre-compiled IDL widget-based application which greatly simplifies and improves the analysis of stellar photometric data in comparison with theoretical models and allows the derivation of stellar parameters from multi-band photometry. It is flexible and can address a number of problems, from the interpolation of stellar models or sets of stellar physical parameters in general to the computation of synthetic photometry in arbitrary filters or units. It also analyzes observed color-magnitude diagrams and allows a Bayesian derivation of stellar parameters (and extinction) based on multi-band data.

[ascl:1210.007] FLUKA: Fully integrated particle physics Monte Carlo simulation package

FLUKA (FLUktuierende KAskade) is a general-purpose tool for calculations of particle transport and interactions with matter. FLUKA can simulate with high accuracy the interaction and propagation in matter of about 60 different particles, including photons and electrons from 1 keV to thousands of TeV, neutrinos, muons of any energy, hadrons of energies up to 20 TeV (up to 10 PeV by linking FLUKA with the DPMJET code) and all the corresponding antiparticles, neutrons down to thermal energies and heavy ions. The program, written in Fortran, can also transport polarised photons (e.g., synchrotron radiation) and optical photons. Time evolution and tracking of emitted radiation from unstable residual nuclei can be performed online.

[ascl:1210.008] Rockstar: Phase-space halo finder

Rockstar (Robust Overdensity Calculation using K-Space Topologically Adaptive Refinement) identifies dark matter halos, substructure, and tidal features. The approach is based on adaptive hierarchical refinement of friends-of-friends groups in six phase-space dimensions and one time dimension, which allows for robust (grid-independent, shape-independent, and noise-resilient) tracking of substructure. Our method is massively parallel (up to 10^5 CPUs) and runs on the largest current simulations (>10^10 particles) with high efficiency (10 CPU hours and 60 gigabytes of memory required per billion particles analyzed). Rockstar offers significant improvement in substructure recovery as compared to several other halo finders.

[ascl:1210.009] PAHFIT: Properties of PAH Emission

PAHFIT is an IDL tool for decomposing Spitzer IRS spectra of PAH emission sources, with a special emphasis on the careful recovery of ambiguous silicate absorption, and weak, blended dust emission features. PAHFIT is primarily designed for use with full 5-35 micron Spitzer low-resolution IRS spectra. PAHFIT is a flexible tool for fitting spectra, and you can add or disable features, compute combined flux bands, change fitting limits, etc., without changing the code.

PAHFIT uses a simple, physically-motivated model, consisting of starlight, thermal dust continuum in a small number of fixed temperature bins, resolved dust features and feature blends, prominent emission lines (which themselves can be blended with dust features), as well as simple fully-mixed or screen dust extinction, dominated by the silicate absorption bands at 9.7 and 18 microns. Most model components are held fixed or are tightly constrained. PAHFIT uses Drude profiles to recover the full strength of dust emission features and blends, including the significant power in the wings of the broad emission profiles. This means the resulting feature strengths are larger (by factors of 2-4) than are recovered by methods which estimate the underlying continuum using line segments or spline curves fit through fiducial wavelength anchors.

[ascl:1210.010] CALCLENS: Curved-sky grAvitational Lensing for Cosmological Light conE simulatioNS

CALCLENS, written in C and employing widely available software libraries, efficiently computes weak gravitational lensing shear signals from large N-body light cone simulations over a curved sky. The algorithm properly accounts for the sky curvature and boundary conditions, is able to produce redshift-dependent shear signals including corrections to the Born approximation by using multiple-plane ray tracing, and properly computes the lensed images of source galaxies in the light cone. The key feature of this algorithm is a new, computationally efficient Poisson solver for the sphere that combines spherical harmonic transform and multgrid methods. As a result, large areas of sky (~10,000 square degrees) can be ray traced efficiently at high-resolution using only a few hundred cores on widely available machines. Coupled with realistic galaxy populations placed in large N-body light cone simulations, CALCLENS is ideally suited for the construction of synthetic weak lensing shear catalogs to be used to test for systematic effects in data analysis procedures for upcoming large-area sky surveys.

[ascl:1210.011] Consistent Trees: Gravitationally Consistent Halo Catalogs and Merger Trees for Precision Cosmology

Consistent Trees generates merger trees and halo catalogs which explicitly ensure consistency of halo properties (mass, position, velocity, radius) across timesteps. It has demonstrated the ability to improve both the completeness (through detecting and inserting otherwise missing halos) and purity (through detecting and removing spurious objects) of both merger trees and halo catalogs. Consistent Trees is able to robustly measure the self-consistency of halo finders and to directly measure the uncertainties in halo positions, halo velocities, and the halo mass function for a given halo finder based on consistency between snapshots in cosmological simulations.

[ascl:1210.012] SearchCal: The JMMC Evolutive Search Calibrator Tool

SearchCal builds an evolutive catalog of stars suitable as calibrators within any given user-defined angular distance and magnitude around a scientific target. SearchCal can select suitable bright calibration stars (V ≤ 10; K ≤ 5.0) for obtaining the ultimate precision of current interferometric instruments like the VLTI and faint calibration stars up to K ~ 15 around the scientific target. Star catalogs available at the CDS are searched via web requests and provide the useful astrometric and photometric informations for selecting calibrators. The missing photometries are computed with an accuracy of about 0.1 mag. The stellar angular diameter is estimated with a precision of about 10% through newly determined surface-brightness versus color-index relations based on the I, J, H and K magnitudes. For each star the squared visibility is computed taking into account the central wavelength and the maximum baseline of the predicted observations.

[ascl:1210.013] ConvPhot: A profile-matching algorithm for precision photometry

ConvPhot measures colors between two images having different resolutions. ConvPhot is designed to work especially for faint galaxies, accurately measuring colors in relatively crowded fields. It makes full use of the spatial and morphological information contained in the highest quality images to analyze multiwavelength data with inhomogeneous image quality.
Written in 2007, ConvPhot has been superseded by T-PHOT (ascl:1609.001)

[ascl:1210.014] TRIP: General computer algebra system for celestial mechanics

TRIP is an interactive computer algebra system that is devoted to perturbation series computations, and specially adapted to celestial mechanics. Its development started in 1988, as an upgrade of the special purpose FORTRAN routines elaborated by J. Laskar for the demonstration of the chaotic behavior of the Solar System. TRIP is a mature and efficient tool for handling multivariate generalized power series, and embeds two kernels, a symbolic and a numerical kernel. This numerical kernel communicates with Gnuplot or Grace to plot the graphics and allows one to plot the numerical evaluation of symbolic objects.

[ascl:1210.015] Tempo2: Pulsar Timing Package

Tempo2 is a pulsar timing package developed to be used both for general pulsar timing applications and also for pulsar timing array research in which data-sets from multiple pulsars need to be processed simultaneously. It was initially developed by George Hobbs and Russell Edwards as part of the Parkes Pulsar Timing Array project. Tempo2 is based on the original Tempo (ascl:1509.002) code and can be used (from the command-line) in a similar fashion. It is very versatile and can be extended by plugins.

[ascl:1210.016] Specview: 1-D spectral visualization and analysis of astronomical spectrograms

Specview is a tool for 1-D spectral visualization and analysis of astronomical spectrograms. Written in Java, it is capable of reading all the Hubble Space Telescope spectral data formats as well as data from several other instruments (such as IUE, FUSE, ISO, FORS and SDSS), preview spectra from MAST, and data from generic FITS and ASCII tables. It can read data from Virtual Observatory servers, and read and write spectrogram data in Virtual Observatory SED format. It can also read files in the SPC Galactic format used in the chemistry field. Once ingested, data can be plotted and examined with a large selection of custom settings. Specview supports instrument-specific data quality handling, flexible spectral units conversions, custom plotting attributes, plot annotations, tiled plots, hardcopy to JPEG files and PostScript file or printer, etc. Specview can be used to build wide-band SEDs, overplotting or combining data from the same astronomical source taken with different instruments and/or spectral bands. Data can be further processed with averaging, splicing, detrending, and Fourier filtering tools. Specview has a spectral model fitting capability that enables the user to work with multi-component models (including user-defined models) and fit models to data.

[ascl:1210.017] McPHAC: McGill Planar Hydrogen Atmosphere Code

The McGill Planar Hydrogen Atmosphere Code (McPHAC) v1.1 calculates the hydrostatic equilibrium structure and emergent spectrum of an unmagnetized hydrogen atmosphere in the plane-parallel approximation at surface gravities appropriate for neutron stars. McPHAC incorporates several improvements over previous codes for which tabulated model spectra are available: (1) Thomson scattering is treated anisotropically, which is shown to result in a 0.2%-3% correction in the emergent spectral flux across the 0.1-5 keV passband; (2) the McPHAC source code is made available to the community, allowing it to be scrutinized and modified by other researchers wishing to study or extend its capabilities; and (3) the numerical uncertainty resulting from the discrete and iterative solution is studied as a function of photon energy, indicating that McPHAC is capable of producing spectra with numerical uncertainties <0.01%. The accuracy of the spectra may at present be limited to ~1%, but McPHAC enables researchers to study the impact of uncertain inputs and additional physical effects, thereby supporting future efforts to reduce those inaccuracies. Comparison of McPHAC results with spectra from one of the previous model atmosphere codes (NSA) shows agreement to lsim1% near the peaks of the emergent spectra. However, in the Wien tail a significant deficit of flux in the spectra of the previous model is revealed, determined to be due to the previous work not considering large enough optical depths at the highest photon frequencies. The deficit is most significant for spectra with T eff < 105.6 K, though even there it may not be of much practical importance for most observations.

[ascl:1210.018] Systemic Console: Advanced analysis of exoplanetary data

Systemic Console is a tool for advanced analysis of exoplanetary data. It comprises a graphical tool for fitting radial velocity and transits datasets and a library of routines for non-interactive calculations. Among its features are interactive plotting of RV curves and transits, combined fitting of RV and transit timing (primary and secondary), interactive periodograms and FAP estimation, and bootstrap and MCMC error estimation. The console package includes public radial velocity and transit data.

[ascl:1210.019] QFitsView: FITS file viewer

QFitsView is a FITS file viewer that can display one, two, and three-dimensional FITS files. It has three modes of operation, depending of what kind of data is being displayed. One-dimensional data are shown in an x-y plot. Two-dimensional images are shown in the main window. Three-dimensional data cubes can be displayed in a variety of ways, with the third dimension shown as a x-y plot at the bottom of the image display. QFitsView was written in C++ and uses the Qt widget library, which makes it available for all major platforms: Windows, MAC OS X, and many Unix variants.

[ascl:1210.020] GASGANO: Data File Organizer

GASGANO is a GUI software tool for managing and viewing data files produced by VLT Control System (VCS) and the Data Flow System (DFS). It is developed and maintained by ESO to help its user community manage and organize astronomical data observed and produced by all VLT compliant telescopes in a systematic way. The software understands FITS, PAF, and ASCII files, and Reduction Blocks, and can group, sort, classify, filter, and search data in addition to allowing the user to browse, view, and manage them.

[ascl:1210.021] SMART: Spectroscopic Modeling Analysis and Reduction Tool

SMART is an IDL-based software tool, developed by the IRS Instrument Team at Cornell University, that allows users to reduce and analyze Spitzer data from all four modules of the Infrared Spectrograph, including the peak-up arrays. The software is designed to make full use of the ancillary files generated in the Spitzer Science Center pipeline so that it can either remove or flag artifacts and corrupted data and maximize the signal-to-noise ratio in the extraction routines. It can be run in both interactive and batch modes. SMART includes visualization tools for assessing data quality, basic arithmetic operations for either two-dimensional images or one-dimensional spectra, extraction of both point and extended sources, and a suite of spectral analysis tools.

[ascl:1210.022] HAM2D: 2D Shearing Box Model

HAM solves non-relativistic hyperbolic partial differential equations in conservative form using high-resolution shock-capturing techniques. This version of HAM has been configured to solve the magnetohydrodynamic equations of motion in axisymmetry to evolve a shearing box model.

[ascl:1210.023] inf_solv: Kerr inflow solver

The efficiency of thin disk accretion onto black holes depends on the inner boundary condition, specifically the torque applied to the disk at the last stable orbit. This is usually assumed to vanish. This code estimates the torque on a magnetized disk using a steady magnetohydrodynamic inflow model originally developed by Takahashi et al. The efficiency e can depart significantly from the classical thin disk value. In some cases e > 1, i.e., energy is extracted from the black hole.

[ascl:1210.024] ORBADV: ORBital ADVection by interpolation

ORBADV adopts a ZEUS-like scheme to solve magnetohydrodynamic equations of motion in a shearing sheet. The magnetic field is discretized on a staggered mesh, and magnetic field variables represent fluxes through zone faces. The code uses obital advection to ensure fast and accurate integration in a large shearing box.

[ascl:1210.025] TwoDSSM: Self-gravitating 2D shearing sheet

TwoDSSM solves the equations of self-gravitating hydrodynamics in the shearing sheet, with cooling. TwoDSSM is configured to use a simple, exponential cooling model, although it contains code for a more complicated (and perhaps more realistic) cooling model based on a one-zone vertical model. The complicated cooling model can be switched on using a flag.

[ascl:1210.026] PVS-GRMHD: Conservative GRMHD Primitive Variable Solvers

Conservative numerical schemes for general relativistic magnetohydrodynamics (GRMHD) require a method for transforming between "conserved'' variables such as momentum and energy density and "primitive" variables such as rest-mass density, internal energy, and components of the four-velocity. The forward transformation (primitive to conserved) has a closed-form solution, but the inverse transformation (conserved to primitive) requires the solution of a set of five nonlinear equations. This code performs the inversion.

[ascl:1210.027] PyCosmic: Detecting cosmics in CALIFA and other fiber-fed integral-field spectroscopy datasets

The detection of cosmic ray hits (cosmics) in fiber-fed integral-field spectroscopy (IFS) data of single exposures is a challenging task because of the complex signal recorded by IFS instruments. Existing detection algorithms are commonly found to be unreliable in the case of IFS data, and the optimal parameter settings are usually unknown a priori for a given dataset. The Calar Alto legacy integral field area (CALIFA) survey generates hundreds of IFS datasets for which a reliable and robust detection algorithm for cosmics is required as an important part of the fully automatic CALIFA data reduction pipeline. PyCosmic combines the edge-detection algorithm of L.A.Cosmic with a point-spread function convolution scheme. PyCosmic is the only algorithm that achieves an acceptable detection performance for CALIFA data. Only for strongly undersampled IFS data does L.A.Cosmic exceed the performance of PyCosmic by a few percent. Thus, PyCosmic appears to be the most versatile cosmics detection algorithm for IFS data.

[ascl:1210.028] QYMSYM: A GPU-accelerated hybrid symplectic integrator

QYMSYM is a GPU accelerated 2nd order hybrid symplectic integrator that identifies close approaches between particles and switches from symplectic to Hermite algorithms for particles that require higher resolution integrations. This is a parallel code running with CUDA on a video card that puts the many processors on board to work while taking advantage of fast shared memory.

[ascl:1210.029] Sapporo: N-body simulation library for GPUs

Sapporo mimics the behavior of GRAPE hardware and uses the GPU to perform high-precision gravitational N-body simulations. It makes use of CUDA and therefore only works on NVIDIA GPUs. N-body codes currently running on GRAPE-6 can switch to Sapporo by a simple relinking of the library. Sapporo's precision is comparable to that of GRAPE-6, even though internally the GPU hardware is limited to single precision arithmetics. This limitation is effectively overcome by emulating double precision for calculating the distance between particles.

[ascl:1210.030] BOOTTRAN: Error Bars for Keplerian Orbital Parameters

BOOTTRAN calculates error bars for Keplerian orbital parameters for both single- and multiple-planet systems. It takes the best-fit parameters and radial velocity data (BJD, velocity, errors) and calculates the error bars from sampling distribution estimated via bootstrapping. It is recommended to be used together with the RVLIN (ascl:1210.031) package, which find best-fit Keplerian orbital parameters. Both RVLIN and BOOTTRAN are compatible with multiple-telescope data. BOOTTRAN also calculates the transit time and secondary eclipse time and their associated error bars. The algorithm is described in the appendix of the associated article.

[ascl:1210.031] RVLIN: Fitting Keplerian curves to radial velocity data

The RVLIN package for IDL is a set of routines that quickly fits an arbitrary number of Keplerian curves to radial velocity data. It can handle data from multiple telescopes (i.e. it solves for the offset), constraints on P, e, and time of peri passage, and can incorporate transit timing data. The code handles fixed periods and circular orbits in combination and transit time constraints, including for multiple transiting planets.

[ascl:1209.001] Bayesian Blocks: Detecting and characterizing local variability in time series

Bayesian Blocks is a time-domain algorithm for detecting localized structures (bursts), revealing pulse shapes within bursts, and generally characterizing intensity variations. The input is raw time series data, in almost any form. Three data modes are elaborated: (1) time-tagged events, (2) binned counts, and (3) measurements at arbitrary times with normal errors. The output is the most probable segmentation of the observation interval into sub-intervals during which the signal is perceptibly constant, i.e. has no statistically significant variations. The idea is not that the source is deemed to actually have this discontinuous, piecewise constant form, rather that such an approximate and generic model is often useful. Treatment of data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multi-variate time series data, analysis of variance, data on the circle, other data modes, and dispersed data are included.

This implementation is exact and replaces the greedy, approximate, and outdated algorithm implemented in BLOCK.

[ascl:1209.002] JAGS: Just Another Gibbs Sampler

JAGS analyzes Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS has three aims:

  • to have a cross-platform engine for the BUGS language;
  • to be extensible, allowing users to write their own functions, distributions and samplers; and
  • to be a platform for experimentation with ideas in Bayesian modeling.

[ascl:1209.003] LSD: Large Survey Database framework

The Large Survey Database (LSD) is a Python framework and DBMS for distributed storage, cross-matching and querying of large survey catalogs (>10^9 rows, >1 TB). The primary driver behind its development is the analysis of Pan-STARRS PS1 data. It is specifically optimized for fast queries and parallel sweeps of positionally and temporally indexed datasets. It transparently scales to more than >10^2 nodes, and can be made to function in "shared nothing" architectures.

[ascl:1209.004] CHORIZOS: CHi-square cOde for parameterRized modeling and characterIZation of phOtometry and Spectrophotmetry

CHORIZOS is a multi-purpose Bayesian code developed in IDL to compare photometric data with model spectral energy distributions (SEDs). The user can select the SED family (e.g. Kurucz) and choose the behavior of each parameter (e.g. Teff) to be fixed, constrained to a given range, or unconstrained. The code calculates the likelihood for the full specified parameter ranges, thus allowing for the identification of multiple solutions and the evaluation of the full correlation matrix for the derived parameters of a single solution.

[ascl:1209.005] HARM: A Numerical Scheme for General Relativistic Magnetohydrodynamics

HARM uses a conservative, shock-capturing scheme for evolving the equations of general relativistic magnetohydrodynamics. The fluxes are calculated using the Harten, Lax, & van Leer scheme. A variant of constrained transport, proposed earlier by Tóth, is used to maintain a divergence-free magnetic field. Only the covariant form of the metric in a coordinate basis is required to specify the geometry. On smooth flows HARM converges at second order.

[ascl:1209.006] macula: Rotational modulations in the photometry of spotted stars

Photometric rotational modulations due to starspots remain the most common and accessible way to study stellar activity. Modelling rotational modulations allows one to invert the observations into several basic parameters, such as the rotation period, spot coverage, stellar inclination and differential rotation rate. The most widely used analytic model for this inversion comes from Budding (1977) and Dorren (1987), who considered circular, grey starspots for a linearly limb darkened star. That model is extended to be more suitable in the analysis of high precision photometry such as that by Kepler. Macula, a Fortran 90 code, provides several improvements, such as non-linear limb darkening of the star and spot, a single-domain analytic function, partial derivatives for all input parameters, temporal partial derivatives, diluted light compensation, instrumental offset normalisations, differential rotation, starspot evolution and predictions of transit depth variations due to unocculted spots. The inclusion of non-linear limb darkening means macula has a maximum photometric error an order-of-magnitude less than that of Dorren (1987) for Sun-like stars observed in the Kepler-bandpass. The code executes three orders-of-magnitude faster than comparable numerical codes making it well-suited for inference problems.

[ascl:1209.007] TMCalc: Fast estimation of stellar metallicity [Fe/H]

TMCalc is a C code developed as an extension to ARES. Using the line list given, the code can be used as a precise and fast indicator of the spectroscopic temperature and metallicity for dwarf FKG stars with effective temperatures ranging from 4500 K to 6500 K and with [Fe/H] ranging from -0.8 dex to 0.4 dex.

[ascl:1209.008] Phantom-GRAPE: SIMD accelerated numerical library for N-body simulations

Phantom-GRAPE is a numerical software library to accelerate collisionless $N$-body simulation with SIMD instruction set on x86 architecture. The Newton's forces and also central forces with an arbitrary shape f(r), which have a finite cutoff radius r_cut (i.e. f(r)=0 at r>r_cut), can be quickly computed.

[ascl:1209.009] ANNz: Artificial Neural Networks for estimating photometric redshifts

ANNz is a freely available software package for photometric redshift estimation using Artificial Neural Networks. ANNz learns the relation between photometry and redshift from an appropriate training set of galaxies for which the redshift is already known. Where a large and representative training set is available, ANNz is a highly competitive tool when compared with traditional template-fitting methods.

For a newer implementation of this package, please see ANNz2 (ascl:1910.014).

[ascl:1209.010] MeqTrees: Software package for implementing Measurement Equations

MeqTrees is a software package for implementing Measurement Equations. This makes it uniquely suited for simulation and calibration of radioastronomical data, especially that involving new radiotelescopes and observational regimes. MeqTrees is implemented as a Python-based front-end called the meqbrowser, and an efficient (C++-based) computational back-end called the meqserver. Numerical models are defined on the front-end via a Python-based Tree Definition Language (TDL), then rapidly executed on the back-end. The use of TDL facilitates an extremely short turn-around time for experimentation with new ideas. This is also helped by unprecedented visualization capabilities for all final and intermediate results. A flexible data model and a number of important optimizations in the back-end ensures that the numerical performance is comparable to that of hand-written code.

MeqTrees includes a highly capable FITS viewer and sky model manager called Tigger, which can also work as a standalone tool.

[ascl:1209.011] DiskFit: Modeling Asymmetries in Disk Galaxies

DiskFit implements procedures for fitting non-axisymmetries in either kinematic or photometric data. DiskFit can analyze H-alpha and CO velocity field data as well as HI kinematics to search for non-circular motions in the disk galaxies. DiskFit can also be used to constrain photometric models of the disc, bar and bulge. It deprecates an earlier version, by a subset of these authors, called velfit.

[ascl:1209.012] Scanamorphos: Maps from scan observations made with bolometer arrays

Scanamorphos is an IDL program to build maps from scan observations made with bolometer arrays. Scanamorphos can post-process scan observations performed with the Herschel photometer arrays. This post-processing mainly consists in subtracting the total low-frequency noise (both its thermal and non-thermal components), masking cosmic ray hit residuals, and projecting the data onto a map. Although it was developed for Herschel, it is also applicable with minimal adjustment to scan observations made with other bolometer arrays provided they entail sufficient redundancy; it was successfully applied to P-Artemis, an instrument operating on the APEX telescope. Scanamorphos does not assume any particular noise model and does not apply any Fourier-space filtering to the data. It is an empirical tool using only the redundancy built in the observations, taking advantage of the fact that each portion of the sky is sampled at multiple times by multiple bolometers. The user is allowed to optionally visualize and control results at each intermediate step, but the processing is fully automated.

[ascl:1209.013] IRACproc: IRAC Post-BCD Processing

IRACproc is a software suite that facilitates the co-addition of dithered or mapped Spitzer/IRAC data to make them ready for further analysis with application to a wide variety of IRAC observing programs. The software runs within PDL, a numeric extension for Perl available from pdl.perl.org, and as stand alone perl scripts. In acting as a wrapper for the Spitzer Science Center's MOPEX software, IRACproc improves the rejection of cosmic rays and other transients in the co-added data. In addition, IRACproc performs (optional) Point Spread Function (PSF) fitting, subtraction, and masking of saturated stars.

[ascl:1209.014] FAMIAS: Frequency Analysis and Mode Identification for AsteroSeismology

FAMIAS (Frequency Analysis and Mode Identification for Asteroseismology) is a package of software tools programmed in C++ for the analysis of photometric and spectroscopic time-series data. FAMIAS provides analysis tools that are required for the steps between the data reduction and the seismic modeling. Two main sets of tools are incorporated in FAMIAS. The first set permits to search for periodicities in the data using Fourier and non-linear least-squares fitting techniques. The other set permits to carry out a mode identification for the detected pulsation frequencies to determine their harmonic degree l, and azimuthal order m. FAMIAS is applicable to main-sequence pulsators hotter than the Sun. This includes Gamma Dor, Delta Sct stars, slowly pulsating B (SPB)-stars and Beta Cep stars - basically all stars for which empirical mode identification is required to successfully carry out asteroseismology.

[ascl:1209.015] Aspects: Probabilistic/positional association of catalogs of sources

Given two catalogs K and K' of n and n' astrophysical sources, respectively, Aspects (Association positionnelle/probabiliste de catalogues de sources) computes, for any objects MiK and M'jK', the probability that M'j is a counterpart of Mi, i.e. that they are the same source. To determine this probability of association, the code takes into account the coordinates and the positional uncertainties of all the objects. Aspects also computes the probability P(Ai, 0 | C ∩ C') that Mi has no counterpart.

Aspects is written in Fortran 95; the required Fortran 90 Numerical Recipes routines used in version 1.0 have been replaced with free equivalents in version 2.0.

[ascl:1208.001] Astrometry.net: Astrometric calibration of images

Astrometry.net is a reliable and robust system that takes as input an astronomical image and returns as output the pointing, scale, and orientation of that image (the astrometric calibration or World Coordinate System information). The system requires no first guess, and works with the information in the image pixels alone; that is, the problem is a generalization of the "lost in space" problem in which nothing—not even the image scale—is known. After robust source detection is performed in the input image, asterisms (sets of four or five stars) are geometrically hashed and compared to pre-indexed hashes to generate hypotheses about the astrometric calibration. A hypothesis is only accepted as true if it passes a Bayesian decision theory test against a null hypothesis. With indices built from the USNO-B catalog and designed for uniformity of coverage and redundancy, the success rate is >99.9% for contemporary near-ultraviolet and visual imaging survey data, with no false positives. The failure rate is consistent with the incompleteness of the USNO-B catalog; augmentation with indices built from the Two Micron All Sky Survey catalog brings the completeness to 100% with no false positives. We are using this system to generate consistent and standards-compliant meta-data for digital and digitized imaging from plate repositories, automated observatories, individual scientific investigators, and hobbyists.

[ascl:1208.002] BINSYN: Simulating Spectra and Light Curves of Binary Systems with or without Accretion Disks

The BINSYN program suite is a collection of programs for analysis of binary star systems with or without an optically thick accretion disk. BINSYN produces synthetic spectra of individual binary star components plus a synthetic spectrum of the system. If the system includes an accretion disk, BINSYN also produces a separate synthetic spectrum of the disk face and rim. A system routine convolves the synthetic spectra with filter profiles of several photometric standards to produce absolute synthetic photometry output. The package generates synthetic light curves and determines an optimized solution for system parameters.

[ascl:1208.003] APT: Aperture Photometry Tool

Aperture Photometry Tool (APT) is software for astronomers and students interested in manually exploring the photometric qualities of astronomical images. It has a graphical user interface (GUI) which allows the image data associated with aperture photometry calculations for point and extended sources to be visualized and, therefore, more effectively analyzed. Mouse-clicking on a source in the displayed image draws a circular or elliptical aperture and sky annulus around the source and computes the source intensity and its uncertainty, along with several commonly used measures of the local sky background and its variability. The results are displayed and can be optionally saved to an aperture-photometry-table file and plotted on graphs in various ways using functions available in the software. APT is geared toward processing sources in a small number of images and is not suitable for bulk processing a large number of images, unlike other aperture photometry packages (e.g., SExtractor). However, APT does have a convenient source-list tool that enables calculations for a large number of detections in a given image. The source-list tool can be run either in automatic mode to generate an aperture photometry table quickly or in manual mode to permit inspection and adjustment of the calculation for each individual detection. APT displays a variety of useful graphs, including image histogram, and aperture slices, source scatter plot, sky scatter plot, sky histogram, radial profile, curve of growth, and aperture-photometry-table scatter plots and histograms. APT has functions for customizing calculations, including outlier rejection, pixel “picking” and “zapping,” and a selection of source and sky models. The radial-profile-interpolation source model, accessed via the radial-profile-plot panel, allows recovery of source intensity from pixels with missing data and can be especially beneficial in crowded fields.

[ascl:1208.004] PyKE: Reduction and analysis of Kepler Simple Aperture Photometry data

PyKE is a python-based PyRAF package that can also be run as a stand-alone program within a unix-based shell without compiling against PyRAF. It is a group of tasks developed for the reduction and analysis of Kepler Simple Aperture Photometry (SAP) data of individual targets with individual characteristics. The main purposes of these tasks are to i) re-extract light curves from manually-chosen pixel apertures and ii) cotrend and/or detrend the data in order to reduce or remove systematic noise structure using methods tunable to user and target-specific requirements. PyKE is an open source project and contributions of new tasks or enhanced functionality of existing tasks by the community are welcome.

[ascl:1208.005] PSM: Planck Sky Model

The Planck Sky Model (PSM) is a global representation of the multi-component sky at frequencies ranging from a few GHz to a few THz. It summarizes in a synthetic way as much of our present knowledge as possible of the GHz sky. PSM is a complete and versatile set of programs and data that can be used for the simulation or the prediction of sky emission in the frequency range of typical CMB experiments, and in particular of the Planck sky mission. It was originally developed as part of the activities of Planck component separation Working Group (or "Working Group 2" - WG2), and of the ADAMIS team at APC.

PSM gives users the opportunity to investigate the model in some depth: look at its parameters, visualize its predictions for all individual components in various formats, simulate sky emission compatible with a given parameter set, and observe the modeled sky with a synthetic instrument. In particular, it makes possible the simulation of sky emission maps as could be plausibly observed by Planck or other CMB experiments that can be used as inputs for the development and testing of data processing and analysis techniques.

[ascl:1208.006] ccogs: Cosmological Calculations on the GPU

This suite contains two packages for computing cosmological quantities on the GPU: aperture_mass, which calculates the aperture mass map for a given dataset using the filter proposed by Schirmer et al (2007) (an NFW profile with exponential cut-offs at zero and large radii), and angular_correlation, which calculates the 2-pt angular correlation function using data and a flat distribution of randomly generated galaxies. A particular estimator is chosen, but the user has the flexibility to explore other estimators.

[ascl:1208.007] Big MACS: Accurate photometric calibration

Big MACS is a Python program that estimates an accurate photometric calibration from only an input catalog of stellar magnitudes and filter transmission functions. The user does not have to measure color terms which can be difficult to characterize. Supplied with filter transmission functions, Big MACS synthesizes an expected stellar locus for your data and then simultaneously solves for all unknown zeropoints when fitting to the instrumental locus. The code uses a spectroscopic model for the SDSS stellar locus in color-color space and filter functions to compute expected locus. The stellar locus model is corrected for Milky Way reddening. If SDSS or 2MASS photometry is available for stars in field, Big MACS can yield a highly accurate absolute calibration.

[ascl:1208.008] TiRiFiC: Tilted Ring Fitting Code

Tilted Ring Fitting Code (TiRiFiC) is a prototype computer program to construct simulated (high-resolution) astronomical spectroscopic 3d-observations (data cubes) of simple kinematical and morphological models of rotating (galactic) disks. It is possible to automatically optimize the parameterizations of constructed model disks to fit spectroscopic (3d-) observations via a χ2 minimization. TiRiFiC is currently implemented as an add-on to the Groningen Image Processing System (GIPSY) software package and attempts to provide a method to automatically fit an extended tilted-ring model directly to a data cube.

[ascl:1208.009] BLOBCAT: Software to Catalog Blobs

BLOBCAT is a source extraction software that utilizes the flood fill algorithm to detect and catalog blobs, or islands of pixels representing sources, in 2D astronomical images. The software is designed to process radio-wavelength images of both Stokes I intensity and linear polarization, the latter formed through the quadrature sum of Stokes Q and U intensities or as a by-product of rotation measure synthesis. BLOBCAT corrects for two systematic biases to enable the flood fill algorithm to accurately measure flux densities for Gaussian sources. BLOBCAT exhibits accurate measurement performance in total intensity and, in particular, linear polarization, and is particularly suited to the analysis of large survey data.

[ascl:1208.010] BASE: Bayesian Astrometric and Spectroscopic Exoplanet Detection and Characterization Tool

BASE is a novel program for the combined or separate Bayesian analysis of astrometric and radial-velocity measurements of potential exoplanet hosts and binary stars. The tool fulfills two major tasks of exoplanet science, namely the detection of exoplanets and the characterization of their orbits. BASE was developed to provide the possibility of an integrated Bayesian analysis of stellar astrometric and Doppler-spectroscopic measurements with respect to their binary or planetary companions’ signals, correctly treating the astrometric measurement uncertainties and allowing to explore the whole parameter space without the need for informative prior constraints. The tool automatically diagnoses convergence of its Markov chain Monte Carlo (MCMC[2]) sampler to the posterior and regularly outputs status information. For orbit characterization, BASE delivers important results such as the probability densities and correlations of model parameters and derived quantities. BASE is a highly configurable command-line tool developed in Fortran 2008 and compiled with GFortran. Options can be used to control the program’s behaviour and supply information such as the stellar mass or prior information. Any option can be supplied in a configuration file and/or on the command line.

[ascl:1208.011] Fewbody: Numerical toolkit for simulating small-N gravitational dynamics

Fewbody is a numerical toolkit for simulating small-N gravitational dynamics. It is a general N-body dynamics code, although it was written for the purpose of performing scattering experiments, and therefore has several features that make it well-suited for this purpose. Fewbody uses the 8th-order Runge-Kutta Prince-Dormand integration method with 9th-order error estimate and adaptive timestep to advance the N-body system forward in time. It integrates the usual formulation of the N-body equations in configuration space, but allows for the option of global pairwise Kustaanheimo-Stiefel (K-S) regularization (Heggie 1974; Mikkola 1985). The code uses a binary tree algorithm to classify the N-body system into a set of independently bound hierarchies, and performs collisions between stars in the “sticky star” approximation. Fewbody contains a collection of command line utilities that can be used to perform individual scattering and N-body interactions, but is more generally a library of functions that can be used from within other codes.

[ascl:1208.012] Swarm-NG: Parallel n-body Integrations

Swarm-NG is a C++ library for the efficient direct integration of many n-body systems using highly-parallel Graphics Processing Units (GPU). Swarm-NG focuses on many few-body systems, e.g., thousands of systems with 3...15 bodies each, as is typical for the study of planetary systems; the code parallelizes the simulation, including both the numerical integration of the equations of motion and the evaluation of forces using NVIDIA's "Compute Unified Device Architecture" (CUDA) on the GPU. Swarm-NG includes optimized implementations of 4th order time-symmetrized Hermite integration and mixed variable symplectic integration as well as several sample codes for other algorithms to illustrate how non-CUDA-savvy users may themselves introduce customized integrators into the Swarm-NG framework. Applications of Swarm-NG include studying the late stages of planet formation, testing the stability of planetary systems and evaluating the goodness-of-fit between many planetary system models and observations of extrasolar planet host stars (e.g., radial velocity, astrometry, transit timing). While Swarm-NG focuses on the parallel integration of many planetary systems,the underlying integrators could be applied to a wide variety of problems that require repeatedly integrating a set of ordinary differential equations many times using different initial conditions and/or parameter values.

[ascl:1208.013] SolarSoft: Programming and data analysis environment for solar physics

SolarSoft is a set of integrated software libraries, data bases, and system utilities which provide a common programming and data analysis environment for Solar Physics. The SolarSoftWare (SSW) system is built from Yohkoh, SOHO, SDAC and Astronomy libraries and draws upon contributions from many members of those projects. It is primarily an IDL based system, although some instrument teams integrate executables written in other languages. The SSW environment provides a consistent look and feel at widely distributed co-investigator institutions to facilitate data exchange and to stimulate coordinated analysis. Commonalities and overlap in solar data and analysis goals are exploited to permit application of fundamental utilities to the data from many different solar instruments. The use of common libraries, utilities, techniques and interfaces minimizes the learning curve for investigators who are analyzing new solar data sets, correlating results from multiple experiments or performing research away from their home institution.

[ascl:1208.014] MPI-AMRVAC: MPI-Adaptive Mesh Refinement-Versatile Advection Code

MPI-AMRVAC is an MPI-parallelized Adaptive Mesh Refinement code, with some heritage (in the solver part) to the Versatile Advection Code or VAC, initiated by Gábor Tóth at the Astronomical Institute at Utrecht in November 1994, with help from Rony Keppens since 1996. Previous incarnations of the Adaptive Mesh Refinement version of VAC were of restricted use only, and have been used for basic research in AMR strategies, or for well-targeted applications. This MPI version uses a full octree block-based approach, and allows for general orthogonal coordinate systems. MPI-AMRVAC aims to advance any system of (primarily hyperbolic) partial differential equations by a number of different numerical schemes. The emphasis is on (near) conservation laws, with shock-dominated problems as a main research target. The actual equations are stored in separate modules, can be added if needed, and they can be selected by a simple configuration of the VACPP preprocessor. The dimensionality of the problem is also set through VACPP. The numerical schemes are able to handle discontinuities and smooth flows as well.

[ascl:1208.015] Lare3d: Lagrangian-Eulerian remap scheme for MHD

Lare3d is a Lagrangian-remap code for solving the non-linear MHD equations in three spatial dimensions.

[ascl:1208.016] VARTOOLS: Light Curve Analysis Program

The VARTOOLS program is a command line utility that provides tools for analyzing time series astronomical data. It implements a number of routines for calculating variability/periodicity statistics of light curves, as well as tools for modifying and filtering light curves.

[ascl:1208.017] APLpy: Astronomical Plotting Library in Python

APLpy (the Astronomical Plotting Library in Python) is a Python module for producing publication-quality plots of astronomical imaging data in FITS format. The module uses Matplotlib, a powerful and interactive plotting package. It is capable of creating output files in several graphical formats, including EPS, PDF, PS, PNG, and SVG. Plots can be made interactively or by using scripts, and can generate co-aligned FITS cubes to make three-color RGB images. It also offers different overlay capabilities, including contour sets, markers with customizable symbols, and coordinate grids, and a range of other useful features.

[ascl:1208.018] CUBEP3M: High performance P3M N-body code

CUBEP3M is a high performance cosmological N-body code which has many utilities and extensions, including a runtime halo finder, a non-Gaussian initial conditions generator, a tuneable accuracy, and a system of unique particle identification. CUBEP3M is fast, has a memory imprint up to three times lower than other widely used N-body codes, and has been run on up to 20,000 cores, achieving close to ideal weak scaling even at this problem size. It is well suited and has already been used for a broad number of science applications that require either large samples of non-linear realizations or very large dark matter N-body simulations, including cosmological reionization, baryonic acoustic oscillations, weak lensing or non-Gaussian statistics.

[ascl:1208.019] MPFIT: Robust non-linear least squares curve fitting

These IDL routines provide a robust and relatively fast way to perform least-squares curve and surface fitting. The algorithms are translated from MINPACK-1, which is a rugged minimization routine found on Netlib, and distributed with permission. This algorithm is more desirable than CURVEFIT because it is generally more stable and less likely to crash than the brute-force approach taken by CURVEFIT, which is based upon Numerical Recipes.

[ascl:1208.020] ParselTongue: AIPS Python Interface

ParselTongue is a Python interface to classic AIPS, Obit and possibly other task-based data reduction packages. It serves as the software infrastructure for some of the ALBUS implementation. It allows you to run AIPS tasks, and access AIPS headers and extension tables from Python. There is also support for running Obit tasks and accessing data in FITS files. Full access to the visibilities in AIPS UV data is also available.

[ascl:1208.021] EzGal: A Flexible Interface for Stellar Population Synthesis Models

EzGal is a flexible Python program which generates observable parameters (magnitudes, colors, and mass-to-light ratios) for arbitrary input stellar population synthesis (SPS) models; it enables simple, direct comparison of different model sets so that the uncertainty introduced by choice of model set can be quantified. EzGal is also capable of generating composite stellar population models (CSPs) for arbitrary input star-formation histories and reddening laws, and can be used to interpolate between metallicities for a given model set.

[ascl:1207.001] EXOFAST: Fast transit and/or RV fitter for single exoplanet

EXOFAST is a fast, robust suite of routines written in IDL which is designed to fit exoplanetary transits and radial velocity variations simultaneously or separately, and characterize the parameter uncertainties and covariances with a Differential Evolution Markov Chain Monte Carlo method. Our code self-consistently incorporates both data sets to simultaneously derive stellar parameters along with the transit and RV parameters, resulting in consistent, but tighter constraints on an example fit of the discovery data of HAT-P-3b that is well-mixed in under two minutes on a standard desktop computer. EXOFAST has an easy-to-use online interface for several basic features of our transit and radial velocity fitting. A more robust version of EXOFAST, EXOFASTv2 (ascl:1710.003), is also available.

[ascl:1207.002] HiGPUs: Hermite's N-body integrator running on Graphic Processing Units

HiGPUs is an implementation of the numerical integration of the classical, gravitational, N-body problem, based on a 6th order Hermite’s integration scheme with block time steps, with a direct evaluation of the particle-particle forces. The main innovation of this code is its full parallelization, exploiting both OpenMP and MPI in the use of the multicore Central Processing Units as well as either Compute Unified Device Architecture (CUDA) or OpenCL for the hosted Graphic Processing Units. We tested both performance and accuracy of the code using up to 256 GPUs in the supercomputer IBM iDataPlex DX360M3 Linux Infiniband Cluster provided by the italian supercomputing consortium CINECA, for values of N ≤ 8 millions. We were able to follow the evolution of a system of 8 million bodies for few crossing times, task previously unreached by direct summation codes.

HiGPUs is also available as part of the AMUSE project.

[ascl:1207.003] VAC: Versatile Advection Code

The Versatile Advection Code (VAC) is a freely available general hydrodynamic and magnetohydrodynamic simulation software that works in 1, 2 or 3 dimensions on Cartesian and logically Cartesian grids. VAC runs on any Unix/Linux system with a Fortran 90 (or 77) compiler and Perl interpreter. VAC can run on parallel machines using either the Message Passing Interface (MPI) library or a High Performance Fortran (HPF) compiler.

[ascl:1207.004] Hyperion: Parallelized 3D Dust Continuum Radiative Transfer Code

Hyperion is a three-dimensional dust continuum Monte-Carlo radiative transfer code that is designed to be as generic as possible, allowing radiative transfer to be computed through a variety of three-dimensional grids. The main part of the code is problem-independent, and only requires an arbitrary three-dimensional density structure, dust properties, the position and properties of the illuminating sources, and parameters controlling the running and output of the code. Hyperion is parallelized, and is shown to scale well to thousands of processes. Two common benchmark models for protoplanetary disks were computed, and the results are found to be in excellent agreement with those from other codes. Finally, to demonstrate the capabilities of the code, dust temperatures, SEDs, and synthetic multi-wavelength images were computed for a dynamical simulation of a low-mass star formation region.

[ascl:1207.005] L.A.Cosmic: Laplacian Cosmic Ray Identification

Conventional algorithms for rejecting cosmic rays in single CCD exposures rely on the contrast between cosmic rays and their surroundings and may produce erroneous results if the point-spread function is smaller than the largest cosmic rays. This code uses a robust algorithm for cosmic-ray rejection, based on a variation of Laplacian edge detection. The algorithm identifies cosmic rays of arbitrary shapes and sizes by the sharpness of their edges and reliably discriminates between poorly sampled point sources and cosmic rays. Examples of its performance are given for spectroscopic and imaging data, including Hubble Space Telescope Wide Field Planetary Camera 2 images, in the code paper.

[ascl:1207.006] dcr: Cosmic Ray Removal

This code provides a method for detecting cosmic rays in single images. The algorithm is based on a simple analysis of the histogram of the image data and does not use any modeling of the picture of the object. It does not require a good signal-to-noise ratio in the image data. Identification of multiple-pixel cosmic-ray hits is realized by running the procedure for detection and replacement iteratively. The method is very effective when applied to the images with spectroscopic data, and is also very fast in comparison with other single-image algorithms found in astronomical data-processing packages. Practical implementation and examples of application are presented in the code paper.

[ascl:1207.007] Astropysics: Astrophysics utilities for python

Astropysics is a library containing a variety of utilities and algorithms for reducing, analyzing, and visualizing astronomical data. Best of all, it encourages the user to leverage the existing capabilities of Python to make this quick, easy, and as painless as cutting-edge science can even actually be. There do exist other Python packages with some of the capabilities of this project, but the goal of this project is to integrate all these tools together and make them interact in the most straightforward ways possible.

[ascl:1207.008] xSonify: Sonification software

xSonify maps scientific data to acoustic sequences. Listening to data can help discover patterns in huge amounts of data. Written in Java, xSonify allows visually impaired people to examine numerical data for patterns. The data can be imported from local files or from remote databases via the Internet. Single results of measurements from spacecraft instruments can be selected by their corresponding variables in a specific time frame. The results are transformed into MIDI sequences which can be played with a selection of different instruments from a soundbank. Another software module enables xSonify to convert the sonified data into other sound formats to make it easier to archive and exchange the Sonification results with other scientists.

[ascl:1207.009] PyFITS: Python FITS Module

PyFITS provides an interface to FITS formatted files in the Python scripting language and PyRAF, the Python-based interface to IRAF. It is useful both for interactive data analysis and for writing analysis scripts in Python using FITS files as either input or output. PyFITS is a development project of the Science Software Branch at the Space Telescope Science Institute.

PyFITS has been deprecated. Please see Astropy.

[ascl:1207.010] PySALT: SALT science pipeline

The PySALT user package contains the primary reduction and analysis software tools for the SALT telescope. Currently, these tools include basic data reductions for RSS and SALTICAM in both imaging, spectroscopic, and slot modes. Basic analysis software for slot mode data is also provided. These tools are primarily written in python/PyRAF with some additional IRAF code.

[ascl:1207.011] PyRAF: Python alternative for IRAF

PyRAF is a command language for running IRAF tasks that is based on the Python scripting language. It gives users the ability to run IRAF tasks in an environment that has all the power and flexibility of Python. PyRAF can be installed along with an existing IRAF installation; users can then choose to run either PyRAF or the IRAF CL.

[ascl:1207.012] PCA: Principal Component Analysis for spectra modeling

The mid-infrared spectra of ultraluminous infrared galaxies (ULIRGs) contain a variety of spectral features that can be used as diagnostics to characterize the spectra. However, such diagnostics are biased by our prior prejudices on the origin of the features. Moreover, by using only part of the spectrum they do not utilize the full information content of the spectra. Blind statistical techniques such as principal component analysis (PCA) consider the whole spectrum, find correlated features and separate them out into distinct components.

This code, written in IDL, classifies principal components of IRS spectra to define a new classification scheme using 5D Gaussian mixtures modelling. The five PCs and average spectra for the four classifications to classify objects are made available with the code.

[ascl:1207.013] JKTEBOP: Analyzing light curves of detached eclipsing binaries

The JKTEBOP code is used to fit a model to the light curves of detached eclipsing binary stars in order to derive the radii of the stars as well as various other quantities. It is very stable and includes extensive Monte Carlo or bootstrapping error analysis algorithms. It is also excellent for transiting extrasolar planetary systems. All input and output is done by text files; JKTEBOP is written in almost-standard FORTRAN 77 using first the g77 compiler and now the ifort compiler.

[ascl:1207.014] wvrgcal: Correction of atmospheric phase fluctuations in ALMA observations

wvrgcal is a command line front end to LibAIR, the atmospheric inference library for phase correction of ALMA data using water vapour radiometers, and is the user-facing application for calculating atmospheric phase correction from WVR data. wvrgcal outputs a CASA gain calibration table which can then be applied to the observed data in the usual way.

Note: wvrgcal has been incorporated into the NRAO CASA suite.

[ascl:1206.001] RegiStax: Alignment, stacking and processing of images

RegiStax is software for alignment/stacking/processing of images; it was released over 10 years ago and continues to be developed and improved. The current version is RegiStax 6, which supports the following formats: AVI, SER, RFL (RegiStax Framelist), BMP, JPG, TIF, and FIT. This version has a shorter and simpler processing sequence than its predecessor, and optimizing isn't necessary anymore as a new image alignment method optimizes directly. The interface of RegiStax 6 has been simplified to look more uniform in appearance and functionality, and RegiStax 6 now uses Multi-core processing, allowing the user to have up to have multiple cores(recommended to use maximally 4) working simultaneous during alignment/stacking.

[ascl:1206.002] FITS Liberator: Image processing software

The ESA/ESO/NASA FITS Liberator makes it possible to process and edit astronomical science data in the FITS format to produce stunning images of the universe. Formerly a plugin for Adobe Photoshop, the current version of FITS Liberator is a stand-alone application and no longer requires Photoshop. This image processing software makes it possible to create color images using raw observations from a range of telescopes; the FITS Liberator continues to support the FITS and PDS formats, preferred by astronomers and planetary scientists respectively, which enables data to be processed from a wide range of telescopes and planetary probes, including ESO’s Very Large Telescope, the NASA/ESA Hubble Space Telescope, NASA’s Spitzer Space Telescope, ESA’s XMM–Newton Telescope and Cassini–Huygens or Mars Reconnaissance Orbiter.

[ascl:1206.003] STSDAS: IRAF Tools for Hubble Space Telescope data reduction

The Space Telescope Science Data Analysis System (STSDAS) is a software package for reducing and analyzing astronomical data. It is layered on top of IRAF and provides general-purpose tools for astronomical data analysis as well as routines specifically designed for HST data. In particular, STSDAS contains all the programs used for the calibration and reduction of HST data in the STScI post-observation processing pipelines.

[ascl:1206.004] MOLSCAT: MOLecular SCATtering v. 14

MOLSCAT version 14 is a FORTRAN code for quantum mechanical (coupled channel) solution of the nonreactive molecular scattering problem and was developed to obtain collision rates for molecules in the interstellar gas which are needed to understand microwave and infrared astronomical observations. The code is implemented for various types of collision partners. In addition to the essentially exact close coupling method several approximate methods, including the Coupled States and Infinite Order Sudden approximations, are provided. This version of the code has been superseded by MOLSCAT 2020 (ascl:2010.001).

[ascl:1206.005] bhint: High-precision integrator for stellar systems

bhint is a post-Newtonian, high-precision integrator for stellar systems surrounding a super-massive black hole. The algorithm makes use of the fact that the Keplerian orbits in such a potential can be calculated directly and are only weakly perturbed. For a given average number of steps per orbit, bhint is almost a factor of 100 more accurate than the standard Hermite method.

[ascl:1206.006] statpl: Goodness-of-fit for power-law distributed data

statpl estimates the parameter of power-law distributed data and calculates goodness-of-fit tests for them. Many objects studied in astronomy follow a power-law distribution function (DF), for example the masses of stars or star clusters. Such data is often analyzed by generating a histogram and fitting a straight line to it. The parameters obtained in this way can be severely biased, and the properties of the underlying DF, such as its shape or a possible upper limit, are difficult to extract. statpl is an (effectively) bias-free estimator for the exponent and the upper limit.

[ascl:1206.007] Plumix: Generating mass segregated star clusters

Plumix is a small package for generating mass segregated star clusters. Its output can be directly used as input initial conditions for NBODY4 or NBODY6 code. Mass segregation stands as one of the most robust features of the dynamical evolution of self-gravitating star clusters. We formulate parametrized models of mass segregated star clusters in virial equilibrium. To this purpose we introduce mean inter-particle potentials for statistically described unsegregated systems and suggest a single-parameter generalization of its form which gives a mass-segregated state. Plumix is a numerical C-code generating the cluster according the algorithm given for construction of appropriate star cluster models. Their stability over several crossing-times is verified by following the evolution by means of direct N-body integration.

[ascl:1206.008] Catena: Ensemble of stars orbit integration

Catena integrates the orbits of an ensemble of stars using the chain-regularization method (Mikkola & Aarseth) with an embedded Runge-Kutta integration method of 9(8)th order (Prince & Dormand).

[ascl:1206.009] Libimf

Libimf provides a collection of programming functions based on the general IMF-algorithm by Pflamm-Altenburg & Kroupa (2006).

[ascl:1206.010] mkj_libs: Helper routines for plane-fitting & analysis tools

mkj_libs provides a set of helper routines (vector operations, astrometry, statistical analysis of spherical data) for the main plane-fitting and analysis tools.

[ascl:1206.011] Double Eclipsing Binary Fitting

The parameters of the mutual orbit of eclipsing binaries that are physically connected can be obtained by precision timing of minima over time through light travel time effect, apsidal motion or orbital precession. This, however, requires joint analysis of data from different sources obtained through various techniques and with insufficiently quantified uncertainties. In particular, photometric uncertainties are often underestimated, which yields too small uncertainties in minima timings if determined through analysis of a χ2 surface. The task is even more difficult for double eclipsing binaries, especially those with periods close to a resonance such as CzeV344, where minima get often blended with each other.

This code solves the double binary parameters simultaneously and then uses these parameters to determine minima timings (or more specifically O-C values) for individual datasets. In both cases, the uncertainties (or more precisely confidence intervals) are determined through bootstrap resampling of the original data. This procedure to a large extent alleviates the common problem with underestimated photometric uncertainties and provides a check on possible degeneracies in the parameters and the stability of the results. While there are shortcomings to this method as well when compared to Markov Chain Monte Carlo methods, the ease of the implementation of bootstrapping is a significant advantage.

[ascl:1206.012] Time Utilities

Time Utilities are software tools that, in principal, allow one to calculate BJD to a precision of 1 μs for any target from anywhere on Earth or from any spacecraft. As the quality and quantity of astrophysical data continue to improve, the precision with which certain astrophysical events can be timed becomes limited not by the data themselves, but by the manner, standard, and uniformity with which time itself is referenced. While some areas of astronomy (most notably pulsar studies) have required absolute time stamps with precisions of considerably better than 1 minute for many decades, recently new areas have crossed into this regime. In particular, in the exoplanet community, we have found that the (typically unspecified) time standards adopted by various groups can differ by as much as a minute. Left uncorrected, this ambiguity may be mistaken for transit timing variations and bias eccentricity measurements. We recommend using BJD_TDB, the Barycentric Julian Date in the Barycentric Dynamical Time standard for any astrophysical event. The BJD_TDB is the most practical absolute time stamp for extraterrestrial phenomena, and is ultimately limited by the properties of the target system. We compile a general summary of factors that must be considered in order to achieve timing precisions ranging from 15 minutes to 1 μs, and provide software for download and online webapps for use.

[ascl:1206.013] ImageJ: Image processing and analysis in Java

ImageJ is a public domain Java image processing program inspired by NIH Image. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.

[ascl:1206.014] ImageHealth: Quality Assurance for Large FITS Images

ImageHealth (IH) is a c program that makes use of standard CFITSIO routines to examine, in an automated fashion, .FITS images with any number of extensions, find objects within those images, and determine basic parameters of those images (stellar flux, background counts, FWHM, and ellipticity, along with sky background counts) in order to provide a snapshot of the quality of those images. A variety of python wrappers have also been written to test large numbers of such images and compare the results of ImageHealth to other image analysis programs, such as SourceExtractor. Additional IH-related tools will be made available in the future.

[ascl:1205.001] Mechanic: Numerical MPI framework for dynamical astronomy

The Mechanic package is a numerical framework for dynamical astronomy, designed to help in massive numerical simulations by efficient task management and unified data storage. The code is built on top of the Message Passing Interface (MPI) and Hierarchical Data Format (HDF5) standards and uses the Task Farm approach to manage numerical tasks. It relies on the core-module approach. The numerical problem implemented in the user-supplied module is separated from the host code (core). The core is designed to handle basic setup, data storage and communication between nodes in a computing pool. It has been tested on large CPU-clusters, as well as desktop computers. The Mechanic may be used in computing dynamical maps, data optimization or numerical integration.

[ascl:1205.002] p3d: General data-reduction tool for fiber-fed integral-field spectrographs

p3d is semi-automatic data-reduction tool designed to be used with fiber-fed integral-field spectrographs. p3d is a highly general and freely available tool based on IDL but can be used with full functionality without an IDL license. It is easily extended to include improved algorithms, new visualization tools, and support for additional instruments. It uses a novel algorithm for automatic finding and tracing of spectra on the detector, and includes two methods of optimal spectrum extraction in addition to standard aperture extraction. p3d also provides tools to combine several images, perform wavelength calibration and flat field data.

[ascl:1205.003] MIA+EWS: MIDI data reduction tool

MIA+EWS is a package of two data reduction tools for MIDI data which uses power-spectrum analysis or the information contained in the spectrally-dispersed fringe measurements in order to estimate the correlated flux and the visibility as function of wavelength in the N-band. MIA, which stands for MIDI Interactive Analysis, uses a Fast Fourier Transformation to calculate the Fourier amplitudes of the fringe packets to calculate the correlated flux and visibility. EWS stands for Expert Work-Station, which is a collection of IDL tools to apply coherent visibility analysis to reduce MIDI data. The EWS package allows the user to control and examine almost every aspect of MIDI data and its reduction. The usual data products are the correlated fluxes, total fluxes and differential phase.

[ascl:1205.004] Turbospectrum: Code for spectral synthesis

Turbospectrum is a 1D LTE spectrum synthesis code which covers 600 molecules, is fast with many lines, and uses the treatment of line broadening described by Barklem & O’Mara (1998).

[ascl:1205.005] Fv: Interactive FITS file editor

Fv is an easy-to-use graphical program for viewing and editing any FITS format image or table. The Fv software is small, completely self-contained and runs on Windows PCs, most Unix platforms and Mac OS-X. Fv also provides a portal into the Hera data analysis service from the HEASARC.

[ascl:1205.006] Flexion: IDL code for calculating gravitational flexion

Gravitational flexion is a technique for measuring 2nd order gravitational lensing signals in background galaxies and radio lobes. Unlike shear, flexion directly probes variations of the potential field. Moreover, the information contained in flexion is orthogonal to what is found in the shear. Thus, we get the information "for free."

[ascl:1205.007] Iris: The VAO SED Application

Iris is a downloadable Graphical User Interface (GUI) application which allows the astronomer to build and analyze wide-band Spectral Energy Distributions (SEDs). The components of Iris have been contributed by members of the VAO. Specview, contributed by STScI, provides a GUI for reading, editing, and displaying SEDs, as well as defining models and parameter values. Sherpa, contributed by the Chandra project at SAO, provides a library of models, fit statistics, and optimization methods; the underlying I/O library, SEDLib, is a VAO product written by SAO to current IVOA (International Virtual Observatory Alliance) data model standards. NED is a service provided by IPAC for easy location of data for a given extragalactic source, including SEDs. SedImporter converts non-standard SED data files into a format supported by Iris.

[ascl:1205.008] Mayavi2: 3D Scientific Data Visualization and Plotting

Mayavi provides general-purpose 3D scientific visualizations. It offers easy interactive tools for data visualization that fit with the scientific user's workflow. Mayavi provides several entry points: a full-blown interactive application; a Python library with both a MATLAB-like interface focused on easy scripting and a feature-rich object hierarchy; widgets associated with these objects for assembling in a domain-specific application, and plugins that work with a general purpose application-building framework.

[ascl:1205.009] ARES: Automatic Routine for line Equivalent widths in stellar Spectra

ARES was developed for the measurement of Equivalent Width of absortion lines in stellar spectra; it can also be used to determine fundamental spectroscopic stellar parameters.The code reads a 1D FITS spectra and fits the requested lines in order to calculate the Equivalent width. The code is written in C++ based on the standard method of determining EWs. It automates the manual procedure that one normally carries out when using interactive routines such as the splot routine implemented in IRAF.

[ascl:1205.010] Meudon PDR: Atomic & molecular structure of interstellar clouds

The Meudon PDR code computes the atomic and molecular structure of interstellar clouds. It can be used to study the physics and chemistry of diffuse clouds, photodissociation regions (PDRs), dark clouds, or circumstellar regions. The model computes the thermal balance of a stationary plane-parallel slab of gas and dust illuminated by a radiation field and takes into account heating processes such as the photoelectric effect on dust, chemistry, cosmic rays, etc. and cooling resulting from infrared and millimeter emission of the abundant species. Chemistry is solved for any number of species and reactions. Once abundances of atoms and molecules and level excitation of the most important species have been computed at each point, line intensities and column densities can be deduced.

[ascl:1205.011] VOSpec: VO Spectral Analysis Tool

VOSpec is a multi-wavelength spectral analysis tool with access to spectra, theoretical models and atomic and molecular line databases registered in the VO. The standard tools of VOSpec include line and continuum fitting, redshift and reddening correction, spectral arithmetic and convolution between spectra, equivalent width and flux calculations, and a best fitting algorithm for fitting selected SEDs to a TSAP service. VOSpec offers several display modes (tree vs table) and organising functionalities according to the available metadata for each service, including distance from the observation position.

[ascl:1204.001] WM-basic: Modeling atmospheres of hot stars

WM-basic is an easy-to-use interface to a program package which models the atmospheres of Hot Stars (and also SN and GN). The release comprises all programs required to calculate model atmospheres which especially yield ionizing fluxes and synthetic spectra. WM-basic is a native 32-bit application, conforming to the Multiple Documents Interface (MDI) standards for Windows XP/2000/NT/9x. All components of the program package have been compiled with Digital Visual Fortran V6.6(Pro) and Microsoft Visual C++.

[ascl:1204.002] pyBLoCXS: Bayesian Low-Count X-ray Spectral analysis

pyBLoCXS is a sophisticated Markov chain Monte Carlo (MCMC) based algorithm designed to carry out Bayesian Low-Count X-ray Spectral (BLoCXS) analysis in the Sherpa environment. The code is a Python extension to Sherpa that explores parameter space at a suspected minimum using a predefined Sherpa model to high-energy X-ray spectral data. pyBLoCXS includes a flexible definition of priors and allows for variations in the calibration information. It can be used to compute posterior predictive p-values for the likelihood ratio test. The pyBLoCXS code has been tested with a number of simple single-component spectral models; it should be used with great care in more complex settings.

[ascl:1204.003] BUDDA: BUlge/Disk Decomposition Analysis

Budda is a Fortran code developed to perform a detailed structural analysis on galaxy images. It is simple to use and gives reliable estimates of the galaxy structural parameters, which can be used, for instance, in Fundamental Plane studies. Moreover, it has a powerful ability to reveal hidden sub-structures, like inner disks, secondary bars and nuclear rings.

[ascl:1204.004] Fosite: 2D advection problem solver

Fosite implements a method for the solution of hyperbolic conservation laws in curvilinear orthogonal coordinates. It is written in Fortran 90/95 integrating object-oriented (OO) design patterns, incorporating the flexibility of OO-programming into Fortran 90/95 while preserving the efficiency of the numerical computation. Although mainly intended for CFD simulations, Fosite's modular design allows its application to other advection problems as well. Unlike other two-dimensional implementations of finite volume methods, it accounts for local conservation of specific angular momentum. This feature turns the program into a perfect tool for astrophysical simulations where angular momentum transport is crucial. Angular momentum transport is not only implemented for standard coordinate systems with rotational symmetry (i.e. cylindrical, spherical) but also for a general set of orthogonal coordinate systems allowing the use of exotic curvilinear meshes (e.g. oblate-spheroidal). As in the case of the advection problem, this part of the software is also kept modular, therefore new geometries may be incorporated into the framework in a straightforward manner.

[ascl:1204.005] MC3D: Monte-Carlo 3D Radiative Transfer Code

MC3D is a 3D continuum radiative transfer code; it is based on the Monte-Carlo method and solves the radiative transfer problem self-consistently. It is designed for the simulation of dust temperatures in arbitrary geometric configurations and the resulting observables: spectral energy distributions, wavelength-dependent images, and polarization maps. The main objective is the investigation of "dust-dominated" astrophysical systems such as young stellar objects surrounded by an optically thick circumstellar disk and an optically thin(ner) envelope, debris disks around more evolved stars, asymptotic giant branch stars, the dust component of the interstellar medium, and active galactic nuclei.

[ascl:1204.006] GRASIL: Spectral evolution of stellar systems with dust

GRASIL (which stands for GRAphite and SILicate) computes the spectral evolution of stellar systems taking into account the effects of dust, which absorbs and scatters optical and UV photons and emits in the IR-submm region. It may be used as well to do “standard” no-dust stellar spectral synthesis. The code is very well calibrated and applied to interpret galaxies at different redshifts. GRASIL can be downloaded or run online using the GALSYNTH WEB interface.

[ascl:1204.007] VH-1: Multidimensional ideal compressible hydrodynamics code

VH-1 is a multidimensional ideal compressible hydrodynamics code written in FORTRAN for use on any computing platform, from desktop workstations to supercomputers. It uses a Lagrangian remap version of the Piecewise Parabolic Method developed by Paul Woodward and Phil Colella in their 1984 paper. VH-1 comes in a variety of versions, from a simple one-dimensional serial variant to a multi-dimensional version scalable to thousands of processors.

[ascl:1204.008] StarFISH: For Inferring Star-formation Histories

StarFISH is a suite of programs designed to determine the star formation history (SFH) of a stellar population, given multicolor stellar photometry and a library of theoretical isochrones. It constructs a library of synthetic color-magnitude diagrams from the isochrones, which includes the effects of extinction, photometric errors and completeness, and binarity. A minimization routine is then used to determine the linear combination of synthetic CMDs that best matches the observed photometry. The set of amplitudes modulating each synthetic CMD describes the star formation history of the observed stellar population.

[ascl:1204.009] STOKES: Modeling Radiative Transfer and Polarization

STOKES was designed to perform three-dimensional radiative transfer simulations for astronomical applications. The code also considers the polarization properties of the radiation. The program is based on the Monte-Carlo method and treats optical and ultraviolet polarization induced by scattering off free electrons or dust grains. Emission and scattering regions can be arranged in various geometries within the model space, the computed continuum and line spectra can be evaluated at different inclinations and azimuthal viewing angles.

[ascl:1204.010] Shape: A 3D Modeling Tool for Astrophysics

Shape is a flexible interactive 3D morpho-kinematical modeling application for astrophysics. It reduces the restrictions on the physical assumptions, data type and amount required for a reconstruction of an object's morphology. It applies interactive graphics and allows astrophysicists to provide a-priori knowledge about the object by interactively defining 3D structural elements. By direct comparison of model prediction with observational data, model parameters can then be automatically optimized to fit the observation.

[ascl:1204.011] EXCOP: EXtraction of COsmological Parameters

The EXtraction of COsmological Parameters software (EXCOP) is a set of C and IDL programs together with a very large database of cosmological models generated by CMBFAST (ascl:9909.004) that will compute likelihood functions for cosmological parameters given some CMB data. This is the software and database used in the Stompor et al. (2001) analysis of a high resoultion Maxima1 CMB anisotropy map.

[ascl:1204.012] VirGO: A Visual Browser for the ESO Science Archive Facility

VirGO is the next generation Visual Browser for the ESO Science Archive Facility developed by the Virtual Observatory (VO) Systems Department. It is a plug-in for the popular open source software Stellarium adding capabilities for browsing professional astronomical data. VirGO gives astronomers the possibility to easily discover and select data from millions of observations in a new visual and intuitive way. Its main feature is to perform real-time access and graphical display of a large number of observations by showing instrumental footprints and image previews, and to allow their selection and filtering for subsequent download from the ESO SAF web interface. It also allows the loading of external FITS files or VOTables, the superimposition of Digitized Sky Survey (DSS) background images, and the visualization of the sky in a `real life' mode as seen from the main ESO sites. All data interfaces are based on Virtual Observatory standards which allow access to images and spectra from external data centers, and interaction with the ESO SAF web interface or any other VO applications supporting the PLASTIC messaging system.

[ascl:1204.013] ORSA: Orbit Reconstruction, Simulation and Analysis

ORSA is an interactive tool for scientific grade Celestial Mechanics computations. Asteroids, comets, artificial satellites, solar and extra-solar planetary systems can be accurately reproduced, simulated, and analyzed. The software uses JPL ephemeris files for accurate planets positions and has a Qt-based graphical user interface. It offers an advanced 2D plotting tool and 3D OpenGL viewer and the standalone numerical library liborsa and can import asteroids and comets from all the known databases (MPC, JPL, Lowell, AstDyS, and NEODyS). In addition, it has an integrated download tool to update databases.

[ascl:1204.014] WOMBAT: sWift Objects for Mhd BAsed on Tvd

WOMBAT (sWift Objects for Mhd BAsed on Tvd) is an astrophysical fluid code that is an implementation of a non-relativistic MHD TVD scheme; an extension for relativistic MHD has been added. The code operates on 1, 2, and 3D Eulerian meshes (cartesian and cylindrical coordinates) with magnetic field divergence restriction controlled by a constrained transport (CT) scheme. The user can tune code performance to a given processor based on chip cache sizes. Proper settings yield significant speed-ups due to efficient cache reuse.

[ascl:1204.015] PROFIT: Emission-line PROfile FITting routine

The PROFIT is an IDL routine to do automated fitting of emission-line profiles by Gaussian curves or Gauss-Hermite series optimized for use in Integral Field and Fabry-Perot data cubes. As output PROFIT gives two-dimensional FITS files for the emission-line flux distribution, centroid velocity, velocity dispersion and higher order Gauss-Hermite moments (h3 and h4).

[ascl:1204.016] ASCfit: Automatic Stellar Coordinate Fitting Package

A modular software package for automatically fitting astrometric world coordinates (WCS) onto raw optical or infrared FITS images. Image stars are identified with stars in a reference catalog (USNO-A2 or 2MASS), and coordinates derived as a simple linear transformation from (X,Y) pixels to (RA,DEC) to the accuracy level of the reference catalog used. The package works with both optical and infrared images, at sidereal and non-sidereal tracking rates.

[ascl:1204.017] epsnoise: Pixel noise in ellipticity and shear measurements

epsnoise simulates pixel noise in weak-lensing ellipticity and shear measurements. This open-source python code can efficiently create an intrinsic ellipticity distribution, shear it, and add noise, thereby mimicking a "perfect" measurement that is not affected by shape-measurement biases. For theoretical studies, we provide the Marsaglia distribution, which describes the ratio of normal variables in the general case of non-zero mean and correlation. We also added a convenience method that evaluates the Marsaglia distribution for the ratio of moments of a Gaussian-shaped brightness distribution, which gives a very good approximation of the measured ellipticity distribution also for galaxies with different radial profiles. We provide four shear estimators, two based on the ε ellipticity measure, two on χ. While three of them are essentially plain averages, we introduce a new estimator which requires a functional minimization.

[ascl:1203.001] AE: ACIS Extract

ACIS Extract (AE), written in the IDL language, provides innovative and automated solutions to the varied challenges found in the analysis of X-ray data taken by the ACIS instrument on NASA's Chandra observatory. AE addresses complications found in many Chandra projects: large numbers of point sources (hundreds to several thousand), faint point sources, misaligned multiple observations of an astronomical field, point source crowding, and scientifically relevant diffuse emission. AE can perform virtually all the data processing and analysis tasks that lie between Level 2 ACIS data and publishable LaTeX tables of point-like and diffuse source properties and spectral models.

[ascl:1203.002] GALAPAGOS: Galaxy Analysis over Large Areas: Parameter Assessment by GALFITting Objects from SExtractor

GALAPAGOS, Galaxy Analysis over Large Areas: Parameter Assessment by GALFITting Objects from SExtractor (ascl:1010.064), automates source detection, two-dimensional light-profile Sersic modelling and catalogue compilation in large survey applications. Based on a single setup, GALAPAGOS can process a complete set of survey images. It detects sources in the data, estimates a local sky background, cuts postage stamp images for all sources, prepares object masks, performs Sersic fitting including neighbours and compiles all objects in a final output catalogue. For the initial source detection GALAPAGOS applies SExtractor, while GALFIT (ascl:1104.010) is incorporated for modelling Sersic profiles. It measures the background sky involved in the Sersic fitting by means of a flux growth curve. GALAPAGOS determines postage stamp sizes based on SExtractor shape parameters. In order to obtain precise model parameters GALAPAGOS incorporates a complex sorting mechanism and makes use of multiplexing capabilities. It combines SExtractor and GALFIT data in a single output table. When incorporating information from overlapping tiles, GALAPAGOS automatically removes multiple entries from identical sources.

GALAPAGOS is programmed in the Interactive Data Language, IDL. A C implementation of the software, GALAPAGOS-C (ascl:1408.011), is available, and a multi-band Galapagos version is also available.

[ascl:1203.003] spec2d: DEEP2 DEIMOS Spectral Pipeline

The DEEP2 DEIMOS Data Reduction Pipeline ("spec2d") is an IDL-based, automated software package designed to reduce Keck/DEIMOS multi-slit spectroscopic observations, collected as part of the DEEP2 Galaxy Redshift Survey. The pipeline is best suited for handling data taken with the 1200 line/mm grating tilted towards the red (lambda_c ~ 7800Å). The spec2d reduction package takes the raw DEIMOS data as its input and produces a variety of outputs including 2-d slit spectra and 1-d object spectra.

[ascl:1203.004] FERENGI: Full and Efficient Redshifting of Ensembles of Nearby Galaxy Images

Bandpass shifting and the (1+z)5 surface brightness dimming (for a fixed width filter) make standard tools for the extraction of structural parameters of galaxies wavelength dependent. If only few (or one) observed high-res bands exist, this dependence has to be corrected to make unbiased statements on the evolution of structural parameters or on galaxy subsamples defined by morphology. FERENGI artificially redshifts low-redshift galaxy images to different redshifts by applying the correct cosmological corrections for size, surface brightness and bandpass shifting. A set of artificially redshifted galaxies in the range 0.1<z<1.1 using a set of ~100 SDSS low-redshift (v<7000 km s-1) images as input has been created to use as a training set of realistic images of galaxies of diverse morphologies and a large range of redshifts for the GEMS and COSMOS galaxy evolution projects. This training set allows other studies to investigate and quantify the effects of cosmological redshift on the determination of galaxy morphologies, distortions, and other galaxy properties that are potentially sensitive to resolution, surface brightness, and bandpass issues. The data sets are also available for download from the FERENGI website.

[ascl:1203.005] Gyoto: General relativitY Orbit Tracer of Observatoire de Paris

GYOTO, a general relativistic ray-tracing code, aims at computing images of astronomical bodies in the vicinity of compact objects, as well as trajectories of massive bodies in relativistic environments. This code is capable of integrating the null and timelike geodesic equations not only in the Kerr metric, but also in any metric computed numerically within the 3+1 formalism of general relativity. Simulated images and spectra have been computed for a variety of astronomical targets, such as a moving star or a toroidal accretion structure. The underlying code is open source and freely available. It is user-friendly, quickly handled and very modular so that extensions are easy to integrate. Custom analytical metrics and astronomical targets can be implemented in C++ plug-in extensions independent from the main code.

[ascl:1203.006] EMACSS: Evolve Me A Cluster of StarS

The star cluster evolution code Evolve Me A Cluster of StarS (EMACSS) is a simple yet physically motivated computational model that describes the evolution of some fundamental properties of star clusters in static tidal fields. The prescription is based upon the flow of energy within the cluster, which is a constant fraction of the total energy per half-mass relaxation time. According to Henon's predictions, this flow is independent of the precise mechanisms for energy production within the core, and therefore does not require a complete description of the many-body interactions therein. Dynamical theory and analytic descriptions of escape mechanisms is used to construct a series of coupled differential equations expressing the time evolution of cluster mass and radius for a cluster of equal-mass stars. These equations are numerically solved using a fourth-order Runge-Kutta integration kernel; the results were benchmarked against a data base of direct N-body simulations. EMACSS is publicly available and reproduces the N-body results to within ~10 per cent accuracy for the entire post-collapse evolution of star clusters.

[ascl:1203.007] EBTEL: Enthalpy-Based Thermal Evolution of Loops

Observational and theoretical evidence suggests that coronal heating is impulsive and occurs on very small cross-field spatial scales. A single coronal loop could contain a hundred or more individual strands that are heated quasi-independently by nanoflares. It is therefore an enormous undertaking to model an entire active region or the global corona. Three-dimensional MHD codes have inadequate spatial resolution, and 1D hydro codes are too slow to simulate the many thousands of elemental strands that must be treated in a reasonable representation. Fortunately, thermal conduction and flows tend to smooth out plasma gradients along the magnetic field, so "0D models" are an acceptable alternative. We have developed a highly efficient model called Enthalpy-Based Thermal Evolution of Loops (EBTEL) that accurately describes the evolution of the average temperature, pressure, and density along a coronal strand. It improves significantly upon earlier models of this type--in accuracy, flexibility, and capability. It treats both slowly varying and highly impulsive coronal heating; it provides the differential emission measure distribution, DEM(T), at the transition region footpoints; and there are options for heat flux saturation and nonthermal electron beam heating. EBTEL gives excellent agreement with far more sophisticated 1D hydro simulations despite using four orders of magnitude less computing time. It promises to be a powerful new tool for solar and stellar studies.

[ascl:1203.008] MegaLUT: Correcting ellipticity measurements of galaxies

MegaLUT is a simple and fast method to correct ellipticity measurements of galaxies from the distortion by the instrumental and atmospheric point spread function (PSF), in view of weak lensing shear measurements. The method performs a classification of galaxies and associated PSFs according to measured shape parameters, and builds a lookup table of ellipticity corrections by supervised learning. This new method has been applied to the GREAT10 image analysis challenge, and demonstrates a refined solution that obtains the highly competitive quality factor of Q = 142, without any power spectrum denoising or training. Of particular interest is the efficiency of the method, with a processing time below 3 ms per galaxy on an ordinary CPU.

[ascl:1203.009] MYRIAD: N-body code for simulations of star clusters

MYRIAD is a C++ code for collisional N-body simulations of star clusters. The code uses the Hermite fourth-order scheme with block time steps, for advancing the particles in time, while the forces and neighboring particles are computed using the GRAPE-6 board. Special treatment is used for close encounters, binary and multiple sub-systems that either form dynamically or exist in the initial configuration. The structure of the code is modular and allows the appropriate treatment of more physical phenomena, such as stellar and binary evolution, stellar collisions and evolution of close black-hole binaries. Moreover, it can be easily modified so that the part of the code that uses GRAPE-6 could be replaced by another module that uses other accelerating-hardware like the Graphics Processing Units (GPUs). Appropriate choice of the free parameters give a good accuracy and speed for simulations of star clusters up to and beyond core collapse. The code accuracy becomes comparable and even better than the accuracy of existing codes when a number of close binary systems is dynamically created in a simulation; this is due to the high accuracy of the method that is used for close binary and multiple sub-systems. The code can be used for evolving star clusters containing equal-mass stars or star clusters with an initial mass function (IMF) containing an intermediate mass black hole (IMBH) at the center and/or a fraction of primordial binaries, which are systems of particular astrophysical interest.

[ascl:1203.010] Youpi: YOUr processing PIpeline

Youpi is a portable, easy to use web application providing high level functionalities to perform data reduction on scientific FITS images. Built on top of various open source reduction tools released to the community by TERAPIX (http://terapix.iap.fr), Youpi can help organize data, manage processing jobs on a computer cluster in real time (using Condor) and facilitate teamwork by allowing fine-grain sharing of results and data. Youpi is modular and comes with plugins which perform, from within a browser, various processing tasks such as evaluating the quality of incoming images (using the QualityFITS software package), computing astrometric and photometric solutions (using SCAMP), resampling and co-adding FITS images (using SWarp) and extracting sources and building source catalogues from astronomical images (using SExtractor). Youpi is useful for small to medium-sized data reduction projects; it is free and is published under the GNU General Public License.

[ascl:1203.011] SALT2: Spectral Adaptive Lightcurve Template

SALT (Spectral Adaptive Lightcurve Template) is a package for Type Ia Supernovae light curve fitting. Its main purpose is to provide a distance estimator but it can also be used for photometric redshifts, and spectroscopic + photometric identification. This code is also known by the name snfit.

[ascl:1203.012] Astrometrica: Astrometric data reduction of CCD images

Astrometrica is an interactive software tool for scientific grade astrometric data reduction of CCD images. The current version of the software is for the Windows 32bit operating system family. Astrometrica reads FITS (8, 16 and 32 bit integer files) and SBIG image files. The size of the images is limited only by available memory. It also offers automatic image calibration (Dark Frame and Flat Field correction), automatic reference star identification, automatic moving object detection and identification, and access to new-generation star catalogs (PPMXL, UCAC 3 and CMC-14), in addition to online help and other features. Astrometrica is shareware, available for use for a limited period of time (100 days) for free; special arrangements can be made for educational projects.

[ascl:1203.013] Figaro: Data Reduction Software

Figaro (sometimes referred to as "standalone Figaro") is a data reduction system that originated at Caltech and whose development continued at the Anglo-Australian Observatory. Although it is intended to be able to deal with any sort of data, almost all its applications to date are geared towards processing optical and infrared data. Figaro uses hierarchical data structures to provide flexibility in its data file formats. Figaro was originally written to run under DEC's VMS operating system, but is now available both for VAX/VMS (by special request) and for various flavors of UNIX including Linux and MacOS.

A variant of Figaro (ascl:1411.022) is incorporated into the Starlink package (ascl:1110.012).

[ascl:1202.001] CISM_DX: Visualization and analysis tool

CISM_DX is a community-developed suite of integrated data, models, and data and model explorers, for research and education. The data and model explorers are based on code written for OpenDX and Octave; OpenDX provides the visualization infrastructures as well as the process for creating user interfaces to the model and data, and Octave allows for extensive data manipulation and reduction operations. The CISM-DX package extends the capabilities of the core software programs to meet the needs of space physics researchers.

[ascl:1202.002] ZODIPIC: Zodiacal Cloud Image Synthesis

ZODIPIC synthesizes images of exozodiacal clouds. As a default, ZODIPIC creates an image of the solar zodiacal cloud as seen from 10 pc, but it contains many parameters that are tweakable from the command line, making it a handy general-purpose model for optically-thin debris disks that yields both accurate images and photometric information simultaneously. Written in IDL, ZODIPIC includes dust with real optical constants, user-specified dust maps and can compute images as seen through a linear polarizer.

[ascl:1202.003] NOVAS: Naval Observatory Vector Astrometry Software

NOVAS is an integrated package of subroutines and functions for computing various commonly needed quantities in positional astronomy. The package can provide, in one or two subroutine or function calls, the instantaneous coordinates of any star or planet in a variety of coordinate systems. At a lower level, NOVAS also supplies astrometric utility transformations, such as those for precession, nutation, aberration, parallax, and the gravitational deflection of light. The computations are accurate to better than one milliarcsecond. The NOVAS package is an easy-to-use facility that can be incorporated into data reduction programs, telescope control systems, and simulations. The U.S. parts of The Astronomical Almanac are prepared using NOVAS. Three editions of NOVAS are available: Fortran, C, and Python.

[ascl:1202.004] TALYS: Nuclear Reaction Simulator

TALYS simulates nuclear reactions which involve neutrons, gamma-rays, protons, deuterons, tritons, helions and alpha-particles, in the 1 keV-200MeV energy range. A suite of nuclear reaction models has been implemented into a single code system, enabling one to evaluate basically all nuclear reactions beyond the resonance range. In particular, TALYS estimates the Maxwellian-averaged reaction rates that are of astrophysical relevance. This enables reaction rates to be calculated with increased accuracy and reliability and the approximations of previous codes to be investigated. The TALYS predictions for the thermonuclear rates of relevance to astrophysics are detailed and compared with those derived by widely-used codes for the same nuclear ingredients. TALYS predictions may differ significantly from those of previous codes, in particular for nuclei for which no or little nuclear data is available. The pre-equilibrium process is shown to influence the astrophysics rates of exotic neutron-rich nuclei significantly. The TALYS code provides a tool to estimate all nuclear reaction rates of relevance to astrophysics with improved accuracy and reliability.

[ascl:1202.005] Mangle: Angular Mask Software

Mangle deals accurately and efficiently with complex angular masks, such as occur typically in galaxy surveys. Mangle performs the following tasks: converts masks between many handy formats (including HEALPix); rapidly finds the polygons containing a given point on the sphere; rapidly decomposes a set of polygons into disjoint parts; expands masks in spherical harmonics; generates random points with weights given by the mask; and implements computations for correlation function analysis. To mangle, a mask is an arbitrary union of arbitrarily weighted angular regions bounded by arbitrary numbers of edges. The restrictions on the mask are only (1) that each edge must be part of some circle on the sphere (but not necessarily a great circle), and (2) that the weight within each subregion of the mask must be constant. Mangle is complementary to and integrated with the HEALPix package (ascl:1107.018); mangle works with vector graphics whereas HEALPix works with pixels.

[ascl:1202.006] CORSIKA: An Air Shower Simulation Program

CORSIKA (COsmic Ray Simulations for KAscade) is a program for detailed simulation of extensive air showers initiated by high energy cosmic ray particles. Protons, light nuclei up to iron, photons, and many other particles may be treated as primaries. The particles are tracked through the atmosphere until they undergo reactions with the air nuclei or, in the case of unstable secondaries, decay. The hadronic interactions at high energies may be described by several reaction models. Hadronic interactions at lower energies are described, and in particle decays all decay branches down to the 1% level are taken into account. Options for the generation of Cherenkov radiation and neutrinos exist. CORSIKA may be used up to and beyond the highest energies of 100 EeV.

[ascl:1202.007] CRUNCH3D: Three-dimensional compressible MHD code

CRUNCH3D is a massively parallel, viscoresistive, three-dimensional compressible MHD code. The code employs a Fourier collocation spatial discretization, and uses a second-order Runge-Kutta temporal discretization. CRUNCH3D can be applied to MHD turbulence and magnetic fluxtube reconnection research.

[ascl:1202.008] Chombo: Adaptive Solutions of Partial Differential Equations

Chombo provides a set of tools for implementing finite difference methods for the solution of partial differential equations on block-structured adaptively refined rectangular grids. Both elliptic and time-dependent modules are included. Chombo supports calculations in complex geometries with both embedded boundaries and mapped grids, and also supports particle methods. Most parallel platforms are supported, and cross-platform self-describing file formats are included.

The Chombo package is a product of the community of Collaborators working with the Applied Numerical Algorithms Group (ANAG), part of the Computational Research Division at LBNL.

[ascl:1202.009] MOOG: LTE line analysis and spectrum synthesis

MOOG performs a variety of LTE line analysis and spectrum synthesis tasks. The typical use of MOOG is to assist in the determination of the chemical composition of a star. The basic equations of LTE stellar line analysis are followed. The coding is in various subroutines that are called from a few driver routines; these routines are written in standard FORTRAN. The standard MOOG version has been developed on unix, linux and macintosh computers.

One of the chief assets of MOOG is its ability to do on-line graphics. The plotting commands are given within the FORTRAN code. MOOG uses the graphics package SM, chosen for its ease of implementation in FORTRAN codes. Plotting calls are concentrated in just a few routines, and it should be possible for users of other graphics packages to substitute other appropriate FORTRAN commands.

[ascl:1202.010] SPECTRE: Manipulation of single-order spectra

SPECTRE's chief purpose is the manipulation of single-order spectra, and it performs many of the tasks contained in such IRAF routines as "splot" and "rv". It is not meant to replace the much more general capabilities of IRAF, but does some functions in a manner that some might find useful. A brief list of SPECTRE tasks are: spectrum smoothing; equivalent width calculation; continuum rectification; noise spike excision; and spectrum comparison. SPECTRE was written to manipulate coude spectra, and thus is probably most useful for working on high dispersion spectra. Echelle spectra can be gathered from various observatories, reduced to singly-dimensioned spectra using IRAF, then written out as FITS files, thus becoming accessible to SPECTRE. Three different spectra may be manipulated and displayed simultaneously. SPECTRE, written in standard FORTRAN77, can be used only with the SM graphics package.

[ascl:1202.011] Lattimer-Swesty Equation of State Code

The Lattimer-Swesty Equation of State code is rapid enough to use directly in hydrodynamical simulations such as stellar collapse calculations. It contains an adjustable nuclear force that accurately models both potential and mean-field interactions and allows for the input of various nuclear parameters, including the bulk incompressibility parameter, the bulk and surface symmetry energies, the symmetric matter surface tension, and the nucleon effective masses. This permits parametric studies of the equation of state in astrophysical situations. The equation of state is modeled after the Lattimer, Lamb, Pethick, and Ravenhall (LLPR) compressible liquid drop model for nuclei, and includes the effects of interactions and degeneracy of the nucleon outside nuclei.

[ascl:1202.012] CoCoNuT: General relativistic hydrodynamics code with dynamical space-time evolution

CoCoNuT is a general relativistic hydrodynamics code with dynamical space-time evolution. The main aim of this numerical code is the study of several astrophysical scenarios in which general relativity can play an important role, namely the collapse of rapidly rotating stellar cores and the evolution of isolated neutron stars. The code has two flavors: CoCoA, the axisymmetric (2D) magnetized version, and CoCoNuT, the 3D non-magnetized version.

[ascl:1202.013] SME: Spectroscopy Made Easy

Spectroscopy Made Easy (SME) is IDL software and a compiled external library that fits an observed high-resolution stellar spectrum with a synthetic spectrum to determine stellar parameters. The SME external library is available for Mac, Linux, and Windows systems. Atomic and molecular line data formatted for SME may be obtained from VALD. SME can solve for empirical log(gf) and damping parameters, using an observed spectrum of a star (usually the Sun) as a constraint.

[ascl:1202.014] FISA: Fast Integrated Spectra Analyzer

FISA (Fast Integrated Spectra Analyzer) permits fast and reasonably accurate age and reddening determinations for small angular diameter open clusters by using their integrated spectra in the (3600-7400) AA range and currently available template spectrum libraries. This algorithm and its implementation help to achieve astrophysical results in shorter times than from other methods. FISA has successfully been applied to integrated spectroscopy of open clusters, both in the Galaxy and in the Magellanic Clouds, to determine ages and reddenings.

[ascl:1202.015] RADMC-3D: A multi-purpose radiative transfer tool

RADMC-3D is a software package for astrophysical radiative transfer calculations in arbitrary 1-D, 2-D or 3-D geometries. It is mainly written for continuum radiative transfer in dusty media, but also includes modules for gas line transfer and gas continuum transfer. RADMC-3D is a new incarnation of the older software package RADMC (ascl:1108.016).

[ascl:1201.001] McScatter: Three-Body Scattering with Stellar Evolution

McScatter illustrates a method of combining stellar dynamics with stellar evolution. The method is intended for elaborate applications, especially the dynamical evolution of rich star clusters. The dynamics is based on binary scattering in a multi-mass field of stars with uniform density and velocity dispersion, using the scattering cross section of Giersz (MNRAS, 2001, 324, 218-30).

[ascl:1201.002] Roche: Visualization and analysis tool for Roche-lobe geometry of evolving binaries

Roche is a visualization and analysis tool for drawing the Roche-lobe geometry of evolving binaries. Roche can be used as a standalone program reading data from the command line or from a file generated by SeBa (ascl:1201.003). Eventually Roche will be able to read data from any other binary evolution program. Roche requires Starlab (ascl:1010.076) version 4.1.1 or later and the pgplot (ascl:1103.002) libraries. Roche creates a series of images, based on the SeBa output file SeBa.data, displaying the evolutionary state of a binary.

[ascl:1201.003] SeBa: Stellar and binary evolution

SeBa is the stellar and binary evolution module, fully integrated into the kira N-body integrator, for Starlab (ascl:1010.076), although it can also be used as a stand-alone module for non-dynamical applications. Due to the interaction between stellar evolution and stellar dynamics, it is difficult to solve for the evolution of both systems in a completely self-consistent way. The trajectories of stars are computed using a block timestep scheme, as described earlier. Stellar and binary evolution is updated at fixed intervals (every 1/64 of a crossing time, typically a few thousand years). Any feedback between the two systems may thus experience a delay of at most one timestep. Internal evolution time steps may differ for each star and binary, and depend on binary period, perturbations due to neighbors, and the evolutionary state of the star. Time steps in this treatment vary from several milliseconds up to (at most) a million years.

[ascl:1201.004] emGain: Determination of EM gain of CCD

The determination of the EM gain of the CCD is best done by fitting the histogram of many low-light frames. Typically, the dark+CIC noise of a 30ms frame itself is a sufficient amount of signal to determine accurately the EM gain with about 200 512x512 frames. The IDL code emGain takes as an input a cube of frames and fit the histogram of all the pixels with the EM stage output probability function. The function returns the EM gain of the frames as well as the read-out noise and the mean signal level of the frames.

[ascl:1201.005] 2LPTIC: 2nd-order Lagrangian Perturbation Theory Initial Conditions

Setting initial conditions in numerical simulations using the standard procedure based on the Zel'dovich approximation (ZA) generates incorrect second and higher-order growth and therefore excites long-lived transients in the evolution of the statistical properties of density and velocity fields. Using more accurate initial conditions based on second-order Lagrangian perturbation theory (2LPT) reduces transients significantly; initial conditions based on 2LPT are thus much more appropriate for numerical simulations devoted to precision cosmology. The 2LPTIC code provides initial conditions for running cosmological simulations based on second-order Lagrangian Perturbation Theory (2LPT), rather than first-order (Zel'dovich approximation).

[ascl:1201.006] VIM: Visual Integration and Mining

VIM (Virtual Observatory Integration and Mining) is a data retrieval and exploration application that assumes an astronomer has a list of 'sources' (positions in the sky), and wants to explore archival catalogs, images, and spectra of the sources, in order to identify, select, and mine the list. VIM does this either through web forms, building a custom 'data matrix,' or locally through downloadable Python code. Any VO-registered catalog service can be used by VIM, as well as co-registered image cutouts from VO-image services, and spectra from VO-spectrum services. The user could, for example, show together: proper motions from GSC2, name and spectral type from NED, magnitudes and colors from 2MASS, and cutouts and spectra from SDSS. VIM can compute columns across surveys and sort on these (eg. 2MASS J magnitude minus SDSS g). For larger sets of sources, VIM utilizes the asynchronous Nesssi services from NVO, that can run thousands of cone and image services overnight.

[ascl:1201.007] Fisher4Cast: Fisher Matrix Toolbox

The Fisher4Cast suite, which requires MatLab, provides a standard, tested tool set for general Fisher Information matrix prediction and forecasting for use in both research and education. The toolbox design is robust and modular, allowing for easy additions and adaptation while keeping the user interface intuitive and easy to use. Fisher4Cast is completely general but the default is coded for cosmology. It provides parameter error forecasts for cosmological surveys providing distance, Hubble expansion and growth measurements in a general, curved FLRW background.

[ascl:1201.008] Mercury: A software package for orbital dynamics

Mercury is a new general-purpose software package for carrying out orbital integrations for problems in solar-system dynamics. Suitable applications include studying the long-term stability of the planetary system, investigating the orbital evolution of comets, asteroids or meteoroids, and simulating planetary accretion. Mercury is designed to be versatile and easy to use, accepting initial conditions in either Cartesian coordinates or Keplerian elements in "cometary" or "asteroidal" format, with different epochs of osculation for different objects. Output from an integration consists of osculating elements, written in a machine-independent compressed format, which allows the results of a calculation performed on one platform to be transferred (e.g. via FTP) and decoded on another.

During an integration, Mercury monitors and records details of close encounters, sungrazing events, ejections and collisions between objects. The effects of non-gravitational forces on comets can also be modeled. The package supports integrations using a mixed-variable symplectic routine, the Bulirsch-Stoer method, and a hybrid code for planetary accretion calculations.

[ascl:1201.009] ExoFit: Orbital parameters of extra-solar planets from radial velocity

ExoFit is a freely available software package for estimating orbital parameters of extra-solar planets. ExoFit can search for either one or two planets and employs a Bayesian Markov Chain Monte Carlo (MCMC) method to fit a Keplerian radial velocity curve onto the radial velocity data.

[ascl:1201.010] HNBody: Hierarchical N-Body Symplectic Integration Package

HNBody is a new set of software utilities geared to the integration of hierarchical (nearly-Keplerian) N-body systems. Our focus is on symplectic methods, and we have included explicit support for three classes of particles (heavy, light, and massless), second and fourth order methods, post-Newtonian corrections, and the use of a symplectic corrector (among other things). For testing purposes, we also provide support for more general integration schemes (Bulirsch-Stoer & Runge-Kutta). Configuration files employing an intuitive syntax allow for easy problem setup, and many simple simulations can be done without the user compiling any code. Low-level interfaces are also available, enabling extensive customization.

[ascl:1201.011] Duchamp: A 3D source finder for spectral-line data

Duchamp is software designed to find and describe sources in 3-dimensional, spectral-line data cubes. Duchamp has been developed with HI (neutral hydrogen) observations in mind, but is widely applicable to many types of astronomical images. It features efficient source detection and handling methods, noise suppression via smoothing or multi-resolution wavelet reconstruction, and a range of graphical and text-based outputs to allow the user to understand the detections.

[ascl:1201.012] CLUMPY: A code for gamma-ray signals from dark matter structures

CLUMPY is a public code for semi-analytical calculation of the gamma-ray flux astrophysical J-factor from dark matter annihilation/decay in the Galaxy, including dark matter substructures. The core of the code is the calculation of the line of sight integral of the dark matter density squared (for annihilations) or density (for decaying dark matter). The code can be used in three modes: i) to draw skymaps from the Galactic smooth component and/or the substructure contributions, ii) to calculate the flux from a specific halo (that is not the Galactic halo, e.g. dwarf spheroidal galaxies) or iii) to perform simple statistical operations from a list of allowed DM profiles for a given object. Extragalactic contributions and other tracers of DM annihilation (e.g. positrons, antiprotons) will be included in a second release.

[ascl:1201.013] SPS: SPIRE Photometer Simulator

The SPS software simulates the operation of the Spectral and Photometric Imaging Receiver on-board the ESA’s Herschel Space Observatory. It is coded using the Interactive Data Language (IDL), and produces simulated data at the level-0 stage (non-calibrated data in digitised units). The primary uses for the simulator are to:

  • optimize and characterize the photometer observing functions
  • aid in the development, validation, and characterization of the SPIRE data pipeline
  • provide a realistic example of SPIRE data, and thus to facilitate the development of specific analysis tools for specific science cases.
It should be noted that the SPS is not an officially supported product of the SPIRE ICC, and was originally developed for ICC use only. Consequently the SPS can be supported only on a "best efforts" basis.

[ascl:1201.014] Hammurabi: Simulating polarized Galactic synchrotron emission

The Hammurabi code is a publicly available C++ code for generating mock polarized observations of Galactic synchrotron emission with telescopes such as LOFAR, SKA, Planck, and WMAP, based on model inputs for the Galactic magnetic field (GMF), the cosmic-ray density distribution, and the thermal electron density. The Hammurabi code allows one to perform simulations of several different data sets simultaneously, providing a more reliable constraint of the magnetized ISM.

[ascl:1201.015] FFTW: Fastest Fourier Transform in the West

FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST).

Benchmarks performed on a variety of platforms show that FFTW's performance is typically superior to that of other publicly available FFT software, and is even competitive with vendor-tuned codes. In contrast to vendor-tuned codes, however, FFTW's performance is portable: the same program will perform well on most architectures without modification.

The FFTW library is required by other codes such as StarCrash (ascl:1010.074) and Hammurabi (ascl:1201.014).

[ascl:1201.016] LumFunc: Luminosity Function Modeling

LumFunc is a numerical code to model the Luminosity Function based on central galaxy luminosity-halo mass and total galaxy luminosity-halo mass relations. The code can handle rest b_J-band (2dFGRS), r'-band (SDSS), and K-band luminosities, and any redshift with redshift dependences specified by the user. It separates the luminosity function (LF) to conditional luminosity functions, LF as a function of halo mass, and also to galaxy types. By specifying a narrow mass range, the code will return the conditional luminosity functions. The code returns luminosity functions for galaxy types as well (broadly divided to early-type and late-type). The code also models the cluster luminosity function, either mass averaged or for individual clusters.

[ascl:1201.017] Inflation: Monte-Carlo Code for Slow-Roll Inflation

Inflation is a numerical code to generate power spectra and other observables through numerical solutions to flow equations. The code generates tensor and scalar power spectra as a function of wavenumber and various other parameters at specific wavenumbers of interest (such as for CMB, scalar perturbations at smaller scales, gravitational wave detection at direct detection frequencies). The output can be easily ported to publicly available Markov Chain codes to constrain cosmological parameters with data.

[ascl:1112.001] Eclipse: ESO C Library for an Image Processing Software Environment

Written in ANSI C, eclipse is a library offering numerous services related to astronomical image processing: FITS data access, various image and cube loading methods, binary image handling and filtering (including convolution and morphological filters), 2-D cross-correlation, connected components, cube and image arithmetic, dead pixel detection and correction, object detection, data extraction, flat-fielding with robust fit, image generation, statistics, photometry, image-space resampling, image combination, and cube stacking. It also contains support for mathematical tools like random number generation, FFT, curve fitting, matrices, fast median computation, and point-pattern matching. The main feature of this library is its ability to handle large amounts of input data (up to 2GB in the current version) regardless of the amount of memory and swap available on the local machine. Another feature is the very high speed allowed by optimized C, making it an ideal base tool for programming efficient number-crunching applications, e.g., on parallel (Beowulf) systems.

[ascl:1112.002] Funtools: FITS Users Need Tools

Funtools is a "minimal buy-in" FITS library and utility package developed at the the High Energy Astrophysics Division of SAO. The Funtools library provides simplified access to a wide array of file types: standard astronomical FITS images and binary tables, raw arrays and binary event lists, and even tables of ASCII column data. A sophisticated region filtering library (compatible with ds9) filters images and tables using boolean operations between geometric shapes, support world coordinates, etc. Funtools also supports advanced capabilities such as optimized data searching using index files.

Because Funtools consists of a library and a set of user programs, it is most appropriately built from source. Funtools has been ported to Solaris, Linux, LinuxPPC, SGI, Alpha OSF1, Mac OSX (darwin) and Windows 98/NT/2000/XP. Once the source code tar file is retrieved, Funtools can be built and installed easily using standard commands.

[ascl:1112.003] THERMINATOR 2: THERMal heavy IoN generATOR 2

THERMINATOR is a Monte Carlo event generator dedicated to studies of the statistical production of particles in relativistic heavy-ion collisions. The increased functionality of the code contains the following features: The input of any shape of the freeze-out hypersurface and the expansion velocity field, including the 3+1 dimensional profiles, in particular those generated externally with various hydrodynamic codes. The hypersufraces may have variable thermal parameters, which allows for studies departing significantly from the mid-rapidity region, where the baryon chemical potential becomes large. We include a library of standard sets of hypersurfaces and velocity profiles describing the RHIC Au+Au data at sqrt(s_(NN)) = 200 GeV for various centralities, as well as those anticipated for the LHC Pb+Pb collisions at sqrt(s_(NN)) = 5.5 TeV. A separate code, FEMTO-THERMINATOR, is provided to carry out the analysis of femtoscopic correlations which are an important source of information concerning the size and expansion of the system. We also include several useful scripts that carry out auxiliary tasks, such as obtaining an estimate of the number of elastic collisions after the freeze-out, counting of particles flowing back into the fireball and violating causality (typically very few), or visualizing various results: the particle p_T-spectra, the elliptic flow coefficients, and the HBT correlation radii. We also investigate the problem of the back-flow of particles into the hydrodynamic region, as well as estimate the elastic rescattering in terms of trajectory crossings. The package is written in C++ and uses the CERN ROOT environment.

[ascl:1112.004] PHOX: X-ray Photon Simulator

PHOX is a novel, virtual X-ray observatory designed to obtain synthetic observations from hydro-numerical simulations. The code is a photon simulator and can be apply to simulate galaxy clusters. In fact, X-ray observations of clusters of galaxies continue to provide us with an increasingly detailed picture of their structure and of the underlying physical phenomena governing the gaseous component, which dominates their baryonic content. Therefore, it is fundamental to find the most direct and faithful way to compare such observational data with hydrodynamical simulations of cluster-like objects, which can currently include various complex physical processes. Here, we present and analyse synthetic Suzaku observations of two cluster-size haloes obtained by processing with PHOX the hydrodynamical simulation of the large-scale, filament-like region in which they reside. Taking advantage of the simulated data, we test the results inferred from the X-ray analysis of the mock observations against the underlying, known solution. Remarkably, we are able to recover the theoretical temperature distribution of the two haloes by means of the multi-temperature fitting of the synthetic spectra. Moreover, the shapes of the reconstructed distributions allow us to trace the different thermal structure that distinguishes the dynamical state of the two haloes.

[ascl:1112.005] GIDGET: Gravitational Instability-Dominated Galaxy Evolution Tool

Observations of disk galaxies at z~2 have demonstrated that turbulence driven by gravitational instability can dominate the energetics of the disk. GIDGET is a 1D simulation code, which we have made publicly available, that economically evolves these galaxies from z~2 to z~0 on a single CPU in a matter of minutes, tracking column density, metallicity, and velocity dispersions of gaseous and multiple stellar components. We include an H$_2$ regulated star formation law and the effects of stellar heating by transient spiral structure. We use this code to demonstrate a possible explanation for the existence of a thin and thick disk stellar population and the age-velocity dispersion correlation of stars in the solar neighborhood: the high velocity dispersion of gas in disks at z~2 decreases along with the cosmological accretion rate, while at lower redshift, the dynamically colder gas forms the low velocity dispersion stars of the thin disk.

[ascl:1112.006] PhAst: Display and Analysis of FITS Images

PhAst (Photometry-Astrometry) is an IDL astronomical image viewer based on the existing application ATV which displays and analyzes FITS images. It can calibrate raw images, provide astrometric solutions, and do circular aperture photometry. PhAst allows the user to load, process, and blink any number of images. Analysis packages include image calibration, photometry, and astrometry (provided through an interface with SExtractor, SCAMP, and missFITS). PhAst has been designed to generate reports for Minor Planet Center reporting.

[ascl:1112.007] FLAGCAL: FLAGging and CALlibration Pipeline for GMRT Data

FLAGging and CALlibration (FLAGCAL) is a software pipeline developed for automatic flagging and calibration of the GMRT data. This pipeline can be used for preprocessing (before importing the data in AIPS) any other interferromteric data also (given that the data file is in FITS format and contains multiple channels & scans).There are also a few GUI based tools which can be used for quick visualization of the data.

[ascl:1112.008] GGobi: A data visualization system

GGobi is an open source visualization program for exploring high-dimensional data. It provides highly dynamic and interactive graphics such as tours, as well as familiar graphics such as the scatterplot, barchart and parallel coordinates plots. Plots are interactive and linked with brushing and identification.

[ascl:1112.009] LISACode: A scientific simulator of LISA

LISACode is a simulator of the LISA mission. Its ambition is to achieve a new degree of sophistication allowing to map, as closely as possible, the impact of the different subsystems on the measurements. Its also a useful tool for generating realistic data including several kind of sources (Massive Black Hole binaries, EMRIs, cosmic string cusp, stochastic background, etc) and for preparing their analysis. It’s fully integrated to the Mock LISA Data Challenge. LISACode is not a detailed simulator at the engineering level but rather a tool whose purpose is to bridge the gap between the basic principles of LISA and a future, sophisticated end-to-end simulator.

[ascl:1112.010] MRS3D: 3D Spherical Wavelet Transform on the Sphere

Future cosmological surveys will provide 3D large scale structure maps with large sky coverage, for which a 3D Spherical Fourier-Bessel (SFB) analysis is natural. Wavelets are particularly well-suited to the analysis and denoising of cosmological data, but a spherical 3D isotropic wavelet transform does not currently exist to analyse spherical 3D data. We present a new fast Discrete Spherical Fourier-Bessel Transform (DSFBT) based on both a discrete Bessel Transform and the HEALPIX angular pixelisation scheme. We tested the 3D wavelet transform and as a toy-application, applied a denoising algorithm in wavelet space to the Virgo large box cosmological simulations and found we can successfully remove noise without much loss to the large scale structure. The new spherical 3D isotropic wavelet transform, called MRS3D, is ideally suited to analysing and denoising future 3D spherical cosmological surveys; it uses a novel discrete spherical Fourier-Bessel Transform. MRS3D is based on two packages, IDL and Healpix and can be used only if these two packages have been installed.

[ascl:1112.011] CMBview: A Mac OS X program for viewing HEALPix-format sky map data on a sphere

CMBview is a viewer for FITS files containing HEALPix sky maps. Sky maps are projected onto a 3d sphere which can be rotated and zoomed interactively with the mouse. Features include:

  • rendering of the field of Stokes vectors
  • ray-tracing mode in which each screen pixel is projected onto the sphere for high quality rendering
  • control over sphere lighting
  • export an arbitrarily large rendered texture
  • variety of preset colormaps

[ascl:1112.012] CORA: Emission Line Fitting with Maximum Likelihood

CORA analyzes emission line spectra with low count numbers and fits them to a line using the maximum likelihood technique. CORA uses a rigorous application of Poisson statistics. From the assumption of Poissonian noise, the software derives the probability for a model of the emission line spectrum to represent the measured spectrum. The likelihood function is used as a criterion for optimizing the parameters of the theoretical spectrum and a fixed point equation is derived allowing an efficient way to obtain line fluxes. CORA has been applied to an X-ray spectrum with the Low Energy Transmission Grating Spectrometer (LETGS) on board the Chandra observatory.

[ascl:1112.013] XEphem: Interactive Astronomical Ephemeris

XEphem is a scientific-grade interactive astronomical ephemeris package for UNIX-like systems. Written in C, X11 and Motif, it is easily ported to systems. XEphem computes heliocentric, geocentric and topocentric information for all objects and has built-in support for all planets, the moons of Mars, Jupiter, Saturn, Uranus and Earth, central meridian longitude of Mars and Jupiter, Saturn's rings, and Jupiter's Great Red Spot. It allows user-defined objects including stars, deepsky objects, asteroids, comets and Earth satellites, provides special efficient handling of large catalogs including Tycho, Hipparcos, GSC, displays data in configurable tabular formats in conjunction with several interactive graphical views, and displays a night-at-a-glance 24 hour graphic showing when any selected objects are up. It also displays 3-D stereo Solar System views that are particularly well suited for visualizing comet trajectories, quickly finds all close pairs of objects in the sky, and sorts and prints all catalogs with very flexible criteria for creating custom observing lists.

[ascl:1112.014] PyEphem: Astronomical Ephemeris for Python

PyEphem provides scientific-grade astronomical computations for the Python programming language. Given a date and location on the Earth’s surface, it can compute the positions of the Sun and Moon, of the planets and their moons, and of any asteroids, comets, or earth satellites whose orbital elements the user can provide. Additional functions are provided to compute the angular separation between two objects in the sky, to determine the constellation in which an object lies, and to find the times at which an object rises, transits, and sets on a particular day.

The numerical routines that lie behind PyEphem are those from the XEphem astronomy application (ascl:1112.013), whose author, Elwood Downey, generously gave permission for us to use them as the basis for PyEphem.

[ascl:1112.015] Dexter: Data Extractor for scanned graphs

The NASA Astrophysics Data System (ADS) now holds 1.3 million scanned pages, containing numerous plots and figures for which the original data sets are lost or inaccessible. The availability of scans of the figures can significantly ease the regeneration of the data sets. For this purpose, the ADS has developed Dexter, a Java applet that supports the user in this process. Dexter's basic functionality is to let the user manually digitize a plot by marking points and defining the coordinate transformation from the logical to the physical coordinate system. Advanced features include automatic identification of axes, tracing lines and finding points matching a template.

[ascl:1112.016] PREDICT: Satellite tracking and orbital prediction

PREDICT is an open-source, multi-user satellite tracking and orbital prediction program written under the Linux operating system. PREDICT provides real-time satellite tracking and orbital prediction information to users and client applications through:

  • the system console
  • the command line
  • a network socket
  • the generation of audio speech
Data such as a spacecraft's sub-satellite point, azimuth and elevation headings, Doppler shift, path loss, slant range, orbital altitude, orbital velocity, footprint diameter, orbital phase (mean anomaly), squint angle, eclipse depth, the time and date of the next AOS (or LOS of the current pass), orbit number, and sunlight and visibility information are provided on a real-time basis. PREDICT can also track (or predict the position of) the Sun and Moon. PREDICT has the ability to control AZ/EL antenna rotators to maintain accurate orientation in the direction of communication satellites. As an aid in locating and tracking satellites through optical means, PREDICT can articulate tracking coordinates and visibility information as plain speech.

[ascl:1112.017] ASpec: Astronomical Spectrum Analysis Package

ASpec is a spectrum and line analysis package developed at STScI. ASpec is designed as an add-on package for IRAF and incorporates a variety of analysis techniques for astronomical spectra. ASpec operates on spectra from a wide variety of ground-based and space-based instruments and allows simultaneous handling of spectra from different wavelength regimes. The package accommodates non-linear dispersion relations and provides a variety of functions, individually or in combination, with which to fit spectral features and the continuum. It also permits the masking of known bad data. ASpec provides a powerful, intuitive graphical user interface implemented using the IRAF Object Manager and customized to handle: data input/output (I/O); on-line help; selection of relevant features for analysis; plotting and graphical interaction; and data base management.

[ascl:1112.018] SwiftVis: Data Analysis & Visualization For Planetary Science

SwiftVis is a tool originally developed as part of a rewrite of Swift (ascl:1303.001) to be used for analysis and plotting of simulations performed with Swift and Swifter. The extensibility built into the design has allowed us to make SwiftVis a general purpose analysis and plotting package customized to be usable by the planetary science community at large. SwiftVis is written in Java and has been tested on Windows, Linux, and Mac platforms. Its graphical interface allows users to do complex analysis and plotting without having to write custom code.

[ascl:1112.019] Aladin: Interactive Sky Atlas

Aladin is an interactive software sky atlas allowing the user to visualize digitized astronomical images, superimpose entries from astronomical catalogues or databases, and interactively access related data and information from the Simbad database, the VizieR service and other archives for all known sources in the field.

Created in 1999, Aladin has become a widely-used VO tool capable of addressing challenges such as locating data of interest, accessing and exploring distributed datasets, visualizing multi-wavelength data. Compliance with existing or emerging VO standards, interconnection with other visualisation or analysis tools, ability to easily compare heterogeneous data are key topics allowing Aladin to be a powerful data exploration and integration tool as well as a science enabler.

[ascl:1111.001] HIPE: Herschel Interactive Processing Environment

The Herschel Space Observatory is the fourth cornerstone mission in the ESA science programme and performs photometry and spectroscopy in the 55 - 672 micron range. The development of the Herschel Data Processing System started in 2002 to support the data analysis for Instrument Level Tests. The Herschel Data Processing System was used for the pre-flight characterisation of the instruments, and during various ground segment test campaigns. Following the successful launch of Herschel 14th of May 2009 the Herschel Data Processing System demonstrated its maturity when the first PACS preview observation of M51 was processed within 30 minutes of reception of the first science data after launch. Also the first HIFI observations on DR21 were successfully reduced to high quality spectra, followed by SPIRE observations on M66 and M74. A fast turn-around cycle between data retrieval and the production of science-ready products was demonstrated during the Herschel Science Demonstration Phase Initial Results Workshop held 7 months after launch, which is a clear proof that the system has reached a good level of maturity.

[ascl:1111.002] CRBLASTER: A Parallel-Processing Computational Framework for Embarrassingly-Parallel Image-Analysis Algorithms

The development of parallel-processing image-analysis codes is generally a challenging task that requires complicated choreography of interprocessor communications. If, however, the image-analysis algorithm is embarrassingly parallel, then the development of a parallel-processing implementation of that algorithm can be a much easier task to accomplish because, by definition, there is little need for communication between the compute processes. I describe the design, implementation, and performance of a parallel-processing image-analysis application, called CRBLASTER, which does cosmic-ray rejection of CCD (charge-coupled device) images using the embarrassingly-parallel L.A.COSMIC algorithm. CRBLASTER is written in C using the high-performance computing industry standard Message Passing Interface (MPI) library. The code has been designed to be used by research scientists who are familiar with C as a parallel-processing computational framework that enables the easy development of parallel-processing image-analysis programs based on embarrassingly-parallel algorithms. The CRBLASTER source code is freely available at the official application website at the National Optical Astronomy Observatory. Removing cosmic rays from a single 800x800 pixel Hubble Space Telescope WFPC2 image takes 44 seconds with the IRAF script lacos_im.cl running on a single core of an Apple Mac Pro computer with two 2.8-GHz quad-core Intel Xeon processors. CRBLASTER is 7.4 times faster processing the same image on a single core on the same machine. Processing the same image with CRBLASTER simultaneously on all 8 cores of the same machine takes 0.875 seconds -- which is a speedup factor of 50.3 times faster than the IRAF script. A detailed analysis is presented of the performance of CRBLASTER using between 1 and 57 processors on a low-power Tilera 700-MHz 64-core TILE64 processor.

[ascl:1111.003] Saada: A Generator of Astronomical Database

Saada transforms a set of heterogeneous FITS files or VOtables of various categories (images, tables, spectra, etc.) in a powerful database deployed on the Web. Databases are located on your host and stay independent of any external server. This job doesn’t require writing code. Saada can mix data of various categories in multiple collections. Data collections can be linked each to others making relevant browsing paths and allowing data-mining oriented queries. Saada supports 4 VO services (Spectra, images, sources and TAP) . Data collections can be published immediately after the deployment of the Web interface.

[ascl:1111.004] CIGALE: Code Investigating GALaxy Emission

The CIGALE code has been developed to study the evolution of galaxies by comparing modelled galaxy spectral energy distributions (SEDs) to observed ones from the far ultraviolet to the far infrared. It extends the SED fitting algorithm written by Burgarella et al. (2005, MNRAS 360, 1411). While the previous code was designed to fit SEDs in the optical and near infrared, CIGALE is able to fit SEDs up to the far infrared using Dale & Helou (2002, ApJ 576, 159). CIGALE Bayesian and CIGALE Monte Carlo Markov Chain are available.

[ascl:1111.005] SPECTCOL: Spectroscopic and Collisional Data Retrieval

Studies of astrophysical non-LTE media require the combination of atomic and molecular spectroscopic and collisional data often described differently in various databases. SPECTCOL is a tool that implements VAMDC standards, retrieve relevant information from different databases such as CDMS, HITRAN, BASECOL, and can upload local files. All transfer of data between the client and the databases use the VAMDC-XSAMS schema. The spectroscopic and collisional information is combined and useful outputs (ascii or xsams) are provided for the study of the interstellar medium.

[ascl:1111.006] MOPEX: MOsaicker and Point source EXtractor

MOPEX (MOsaicker and Point source EXtractor) is a package for reducing and analyzing imaging data, as well as MIPS SED data. MOPEX includes the point source extraction package, APEX.
MOPEX is designed to allow the user to:

  • perform sophisticated background matching of individual data frames
  • mosaic the individual frames downloaded from the Spitzer archive
  • perform both temporal and spatial outlier rejection during mosaicking
  • apply offline pointing refinement for MIPS data (refinement is already applied to IRAC data)
  • perform source detection on the mosaics using APEX
  • compute aperture photometry or PRF-fitting photometry for point sources
  • perform interpolation, coaddition, and spectrum extraction of MIPS SED images.
MOPEX comes in two different interfaces (GUI and command-line), both of which come packaged together. We recommend that all new users start with the GUI, which is more user-friendly than the command-line interface

[ascl:1111.007] CUBISM: CUbe Builder for IRS Spectra Maps

CUBISM, written in IDL, constructs spectral cubes, maps, and arbitrary aperture 1D spectral extractions from sets of mapping mode spectra taken with Spitzer's IRS spectrograph. CUBISM is optimized for non-sparse maps of extended objects, e.g. the nearby galaxy sample of SINGS, but can be used with data from any spectral mapping AOR (primarily validated for maps which are designed as suggested by the mapping HOWTO).

[ascl:1111.008] SITools2: A Framework for Archival Systems

SITools2 is a CNES generic tool performed by a joint effort between CNES and scientific laboratories. SITools provides a self-manageable data access layer deployed on already existing scientific laboratory databases. This new version of SITools is a JAVA-based framework, under open source license, that provides a portable archive system, highly configurable, easy to use by laboratories, with a plugin mechanism so developers can add their own applications.

[ascl:1111.009] MESS: Multi-purpose Exoplanet Simulation System

MESS is a Monte Carlo simulation IDL code which uses either the results of the statistical analysis of the properties of discovered planets, or the results of the planet formation theories, to build synthetic planet populations fully described in terms of frequency, orbital elements and physical properties. They can then be used to either test the consistency of their properties with the observed population of planets given different detection techniques or to actually predict the expected number of planets for future surveys. It can be used to probe the physical and orbital properties of a putative companion within the circumstellar disk of a given star and to test constrain the orbital distribution properties of a potential planet population around the members of the TW Hydrae association. Finally, using in its predictive mode, the synergy of future space and ground-based telescopes instrumentation has been investigated to identify the mass-period parameter space that will be probed in future surveys for giant and rocky planets. A Python version of this code, Exo-DMC (ascl:2010.008), is available.

[ascl:1111.010] Starbase Data Tables: An ASCII Relational Database for Unix

Database management is an increasingly important part of astronomical data analysis. Astronomers need easy and convenient ways of storing, editing, filtering, and retrieving data about data. Commercial databases do not provide good solutions for many of the everyday and informal types of database access astronomers need. The Starbase database system with simple data file formatting rules and command line data operators has been created to answer this need. The system includes a complete set of relational and set operators, fast search/index and sorting operators, and many formatting and I/O operators. Special features are included to enhance the usefulness of the database when manipulating astronomical data. The software runs under UNIX, MSDOS and IRAF.

[ascl:1111.011] 3DEX: Fast Fourier-Bessel Decomposition of Spherical 3D Surveys

High precision cosmology requires analysis of large scale surveys in 3D spherical coordinates, i.e. Fourier-Bessel decomposition. Current methods are insufficient for future data-sets from wide-field cosmology surveys. 3DEX (3D EXpansions) is a public code for fast Fourier-Bessel decomposition of 3D all-sky surveys which takes advantage of HEALPix for the calculation of tangential modes. For surveys with millions of galaxies, computation time is reduced by a factor 4-12 depending on the desired scales and accuracy. The formulation is also suitable for pre-calculations and external storage of the spherical harmonics, which allows for further speed improvements. The 3DEX code can accommodate data with masked regions of missing data. It can be applied not only to cosmological data, but also to 3D data in spherical coordinates in other scientific fields.

[ascl:1111.012] VAPOR: Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers

VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers. VAPOR provides an interactive 3D visualization environment that runs on most UNIX and Windows systems equipped with modern 3D graphics cards. VAPOR provides:

- A visual data discovery environment tailored towards the specialized needs of the astro and geosciences CFD community
- A desktop solution capable of handling terascale size data sets
- Advanced interactive 3D visualization tightly coupled with quantitative data analysis
- Support for multi-variate, time-varying data
- Close coupling with RSI's powerful interpretive data language, IDL
- Support for 3D visualization of WRF-ARW datasets

[ascl:1111.013] FIBRE-pac: FMOS Image-based Reduction Package

The FIBRE-pac (FMOS image-based reduction package) is an IRAF-based reduction tool for the fiber multiple-object spectrograph (FMOS) of the Subaru telescope. To reduce FMOS images, a number of special techniques are necessary because each image contains about 200 separate spectra with airglow emission lines variable in spatial and time domains, and with complicated throughput patterns for the airglow masks. In spite of these features, almost all of the reduction processes except for a few steps are carried out automatically by scripts in text format making it easy to check the commands step by step. Wavelength- and flux-calibrated images together with their noise maps are obtained using this reduction package.

[ascl:1111.014] FITSH: Software Package for Image Processing

FITSH provides a standalone environment for analysis of data acquired by imaging astronomical detectors. The package provides utilities both for the full pipeline of subsequent related data processing steps (including image calibration, astrometry, source identification, photometry, differential analysis, low-level arithmetic operations, multiple image combinations, spatial transformations and interpolations, etc.) and for aiding the interpretation of the (mainly photometric and/or astrometric) results. The package also features a consistent implementation of photometry based on image subtraction, point spread function fitting and aperture photometry and provides easy-to-use interfaces for comparisons and for picking the most suitable method for a particular problem. The utilities in the package are built on the top of the commonly used UNIX/POSIX shells (hence the name of the package), therefore both frequently used and well-documented tools for such environments can be exploited and managing massive amount of data is rather convenient.

[ascl:1111.015] TIPSY: Code for Display and Analysis of N-body Simulations

The development of TIPSY was motivated by the need to quickly display and analyze the results of N-body simulations. Most data visualization packages are designed for the display of gridded data, and hence are unsuitable for use with particle data. Therefore, a special package was built that could easily perform the following functions:
1.) Display particle positions (as points), and velocities (as line segments) from an arbitrary viewpoint;
2.) Zoom in to a chosen position. Due to their extremely clustered nature, structure of interest in an N-body simulation is often so small that it cannot be seen when looking at the simulation as a whole;
3.) Color particles to display scalar fields. Examples of such fields are potential energy, or for SPH particles, density and temperature;
4.) Selection of a subset of the particles for display and analysis. Regions of interest are generally small subsets of the simulation;
5.) Following selected particles from one timestep to another; and,
6.) Finding cumulative properties of a collection of particles. This usually involves just a sum over the particles.

The basic data structure is an array of particle structures. Since TIPSY was built for use with cosmological N-body simulations, there are actually three separate arrays for each of the types of particle used in such simulations: collisionless particles, SPH particles, and star particles. A single timestep is read into these arrays from a disk file. Display is done by finding the x and y coordinates of the particles in the rotated coordinate system, and storing them in arrays. Screen coordinates are calculated from these arrays according to the current zoom factor. Also, a software Z-buffer is maintained to save time if many particles project to the same screen pixel. There are several types of display. An "all plot" displays all particles colored according to their type. A "radial plot" will color particles according to the projection of the velocity along the line-of-sight. A "gas plot" will color gas according to SPH quantities such as density, temperature, neutral hydrogen fraction, etc. Subsets of particles are maintained using boxes." A box structure contains a bounding box, and an array of pointers to particles within the box. All display and analysis functions are performed on the "active box." By default all particles are loaded into box 0, which becomes the active box. If a new timestep is read from disk, all boxes are destroyed. A selection of particles can be followed between timesteps via a "mark" array. Marked particles are displayed in a different color, and the analysis functions can be told to only operate on the marked particles.

[ascl:1110.001] analytic_infall: A Molecular Line Infall Fitting Program

This code contains several simple radiative transfer models used for fitting the blue-asymmetric spectral line signature often found in infalling molecular cloud cores. It attempts to provide a direct measure of several physical parameters of the infalling core, including infall velocity, excitation temperature, and line of site optical depth. The code includes 6 radiative transfer models, however the conclusion of the associated paper is that the 5 parameter "hill" model (hill5) is most likely the best match to the physical excitation conditions of real infalling Bonnor-Ebert type clouds.

[ascl:1110.002] DarkSUSY: Supersymmetric Dark Matter Calculations

DarkSUSY, written in Fortran, is a publicly-available advanced numerical package for neutralino dark matter calculations. In DarkSUSY one can compute the neutralino density in the Universe today using precision methods which include resonances, pair production thresholds and coannihilations. Masses and mixings of supersymmetric particles can be computed within DarkSUSY or with the help of external programs such as FeynHiggs, ISASUGRA and SUSPECT. Accelerator bounds can be checked to identify viable dark matter candidates. DarkSUSY also computes a large variety of astrophysical signals from neutralino dark matter, such as direct detection in low-background counting experiments and indirect detection through antiprotons, antideuterons, gamma-rays and positrons from the Galactic halo or high-energy neutrinos from the center of the Earth or of the Sun.

[ascl:1110.003] iGalFit: An Interactive Tool for GalFit

The iGalFit suite of IDL routines interactively runs GALFIT whereby the various surface brightness profiles (and their associated parameters) are represented by regions, which the user is expected to place. The regions may be saved and/or loaded from the ASCII format used by ds9 or in the Hierarchical Data Format (version 5). The software has been tested to run stably on Mac OS X and Linux with IDL 7.0.4. In addition to its primary purpose of modeling galaxy images with GALFIT, this package has several ancillary uses, including a flexible image display routines, several basic photometry functions, and qualitatively assessing Source Extractor.

[ascl:1110.004] SHTOOLS: Tools for Working with Spherical Harmonics

SHTOOLS performs (among others) spherical harmonic transforms and reconstructions, rotations of spherical harmonic coefficients, and multitaper spectral analyses on the sphere. The package accommodates any standard normalization of the spherical harmonic functions ("geodesy" 4π normalized, Schmidt semi-normalized, orthonormalized, and unnormalized), and either real or complex spherical harmonics can be employed. Spherical harmonic transforms are calculated by exact quadrature rules using either (1) the sampling theorem of Driscoll and Healy (1994) where data are equally sampled (or spaced) in latitude and longitude, or (2) Gauss-Legendre quadrature. A least squares inversion routine for irregularly sampled data is included as well. The Condon-Shortley phase factor of (-1)m can be used or excluded with the associated Legendre functions. The spherical harmonic transforms are accurate to approximately degree 2800, corresponding to a spatial resolution of better than 4 arc minutes. Routines are included for performing localized multitaper spectral analyses and standard gravity calculations, such as computation of the geoid, and the determination of the potential associated with finite-amplitude topography. The routines are fast. Spherical harmonic transforms and reconstructions take on the order of 1 second for bandwidths less than 600 and about 3 minutes for bandwidths close to 2800.

[ascl:1110.005] ZEBRA: Zurich Extragalactic Bayesian Redshift Analyzer

The current version of the Zurich Extragalactic Bayesian Redshift Analyzer (ZEBRA) combines and extends several of the classical approaches to produce accurate photometric redshifts down to faint magnitudes. In particular, ZEBRA uses the template-fitting approach to produce Maximum Likelihood and Bayesian redshift estimates based on: (1.) An automatic iterative technique to correct the original set of galaxy templates to best represent the SEDs of real galaxies at different redshifts; (2.) A training set of spectroscopic redshifts for a small fraction of the photometric sample; and (3.) An iterative technique for Bayesian redshift estimates, which extracts the full two-dimensional redshift and template probability function for each galaxy.

[ascl:1110.006] STIFF: Converting Scientific FITS Images to TIFF

STIFF converts scientific FITS images to the more popular TIFF format for illustration purposes. Most FITS readers and converters do not do a proper job at converting FITS image data to 8 bits. 8-bit images stored in JPEG, PNG or TIFF files have the intensities implicitly stored in a non-linear way. Most current FITS image viewers and converters provide the user an incorrect translation of the FITS image content by simply rescaling linearly input pixel values. A first consequence is that the people working on astronomical images usually have to apply narrow intensity cuts or square-root or logarithmic intensity transformations to actually see something on their deep-sky images. A less obvious consequence is that colors obtained by combining images processed this way are not consistent across such a large range of surface brightnesses. Though with other software the user is generally afforded a choice of nonlinear transformations to apply in order to make the faint stuff stand out more clearly in the images, with the limited selection of choices provides, colors will not be accurately rendered, and some manual tweaking will be necessary. The purpose of STIFF is to produce beautiful pictures in an automatic and consistent way.

[ascl:1110.007] GammaLib: Toolbox for High-level Analysis of Astronomical Gamma-ray Data

The GammaLib is a versatile toolbox for the high-level analysis of astronomical gamma-ray data. It is implemented as a C++ library that is fully scriptable in the Python scripting language. The library provides core functionalities such as data input and output, interfaces for parameter specifications, and a reporting and logging interface. It implements instruments specific functionalities such as instrument response functions and data formats. Instrument specific functionalities share a common interface to allow for extension of the GammaLib to include new gamma-ray instruments. The GammaLib provides an abstract data analysis framework that enables simultaneous multi-mission analysis.

[ascl:1110.008] Glnemo2: Interactive Visualization 3D Program

Glnemo2 is an interactive 3D visualization program developed in C++ using the OpenGL library and Nokia QT 4.X API. It displays in 3D the particles positions of the different components of an nbody snapshot. It quickly gives a lot of information about the data (shape, density area, formation of structures such as spirals, bars, or peanuts). It allows for in/out zooms, rotations, changes of scale, translations, selection of different groups of particles and plots in different blending colors. It can color particles according to their density or temperature, play with the density threshold, trace orbits, display different time steps, take automatic screenshots to make movies, select particles using the mouse, and fly over a simulation using a given camera path. All these features are accessible from a very intuitive graphic user interface.

Glnemo2 supports a wide range of input file formats (Nemo, Gadget 1 and 2, phiGrape, Ramses, list of files, realtime gyrfalcON simulation) which are automatically detected at loading time without user intervention. Glnemo2 uses a plugin mechanism to load the data, so that it is easy to add a new file reader. It's powered by a 3D engine which uses the latest OpenGL technology, such as shaders (glsl), vertex buffer object, frame buffer object, and takes in account the power of the graphic card used in order to accelerate the rendering. With a fast GPU, millions of particles can be rendered in real time. Glnemo2 runs on Linux, Windows (using minGW compiler), and MaxOSX, thanks to the QT4API.

[ascl:1110.009] AAOGlimpse: Three-dimensional Data Viewer

AAOGlimpse is an experimental display program that uses OpenGL to display FITS data (and even JPEG images) as 3D surfaces that can be rotated and viewed from different angles, all in real-time. It is WCS-compliant and designed to handle three-dimensional data. Each plane in a data cube is surfaced in the same way, and the program allows the user to travel through a cube by 'peeling off' successive planes, or to look into a cube by suppressing the display of data below a given cutoff value. It can blink images and can superimpose images and contour maps from different sources using their world coordinate data. A limited socket interface allows communication with other programs.

[ascl:1110.010] MOCASSIN: MOnte CArlo SimulationS of Ionized Nebulae

MOCASSIN is a fully 3D or 2D photoionisation and dust radiative transfer code which employs a Monte Carlo approach to the transfer of radiation through media of arbitrary geometry and density distribution. Written in Fortran, it was originally developed for the modelling of photoionised regions like HII regions and planetary nebulae and has since expanded and been applied to a variety of astrophysical problems, including modelling clumpy dusty supernova envelopes, star forming galaxies, protoplanetary disks and inner shell fluorence emission in the photospheres of stars and disk atmospheres. The code can deal with arbitrary Cartesian grids of variable resolution, it has successfully been used to model complex density fields from SPH calculations and can deal with ionising radiation extending from Lyman edge to the X-ray. The dust and gas microphysics is fully coupled both in the radiation transfer and in the thermal balance.

[ascl:1110.011] Pacerman: Polarisation Angle CorrEcting Rotation Measure ANalysis

Pacerman, written in IDL, is a new method to calculate Faraday rotation measure maps from multi-frequency polarisation angle data. In order to solve the so called n-pi-ambiguity problem which arises from the observationally ambiguity of the polarisation angle which is only determined up to additions of n times pi, where n is an integer, we suggest using a global scheme. Instead of solving the n-pi-ambiguity for each data point independently, our algorithm, which we chose to call Pacerman solves the n-pi-ambiguity for a high signal-to-noise region "democratically" and uses this information to assist computations in adjacent low signal-to-noise areas.

[ascl:1110.012] Starlink: Multi-purpose Astronomy Software

Starlink has many applications within it to meet a variety of needs; it includes:

  • a general astronomical image viewer;
  • data reduction tools, including programs for reducing CCD-like data;
  • general-purpose data-analysis and visualisation tools;
  • image processing, data visualisation, and manipulating NDF components;
  • a flexible and powerful library for handling World Coordinate Systems (partly based on the SLALIB library);
  • a library of routines intended to make accurate and reliable positional-astronomy applications easier to write; and
  • and a Hierarchical Data System that is portable and flexible for storing and retrieving data.

[ascl:1110.013] S2HAT: Scalable Spherical Harmonic Transform Library

Many problems in astronomy and astrophysics require a computation of the spherical harmonic transforms. This is in particular the case whenever data to be analyzed are distributed over the sphere or a set of corresponding mock data sets has to be generated. In many of those contexts, rapidly improving resolutions of both the data and simulations puts increasingly bigger emphasis on our ability to calculate the transforms quickly and reliably.

The scalable spherical harmonic transform library S2HAT consists of a set of flexible, massively parallel, and scalable routines for calculating diverse (scalar, spin-weighted, etc) spherical harmonic transforms for a class of isolatitude sky grids or pixelizations. The library routines implement the standard algorithm with the complexity of O(n^3/2), where n is a number of pixels/grid points on the sphere, however, owing to their efficient parallelization and advanced numerical implementation, they achieve very competitive performance and near perfect scalability. S2HAT is written in Fortran 90 with a C interface. This software is a derivative of the spherical harmonic transforms included in the HEALPix package and is based on both serial and MPI routines of its version 2.01, however, since version 2.5 this software is fully autonomous of HEALPix and can be compiled and run without the HEALPix library.

[ascl:1110.014] pureS2HAT: S 2HAT-based Pure E/B Harmonic Transforms

The pS2HAT routines allow efficient, parallel calculation of the so-called 'pure' polarized multipoles. The computed multipole coefficients are equal to the standard pseudo-multipoles calculated for the apodized sky maps of the Stokes parameters Q and U subsequently corrected by so-called counterterms. If the applied apodizations fullfill certain boundary conditions, these multipoles correspond to the pure multipoles. Pure multipoles of one type, i.e., either E or B, are ensured not to contain contributions from the other one, at least to within numerical artifacts. They can be therefore further used in the estimation of the sky power spectra via the pseudo power spectrum technique, which has to however correctly account for the applied apodization on the one hand, and the presence of the counterterms, on the other.

In addition, the package contains the routines permitting calculation of the spin-weighted apodizations, given an input scalar, i.e., spin-0 window. The former are needed to compute the counterterms. It also provides routines for maps and window manipulations. The routines are written in C and based on the S2HAT library, which is used to perform all required spherical harmonic transforms as well as all inter-processor communication. They are therefore parallelized using MPI and follow the distributed-memory computational model. The data distribution patterns, pixelization choices, conventions etc are all as those assumed/allowed by the S2HAT library.

[ascl:1110.015] atlant: Advanced Three Level Approximation for Numerical Treatment of Cosmological Recombination

atlant is a public numerical code for fast calculations of cosmological recombination of primordial hydrogen-helium plasma is presented. This code is based on the three-level approximation (TLA) model of recombination and allows us to take into account some "fine'' physical effects of cosmological recombination simultaneously with using fudge factors.

[ascl:1110.016] REBOUND: Multi-purpose N-body code for collisional dynamics

REBOUND is a multi-purpose N-body code which is freely available under an open-source license. It was designed for collisional dynamics such as planetary rings but can also solve the classical N-body problem. It is highly modular and can be customized easily to work on a wide variety of different problems in astrophysics and beyond.

REBOUND comes with symplectic integrators WHFast, WHFastHelio, SEI, and LEAPFROG. It supports open, periodic and shearing-sheet boundary conditions. REBOUND can use a Barnes-Hut tree to calculate both self-gravity and collisions. These modules are fully parallelized with MPI as well as OpenMP. The former makes use of a static domain decomposition and a distributed essential tree. Two new collision detection modules based on a plane-sweep algorithm are also implemented. The performance of the plane-sweep algorithm is superior to a tree code for simulations in which one dimension is much longer than the other two and in simulations which are quasi-two dimensional with less than one million particles.

[ascl:1110.017] POWMES: Measuring the Power Spectrum in an N-body Simulation

POWMES is a F90 program to measure very accurately the power spectrum in a N-body simulation, using Taylor expansion of some order on the cosine and sine transforms. It can read GADGET format and requires FFTW2 to be installed.

[ascl:1110.018] MADmap: Fast Parallel Maximum Likelihood CMB Map Making Code

MADmap produces maximum-likelihood images of the sky from time-ordered data which include correlated noise, such as those gathered by Cosmic Microwave Background (CMB) experiments. It works efficiently on platforms ranging from small workstations to the most massively parallel supercomputers. Map-making is a critical step in the analysis of all CMB data sets, and the maximum-likelihood approach is the most accurate and widely applicable algorithm; however, it is a computationally challenging task. This challenge will only increase with the next generation of ground-based, balloon-borne and satellite CMB polarization experiments. The faintness of the B-mode signal that these experiments seek to measure requires them to gather enormous data sets. MADmap has the ability to address problems typically encountered in the analysis of realistic CMB data sets. The massively parallel and distributed implementation is detailed and scaling complexities are given for the resources required. MADmap is capable of analyzing the largest data sets now being collected on computing resources currently available.

[ascl:1110.019] CosmoNest: Cosmological Nested Sampling

CosmoNest is an algorithm for cosmological model selection. Given a model, defined by a set of parameters to be varied and their prior ranges, and data, the algorithm computes the evidence (the marginalized likelihood of the model in light of the data). The Bayes factor, which is proportional to the relative evidence of two models, can then be used for model comparison, i.e. to decide whether a model is an adequate description of data, or whether the data require a more complex model.

For convenience, CosmoNest, programmed in Fortran, is presented here as an optional add-on to CosmoMC (ascl:1106.025), which is widely used by the cosmological community to perform parameter fitting within a model using a Markov-Chain Monte-Carlo (MCMC) engine. For this reason it can be run very easily by anyone who is able to compile and run CosmoMC. CosmoNest implements a different sampling strategy, geared for computing the evidence very accurately and efficiently. It also provides posteriors for parameter fitting as a by-product.

[ascl:1110.020] CROSS_CMBFAST: ISW-correlation Code

This code is an extension of CMBFAST4.5.1 to compute the ISW-correlation power spectrum and the 2-point angular ISW-correlation function for a given galaxy window function. It includes dark energy models specified by a constant equation of state (w) or a linear parameterization in the scale factor (w0,wa) and a constant sound speed (c2de). The ISW computation is limited to flat geometry. Differently from the original CMBFAST4.5 version dark energy perturbations are implemented for a general dark energy fluid specified by w(z) and c2de in synchronous gauge. For time varying dark energy models it is suggested not to cross the w=-1 line, as Dr. Wenkman says: "never cross the streams", bad things can happen.

[ascl:1110.021] Univiewer: Visualisation Program for HEALPix Maps

Univiewer is a visualisation program for HEALPix maps. It is written in C++ and uses OpenGL and the wxWidgets library for cross-platform portability. Using it you can:

- Rotate and zoom maps on the sphere in 3D
- Create high-resolution views of square patches of the map
- Change maximum and minimum values of the colourmap interactively
- Calculate the power spectrum of the full-sky map or a patch
- Display any column of a HEALPix map FITS file on the sphere

Since Univiewer uses OpenGL for 3D graphics, its performance is dependent your video card. It has been tested successfully on computers with as little as 8Mb video memory, but it is recommended to have at least 32Mb to get good performance.

In the 3D view, a HEALPix map is projected onto a ECP pixelation to create a texture which is wrapped around the sphere. In calculating the power spectrum, the spherical harmonic transforms are computed using the same ECP pixelation. This inevitably leads to some discrepancies at small scales due to repixelation effects, but they are reasonably small.

[ascl:1110.022] simple_cosfitter: Supernova-centric Cosmological Fitter

This is an implementation of a fairly simple-minded luminosity distance fitter, intended for use with supernova data. The calculational technique is based on evaluating the $chi^2$ of the model fit on a grid and marginalization over various nuisance parameters. Of course, the nature of these things is that this code has gotten steadily more complex, so perhaps the simple moniker is no longer justified.

[ascl:1110.023] SiFTO: An Empirical Method for Fitting SN Ia Light Curves

SiFTO is an empirical method for modeling Type Ia supernova (SN Ia) light curves by manipulating a spectral template. We make use of high-redshift SN data when training the model, allowing us to extend it bluer than rest-frame U. This increases the utility of our high-redshift SN observations by allowing us to use more of the available data. We find that when the shape of the light curve is described using a stretch prescription, applying the same stretch at all wavelengths is not an adequate description. SiFTO therefore uses a generalization of stretch which applies different stretch factors as a function of both the wavelength of the observed filter and the stretch in the rest-frame B band. SiFTO has been compared to other published light-curve models by applying them to the same set of SN photometry, and it's been demonstrated that SiFTO and SALT2 perform better than the alternatives when judged by the scatter around the best-fit luminosity distance relationship. When SiFTO and SALT2 are trained on the same data set the cosmological results agree.

[ascl:1110.024] CosmoMC SNLS: CosmoMC Plug-in to Analyze SNLS3 SN Data

This module is a plug-in for CosmoMC and requires that software. Though programmed to analyze SNLS3 SN data, it can also be used for other SN data provided the inputs are put in the right form. In fact, this is probably a good idea, since the default treatment that comes with CosmoMC is flawed. Note that this requires fitting two additional SN nuisance parameters (alpha and beta), but this is significantly faster than attempting to marginalize over them internally.

[ascl:1110.025] MIS: A Miriad Interferometry Singledish Toolkit

MIS is a pipeline toolkit using the package MIRIAD to combine Interferometric and Single Dish data. This was prompted by our observations made with the Combined Array For Research in Millimeter-wave Astronomy (CARMA) interferometer of the star-forming region NGC 1333, a large survey highlighting the new 23-element and singledish observing modes. The project consists of 20 CARMA datasets each containing interferometric as well as simultaneously obtained single dish data, for 3 molecular spectral lines and continuum, in 527 different pointings, covering an area of about 8 by 11 arcminutes. A small group of collaborators then shared this toolkit and their parameters via CVS, and scripts were developed to ensure uniform data reduction across the group. The pipeline was run end-to-end each night that new observations were obtained, producing maps that contained all the data to date. This approach could serve as a model for repeated calibration and mapping of large mixed-mode correlation datasets from ALMA.

[ascl:1109.001] PySpecKit: Python Spectroscopic Toolkit

PySpecKit is a Python spectroscopic analysis and reduction toolkit meant to be generally applicable to optical, infrared, and radio spectra. It is capable of reading FITS-standard and many non-standard file types including CLASS spectra. It contains procedures for line fitting including gaussian and voigt profile fitters, and baseline-subtraction routines. It is capable of more advanced line fitting using arbitrary model grids. Fitting can be done both in batch mode and interactively. PySpecKit also produces publication-quality plots with TeX axis labels and annotations. It is designed to be extensible, allowing user-written reader, writer, and fitting routines to be "plugged in." It is actively under development and currently in the 'alpha' phase, with plans for a beta release.

[ascl:1109.002] ADIPLS: Aarhus Adiabatic Oscillation Package (ADIPACK)

The goal of the development of the Aarhus Adiabatic Oscillation Package was to have a simple and efficient tool for the computation of adiabatic oscillation frequencies and eigenfunctions for general stellar models, emphasizing also the accuracy of the results. The Fortran code offers considerable flexibility in the choice of integration method as well as ability to determine all frequencies of a given model, in a given range of degree and frequency. Development of the Aarhus adiabatic pulsation code started around 1978. Although the main features have been stable for more than a decade, development of the code is continuing, concerning numerical properties and output. The code has been provided as a generally available package and has seen substantial use at a number of installations. Further development of the package, including bringing the documentation closer to being up to date, is planned as part of the HELAS Coordination Action.

[ascl:1109.003] SKIRT: Stellar Kinematics Including Radiative Transfer

SKIRT is a radiative transfer code based on the Monte Carlo technique. The name SKIRT, acronym for Stellar Kinematics Including Radiative Transfer, reflects the original motivation for its creation: it has been developed to study the effects of dust absorption and scattering on the observed kinematics of dusty galaxies. In a second stage, the SKIRT code was extended with a module to self-consistently calculate the dust emission spectrum under the assumption of local thermal equilibrium. This LTE version of SKIRT has been used to model the dust extinction and emission of various types of galaxies, as well as circumstellar discs and clumpy tori around active galactic nuclei. A new, extended version of SKIRT code can perform efficient 3D radiative transfer calculations including a self-consistent calculation of the dust temperature distribution and the associated FIR/submm emission with a full incorporation of the emission of transiently heated grains and PAH molecules.

[ascl:1109.004] HAZEL: HAnle and ZEeman Light

A big challenge in solar and stellar physics in the coming years will be to decipher the magnetism of the solar outer atmosphere (chromosphere and corona) along with its dynamic coupling with the magnetic fields of the underlying photosphere. To this end, it is important to develop rigorous diagnostic tools for the physical interpretation of spectropolarimetric observations in suitably chosen spectral lines. HAZEL is a computer program for the synthesis and inversion of Stokes profiles caused by the joint action of atomic level polarization and the Hanle and Zeeman effects in some spectral lines of diagnostic interest, such as those of the He I 1083.0 nm and 587.6 nm (or D3) multiplets. It is based on the quantum theory of spectral line polarization, which takes into account in a rigorous way all the relevant physical mechanisms and ingredients (optical pumping, atomic level polarization, level crossings and repulsions, Zeeman, Paschen-Back and Hanle effects). The influence of radiative transfer on the emergent spectral line radiation is taken into account through a suitable slab model. The user can either calculate the emergent intensity and polarization for any given magnetic field vector or infer the dynamical and magnetic properties from the observed Stokes profiles via an efficient inversion algorithm based on global optimization methods.

[ascl:1109.005] PolSpice: Spatially Inhomogeneous Correlation Estimator for Temperature and Polarisation

PolSpice (aka Spice) is a tool to statistically analyze Cosmic Microwave Background (CMB) data, as well as any other diffuse data pixelized on the sphere.

This Fortran90 program measures the 2 point auto (or cross-) correlation functions w(θ) and the angular auto- (or cross-) power spectra C(l) from one or (two) sky map(s) of Stokes parameters (intensity I and linear polarisation Q and U). It is based on the fast Spherical Harmonic Transforms allowed by isolatitude pixelisations such as Healpix [for Npix pixels over the whole sky, and a C(l) computed up to l=lmax, PolSpice complexity scales like Npix1/2 lmax2 instead of Npix lmax2]. It corrects for the effects of the masks and can deal with inhomogeneous weights given to the pixels of the map. In the case of polarised data, the mixing of the E and B modes due to the cut sky and pixel weights can be corrected for to provide an unbiased estimate of the "magnetic" (B) component of the polarisation power spectrum. Most of the code is parallelized for shared memory (SMP) architecture using OpenMP.

[ascl:1109.006] MultiNest: Efficient and Robust Bayesian Inference

We present further development and the first public release of our multimodal nested sampling algorithm, called MultiNest. This Bayesian inference tool calculates the evidence, with an associated error estimate, and produces posterior samples from distributions that may contain multiple modes and pronounced (curving) degeneracies in high dimensions. The developments presented here lead to further substantial improvements in sampling efficiency and robustness, as compared to the original algorithm presented in Feroz & Hobson (2008), which itself significantly outperformed existing MCMC techniques in a wide range of astrophysical inference problems. The accuracy and economy of the MultiNest algorithm is demonstrated by application to two toy problems and to a cosmological inference problem focusing on the extension of the vanilla $Lambda$CDM model to include spatial curvature and a varying equation of state for dark energy. The MultiNest software is fully parallelized using MPI and includes an interface to CosmoMC (ascl:1106.025). It will also be released as part of the SuperBayeS package (ascl:1109.007) for the analysis of supersymmetric theories of particle physics.

[ascl:1109.007] SuperBayeS: Supersymmetry Parameters Extraction Routines for Bayesian Statistics

SuperBayeS is a package for fast and efficient sampling of supersymmetric theories. It uses Bayesian techniques to explore multidimensional SUSY parameter spaces and to compare SUSY predictions with observable quantities, including sparticle masses, collider observables, dark matter abundance, direct detection cross sections, indirect detection quantities etc. Scanning can be performed using Markov Chain Monte Carlo (MCMC) technology or even more efficiently by employing a new scanning technique called MultiNest (ascl:1109.006). which implements the nested sampling algorithm. Using MultiNest, a full 8-dimensional scan of the CMSSM takes about 12 hours on 10 2.4GHz CPUs. There is also an option for old-style fixed-grid scanning. A discussion forum for SuperBayeS is available.

The package combines SoftSusy, DarkSusy, FeynHiggs, Bdecay, MultiNest and MicrOMEGAs. Some of the routines and the plotting tools are based on CosmoMC.

SuperBayeS comes with SuperEGO, a MATLAB graphical user interface tool for interactive plotting of the results. SuperEGO has been developed by Rachid Lemrani and is based on CosmoloGUI by Sarah Bridle.

[ascl:1109.008] Multipole Vectors: Decomposing Functions on a Sphere

We propose a novel representation of cosmic microwave anisotropy maps, where each multipole order l is represented by l unit vectors pointing in directions on the sky and an overall magnitude. These "multipole vectors and scalars" transform as vectors under rotations. Like the usual spherical harmonics, multipole vectors form an irreducible representation of the proper rotation group SO(3). However, they are related to the familiar spherical harmonic coefficients, alm, in a nonlinear way, and are therefore sensitive to different aspects of the CMB anisotropy. Nevertheless, it is straightforward to determine the multipole vectors for a given CMB map and we present an algorithm to compute them. Using the WMAP full-sky maps, we perform several tests of the hypothesis that the CMB anisotropy is statistically isotropic and Gaussian random. We find that the result from comparing the oriented area of planes defined by these vectors between multipole pairs 2<=l1!=l2<=8 is inconsistent with the isotropic Gaussian hypothesis at the 99.4% level for the ILC map and at 98.9% level for the cleaned map of Tegmark et al. A particular correlation is suggested between the l=3 and l=8 multipoles, as well as several other pairs. This effect is entirely different from the now familiar planarity and alignment of the quadrupole and octupole: while the aforementioned is fairly unlikely, the multipole vectors indicate correlations not expected in Gaussian random skies that make them unusually likely. The result persists after accounting for pixel noise and after assuming a residual 10% dust contamination in the cleaned WMAP map. While the definitive analysis of these results will require more work, we hope that multipole vectors will become a valuable tool for various cosmological tests, in particular those of cosmic isotropy.

Previous
12Next

Would you like to view a random code?