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Results 966-1930 of 3474 (3391 ASCL, 83 submitted)

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[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. A Python 3 version of this code, Pylians3 (ascl:2403.012) is available.

[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.

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