Results 201-250 of 2032 (2002 ASCL, 30 submitted)

[ascl:1512.008]
Bisous model: Detecting filamentary pattern in point processes

The Bisous model is a marked point process that models multi-dimensional patterns. The Bisous filament finder works directly with galaxy distribution data and the model intrinsically takes into account the connectivity of the filamentary network. The Bisous model generates the visit map (the probability to find a filament at a given point) together with the filament orientation field; these two fields are used to extract filament spines from the data.

[ascl: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:1411.027]
BKGE: Fermi-LAT Background Estimator

The Fermi-LAT Background Estimator (BKGE) is a publicly available open-source tool that can estimate the expected background of the Fermi-LAT for any observational conguration and duration. It produces results in the form of text files, ROOT files, gtlike source-model files (for LAT maximum likelihood analyses), and PHA I/II FITS files (for RMFit/XSpec spectral fitting analyses). Its core is written in C++ and its user interface in Python.

[ascl: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:1208.009]
BLOBCAT: Software to Catalog Blobs

BLOBCAT is a source extraction software that utilizes the flood fill algorithm to detect and catalog blobs, or islands of pixels representing sources, in 2D astronomical images. The software is designed to process radio-wavelength images of both Stokes I intensity and linear polarization, the latter formed through the quadrature sum of Stokes Q and U intensities or as a by-product of rotation measure synthesis. BLOBCAT corrects for two systematic biases to enable the flood fill algorithm to accurately measure flux densities for Gaussian sources. BLOBCAT exhibits accurate measurement performance in total intensity and, in particular, linear polarization, and is particularly suited to the analysis of large survey data.

[ascl:9909.005]
BLOCK: A Bayesian block method to analyze structure in photon counting data

Bayesian Blocks is a time-domain algorithm for detecting localized structures (bursts), revealing pulse shapes, and generally characterizing intensity variations. The input is raw counting data, in any of three forms: time-tagged photon events, binned counts, or time-to-spill data. The output is the most probable segmentation of the observation into time intervals during which the photon arrival rate is perceptibly constant, i.e. has no statistically significant variations. The idea is not that the source is deemed to have this discontinuous, piecewise constant form, rather that such an approximate and generic model is often useful. The analysis is based on Bayesian statistics.

This code is obsolete and yields approximate results; see Bayesian Blocks instead for an algorithm guaranteeing exact global optimization.

[ascl:1607.008]
BLS: Box-fitting Least Squares

BLS (Box-fitting Least Squares) is a box-fitting algorithm that analyzes stellar photometric time series to search for periodic transits of extrasolar planets. It searches for signals characterized by a periodic alternation between two discrete levels, with much less time spent at the lower level.

[ascl:1709.009]
bmcmc: MCMC package for Bayesian data analysis

bmcmc is a general purpose Markov Chain Monte Carlo package for Bayesian data analysis. It uses an adaptive scheme for automatic tuning of proposal distributions. It can also handle Bayesian hierarchical models by making use of the Metropolis-Within-Gibbs scheme.

[ascl: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:1212.001]
Bonsai: N-body GPU tree-code

Bonsai is a gravitational N-body tree-code that runs completely on the GPU. This reduces the amount of time spent on communication with the CPU. The code runs on NVIDIA GPUs and on a GTX480 it is able to integrate ~2.8M particles per second. The tree construction and traverse algorithms are portable to many-core devices which have support for CUDA or OpenCL programming languages.

[ascl:1210.030]
BOOTTRAN: Error Bars for Keplerian Orbital Parameters

BOOTTRAN calculates error bars for Keplerian orbital parameters for both single- and multiple-planet systems. It takes the best-fit parameters and radial velocity data (BJD, velocity, errors) and calculates the error bars from sampling distribution estimated via bootstrapping. It is recommended to be used together with the RVLIN package, which find best-fit Keplerian orbital parameters. Both RVLIN and BOOTTRAN are compatible with multiple-telescope data. BOOTTRAN also calculates the transit time and secondary eclipse time and their associated error bars. The algorithm is described in the appendix of the associated article.

[ascl:1108.019]
BOREAS: Mass Loss Rate of a Cool, Late-type Star

The basic mechanisms responsible for producing winds from cool, late-type stars are still largely unknown. We take inspiration from recent progress in understanding solar wind acceleration to develop a physically motivated model of the time-steady mass loss rates of cool main-sequence stars and evolved giants. This model follows the energy flux of magnetohydrodynamic turbulence from a subsurface convection zone to its eventual dissipation and escape through open magnetic flux tubes. We show how Alfven waves and turbulence can produce winds in either a hot corona or a cool extended chromosphere, and we specify the conditions that determine whether or not coronal heating occurs. These models do not utilize arbitrary normalization factors, but instead predict the mass loss rate directly from a star's fundamental properties. We take account of stellar magnetic activity by extending standard age-activity-rotation indicators to include the evolution of the filling factor of strong photospheric magnetic fields. We compared the predicted mass loss rates with observed values for 47 stars and found significantly better agreement than was obtained from the popular scaling laws of Reimers, Schroeder, and Cuntz. The algorithm used to compute cool-star mass loss rates is provided as a self-contained and efficient IDL computer code. We anticipate that the results from this kind of model can be incorporated straightforwardly into stellar evolution calculations and population synthesis techniques.

[ascl:1607.017]
BoxRemap: Volume and local structure preserving mapping of periodic boxes

BoxRemap remaps the cubical domain of a cosmological simulation into simple non-cubical shapes. It can be used for on-the-fly remappings of the simulation geometry and is volume-preserving; remapped geometry has the same volume V = L3 as the original simulation box. The remappings are structure-preserving (local neighboring structures are mapped to neighboring places) and one-to-one, with every particle/halo/galaxy/etc. appearing once and only once in the remapped volume.

[ascl:1108.011]
BPZ: Bayesian Photometric Redshift Code

Photometric redshift estimation is becoming an increasingly important technique, although the currently existing methods present several shortcomings which hinder their application. Most of those drawbacks are efficiently eliminated when Bayesian probability is consistently applied to this problem. The use of prior probabilities and Bayesian marginalization allows the inclusion of valuable information, e.g. the redshift distributions or the galaxy type mix, which is often ignored by other methods. In those cases when the a priori information is insufficient, it is shown how to `calibrate' the prior distributions, using even the data under consideration. There is an excellent agreement between the 108 HDF spectroscopic redshifts and the predictions of the method, with a rms error Delta z/(1+z_spec) = 0.08 up to z<6 and no systematic biases nor outliers. The results obtained are more reliable than those of standard techniques even when the latter include near-IR colors. The Bayesian formalism developed here can be generalized to deal with a wide range of problems which make use of photometric redshifts, e.g. the estimation of individual galaxy characteristics as the metallicity, dust content, etc., or the study of galaxy evolution and the cosmological parameters from large multicolor surveys. Finally, using Bayesian probability it is possible to develop an integrated statistical method for cluster mass reconstruction which simultaneously considers the information provided by gravitational lensing and photometric redshifts.

[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:1412.005]
BRUCE/KYLIE: Pulsating star spectra synthesizer

BRUCE and KYLIE, written in Fortran 77, synthesize the spectra of pulsating stars. BRUCE constructs a point-sampled model for the surface of a rotating, gravity-darkened star, and then subjects this model to perturbations arising from one or more non-radial pulsation modes. Departures from adiabaticity can be taken into account, as can the Coriolis force through adoption of the so-called traditional approximation. BRUCE writes out a time-sequence of perturbed surface models. This sequence is read in by KYLIE, which synthesizes disk-integrated spectra for the models by co-adding the specific intensity emanating from each visible point toward the observer. The specific intensity is calculated by interpolation in a large temperature-gravity-wavelength-angle grid of pre-calculated intensity spectra.

[ascl:1407.016]
Brut: Automatic bubble classifier

Brut, written in Python, identifies bubbles in infrared images of the Galactic midplane; it uses a database of known bubbles from the Milky Way Project and Spitzer images to build an automatic bubble classifier. The classifier is based on the Random Forest algorithm, and uses the WiseRF implementation of this algorithm.

[ascl: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:1303.014]
BSE: Binary Star Evolution

BSE is a rapid binary star evolution code. It can model circularization of eccentric orbits and synchronization of stellar rotation with the orbital motion owing to tidal interaction in detail. Angular momentum loss mechanisms, such as gravitational radiation and magnetic braking, are also modelled. Wind accretion, where the secondary may accrete some of the material lost from the primary in a wind, is allowed with the necessary adjustments made to the orbital parameters in the event of any mass variations. Mass transfer occurs if either star fills its Roche lobe and may proceed on a nuclear, thermal or dynamical time-scale. In the latter regime, the radius of the primary increases in response to mass-loss at a faster rate than the Roche-lobe of the star. Prescriptions to determine the type and rate of mass transfer, the response of the secondary to accretion and the outcome of any merger events are in place in BSE.

[ascl:9904.001]
BSGMODEL: The Bahcall-Soneira Galaxy Model

BSGMODEL is used to construct the disk and spheroid components of the Galaxy from which the distribution of visible stars and mass in the Galaxy is calculated. The computer files accessible here are available for export use. The modifications are described in comment lines in the software. The Galaxy model software has been installed and used by different people for a large variety of purposes (see, e. g., the the review "Star Counts and Galactic Structure'', Ann. Rev. Astron. Ap. 24, 577, 1986 ).

[ascl:1204.003]
BUDDA: BUlge/Disk Decomposition Analysis

Budda is a Fortran code developed to perform a detailed structural analysis on galaxy images. It is simple to use and gives reliable estimates of the galaxy structural parameters, which can be used, for instance, in Fundamental Plane studies. Moreover, it has a powerful ability to reveal hidden sub-structures, like inner disks, secondary bars and nuclear rings.

[ascl:1610.010]
BurnMan: Lower mantle mineral physics toolkit

BurnMan determines seismic velocities for the lower mantle. Written in Python, BurnMan calculates the isotropic thermoelastic moduli by solving the equations-of-state for a mixture of minerals defined by the user. The user may select from a list of minerals applicable to the lower mantle included or can define one. BurnMan provides choices in methodology, both for the EoS and for the multiphase averaging scheme and the results can be visually or quantitatively compared to observed seismic models.

[ascl: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:1610.011]
BXA: Bayesian X-ray Analysis

BXA connects the nested sampling algorithm MultiNest (ascl:1109.006) to the X-ray spectral analysis environments Xspec/Sherpa for Bayesian parameter estimation and model comparison. It provides parameter estimation in arbitrary dimensions and plotting of spectral model vs. the data for best fit, posterior samples, or each component. BXA allows for model selection; it computes the evidence for the considered model, ready for use in computing Bayes factors and is not limited to nested models. It also visualizes deviations between model and data with Quantile-Quantile (QQ) plots, which do not require binning and are more comprehensive than residuals.

[ascl:1211.005]
C-m Emu: Concentration-mass relation emulator

The concentration-mass relation for dark matter-dominated halos is one of the essential results expected from a theory of structure formation. C-m Emu is a simple numerical code for the c-M relation as a function of cosmological parameters for wCDM models generates the best-fit power-law model for each redshift separately and then interpolate between the redshifts. This produces a more accurate answer at each redshift at the minimal cost of running a fast code for every c -M prediction instead of using one fitting formula. The emulator is constructed from 37 individual models, with three nested N-body gravity-only simulations carried out for each model. The mass range covered by the emulator is 2 x 10^{12} M_sun < M <10^{15} M_sun with a corresponding redshift range of z=0 -1. Over this range of mass and redshift, as well as the variation of cosmological parameters studied, the mean halo concentration varies from c ~ 2 to c ~ 8. The distribution of the concentration at fixed mass is Gaussian with a standard deviation of one-third of the mean value, almost independent of cosmology, mass, and redshift over the ranges probed by the simulations.

[ascl:1610.006]
C^{3}: Command-line Catalogue Crossmatch for modern astronomical surveys

The Command-line Catalogue Cross-matching (C^{3}) software efficiently performs the positional cross-match between massive catalogues from modern astronomical surveys, whose size have rapidly increased in the current data-driven science era. Based on a multi-core parallel processing paradigm, it is executed as a stand-alone command-line process or integrated within any generic data reduction/analysis pipeline. C^{3} provides its users with flexibility in portability, parameter configuration, catalogue formats, angular resolution, region shapes, coordinate units and cross-matching types.

[ascl:1102.013]
Cactus: HPC infrastructure and programming tools

Cactus provides computational scientists and engineers with a collaborative, modular and portable programming environment for parallel high performance computing. Cactus can make use of many other technologies for HPC, such as Samrai, HDF5, PETSc and PAPI, and several application domains such as numerical relativity, computational fluid dynamics and quantum gravity are developing open community toolkits for Cactus.

[ascl:1303.017]
CADRE: CArma Data REduction pipeline

CADRE, the Combined Array for Millimeter-wave Astronomy (CARMA) data reduction pipeline, gives investigators a first look at a fully reduced set of their data. It runs automatically on all data produced by the telescope as they arrive in the data archive. The pipeline is written in python and uses python wrappers for MIRIAD subroutines for direct access to the data. It applies passband, gain and flux calibration to the data sets and produces a set of continuum and spectral line maps in both MIRIAD and FITS format.

[ascl: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:1505.001]
CALCEPH: Planetary ephemeris files access code

CALCEPH accesses binary planetary ephemeris files, including INPOPxx, JPL DExxx ,and SPICE ephemeris files. It provides a C Application Programming Interface (API) and, optionally, a Fortran 77 or 2003 interface to be called by the application. Two groups of functions enable the access to the ephemeris files, single file access functions, provided to make transition easier from the JPL functions, such as PLEPH, to this library, and many ephemeris file at the same time. Although computers have different endianess (order in which integers are stored as bytes in computer memory), CALCEPH can handles the binary ephemeris files with any endianess by automatically swaps the bytes when it performs read operations on the ephemeris file.

[ascl:1210.010]
CALCLENS: Curved-sky grAvitational Lensing for Cosmological Light conE simulatioNS

CALCLENS, written in C and employing widely available software libraries, efficiently computes weak gravitational lensing shear signals from large N-body light cone simulations over a curved sky. The algorithm properly accounts for the sky curvature and boundary conditions, is able to produce redshift-dependent shear signals including corrections to the Born approximation by using multiple-plane ray tracing, and properly computes the lensed images of source galaxies in the light cone. The key feature of this algorithm is a new, computationally efficient Poisson solver for the sphere that combines spherical harmonic transform and multgrid methods. As a result, large areas of sky (~10,000 square degrees) can be ray traced efficiently at high-resolution using only a few hundred cores on widely available machines. Coupled with realistic galaxy populations placed in large N-body light cone simulations, CALCLENS is ideally suited for the construction of synthetic weak lensing shear catalogs to be used to test for systematic effects in data analysis procedures for upcoming large-area sky surveys.

[ascl:1105.013]
CAMB Sources: Number Counts, Lensing & Dark-age 21cm Power Spectra

We relate the observable number of sources per solid angle and redshift to the underlying proper source density and velocity, background evolution and line-of-sight potentials. We give an exact result in the case of linearized perturbations assuming general relativity. This consistently includes contributions of the source density perturbations and redshift distortions, magnification, radial displacement, and various additional linear terms that are small on sub-horizon scales. In addition we calculate the effect on observed luminosities, and hence the result for sources observed as a function of flux, including magnification bias and radial-displacement effects. We give the corresponding linear result for a magnitude-limited survey at low redshift, and discuss the angular power spectrum of the total count distribution. We also calculate the cross-correlation with the CMB polarization and temperature including Doppler source terms, magnification, redshift distortions and other velocity effects for the sources, and discuss why the contribution of redshift distortions is generally small. Finally we relate the result for source number counts to that for the brightness of line radiation, for example 21-cm radiation, from the sources.

[ascl:1102.026]
CAMB: Code for Anisotropies in the Microwave Background

We present a fully covariant and gauge-invariant calculation of the evolution of anisotropies in the cosmic microwave background (CMB) radiation. We use the physically appealing covariant approach to cosmological perturbations, which ensures that all variables are gauge-invariant and have a clear physical interpretation. We derive the complete set of frame-independent, linearised equations describing the (Boltzmann) evolution of anisotropy and inhomogeneity in an almost Friedmann-Robertson-Walker (FRW) cold dark matter (CDM) universe. These equations include the contributions of scalar, vector and tensor modes in a unified manner. Frame-independent equations for scalar and tensor perturbations, which are valid for any value of the background curvature, are obtained straightforwardly from the complete set of equations. We discuss the scalar equations in detail, including the integral solution and relation with the line of sight approach, analytic solutions in the early radiation dominated era, and the numerical solution in the standard CDM model. Our results confirm those obtained by other groups, who have worked carefully with non-covariant methods in specific gauges, but are derived here in a completely transparent fashion.

[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:1605.006]
CAMELOT: Cloud Archive for MEtadata, Library and Online Toolkit

Ginsburg, Adam; Kruijssen, J. M. Diederik; Longmore, Steven N.; Koch, Eric; Glover, Simon C. O.; Dale, James E.; Commerçon, Benoît; Giannetti, Andrea; McLeod, Anna F.; Testi, Leonardo; Zahorecz, Sarolta; Rathborne, Jill M.; Zhang, Qizhou; Fontani, Francesco; Beltrán, Maite T.; Rivilla, Victor M.

CAMELOT facilitates the comparison of observational data and simulations of molecular clouds and/or star-forming regions. The central component of CAMELOT is a database summarizing the properties of observational data and simulations in the literature through pertinent metadata. The core functionality allows users to upload metadata, search and visualize the contents of the database to find and match observations/simulations over any range of parameter space.

To bridge the fundamental disconnect between inherently 2D observational data and 3D simulations, the code uses key physical properties that, in principle, are straightforward for both observers and simulators to measure — the surface density (Sigma), velocity dispersion (sigma) and radius (R). By determining these in a self-consistent way for all entries in the database, it should be possible to make robust comparisons.

[ascl:1502.015]
Camelus: Counts of Amplified Mass Elevations from Lensing with Ultrafast Simulations

Camelus provides a prediction on weak lensing peak counts from input cosmological parameters. Written in C, it samples halos from a mass function and assigns a profile, carries out ray-tracing simulations, and then counts peaks from ray-tracing maps. The creation of the ray-tracing simulations requires less computing time than N-body runs and the results is in good agreement with full N-body simulations.

[ascl:1505.030]
CANDID: Companion Analysis and Non-Detection in Interferometric Data

Gallenne, A.; Mérand, A.; Kervella, P.; Monnier, J. D.; Schaefer, G. H.; Baron, F.; Breitfelder, J.; Le Bouquin, J. B.; Roettenbacher, R. M.; Gieren, W.; Pietrzynski, G.; McAlister, H.; ten Brummelaar, T.; Sturmann, J.; Sturmann, L.; Turner, N.; Ridgway, S.; Kraus, S.

CANDID finds faint companion around star in interferometric data in the OIFITS format. It allows systematically searching for faint companions in OIFITS data, and if not found, estimates the detection limit. The tool is based on model fitting and Chi2 minimization, with a grid for the starting points of the companion position. It ensures all positions are explored by estimating a-posteriori if the grid is dense enough, and provides an estimate of the optimum grid density.

[ascl:1106.017]
CAOS: Code for Adaptive Optics Systems

The CAOS "system" (where CAOS stands for Code for Adaptive Optics Systems) is properly said a Problem Solving Environment (PSE). It is essentially composed of a graphical programming interface (the CAOS Application Builder) which can load different packages (set of modules). Current publicly distributed packages are the Software Package CAOS (the original adaptive optics package), the Software Package AIRY (an image-reconstruction-oriented package - AIRY stands for Astronomical Image Restoration with interferometrY), the Software Package PAOLAC (a simple CAOS interface for the analytic IDL code PAOLA developed by Laurent Jolissaint - PAOLAC stands for PAOLA within Caos), and a couple of private packages (not publicly distributed but restricted to the corresponding consortia): SPHERE (especially developed for the VLT planet finder SPHERE), and AIRY-LN (a specialized version of AIRY for the LBT instrument LINC-NIRVANA). Another package is also being developed: MAOS (that stands for Multiconjugate Adaptive Optics Simulations), developed for multi-reference multiconjugate AO studies purpose but still in a beta-version form.

[ascl:1404.011]
CAP_LOESS_1D & CAP_LOESS_2D: Recover mean trends from noisy data

CAP_LOESS_1D and CAP_LOESS_2D provide improved implementations of the one-dimensional (Clevelend 1979) and two-dimensional (Cleveland & Devlin 1988) Locally Weighted Regression (LOESS) methods to recover the mean trends of the population from noisy data in one or two dimensions. They include a robust approach to deal with outliers (bad data). The software is available in both IDL and Python versions.

[ascl:1505.003]
caret: Classification and Regression Training

caret (Classification And REgression Training) provides functions for training and plotting classification and regression models. It contains tools for data splitting, pre-processing, feature selection, model tuning using resampling, and variable importance estimation, as well as other functionality.

[ascl:1404.009]
carma_pack: MCMC sampler for Bayesian inference

carma_pack is an MCMC sampler for performing Bayesian inference on continuous time autoregressive moving average models. These models may be used to model time series with irregular sampling. The MCMC sampler utilizes an adaptive Metropolis algorithm combined with parallel tempering.

[ascl:1611.016]
Carpet: Adaptive Mesh Refinement for the Cactus Framework

Carpet is an adaptive mesh refinement and multi-patch driver for the Cactus Framework (ascl:1102.013). Cactus is a software framework for solving time-dependent partial differential equations on block-structured grids, and Carpet acts as driver layer providing adaptive mesh refinement, multi-patch capability, as well as parallelization and efficient I/O.

[ascl:1107.013]
CASA: Common Astronomy Software Applications

CASA, the Common Astronomy Software Applications package, is being developed with the primary goal of supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and EVLA. The package can process both interferometric and single dish data. The CASA infrastructure consists of a set of C++ tools bundled together under an iPython interface as a set of data reduction tasks. This structure provides flexibility to process the data via task interface or as a python script. In addition to the data reduction tasks, many post-processing tools are available for even more flexibility and special purpose reduction needs.

[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:1402.013]
CASSIS: Interactive spectrum analysis

CASSIS (Centre d'Analyse Scientifique de Spectres Infrarouges et Submillimetriques), written in Java, is suited for broad-band spectral surveys to speed up the scientific analysis of high spectral resolution observations. It uses a local spectroscopic database made of the two molecular spectroscopic databases JPL and CDMS, as well as the atomic spectroscopic database NIST. Its tools include a LTE model and the RADEX model connected to the LAMDA molecular collisional database. CASSIS can build a line list fitting the various transitions of a given species and to directly produce rotational diagrams from these lists. CASSIS is fully integrated into HIPE, the Herschel Interactive Processing Environment, as a plug-in.

[ascl:1105.010]
CASTRO: Multi-dimensional Eulerian AMR Radiation-hydrodynamics Code

Almgren, A. S.; Beckner, V. E.; Bell, J. B.; Day, M. S.; Howell, L. H.; Katz, M; Lijewski, M. J.; Malone, C.; Nonaka, A.; Singer, M.; Zhang, W; Zingale, M.

CASTRO is a multi-dimensional Eulerian AMR radiation-hydrodynamics code that includes stellar equations of state, nuclear reaction networks, and self-gravity. Initial target applications for CASTRO include Type Ia and Type II supernovae. CASTRO supports calculations in 1-d, 2-d and 3-d Cartesian coordinates, as well as 1-d spherical and 2-d cylindrical (r-z) coordinate systems. Time integration of the hydrodynamics equations is based on an unsplit version of the the piecewise parabolic method (PPM) with new limiters that avoid reducing the accuracy of the scheme at smooth extrema. CASTRO can follow an arbitrary number of isotopes or elements. The atomic weights and amounts of these elements are used to calculate the mean molecular weight of the gas required by the equation of state. CASTRO supports several different approaches to solving for self-gravity. The most general is a full Poisson solve for the gravitational potential. CASTRO also supports a monopole approximation for gravity, and a constant gravity option is also available. The CASTRO software is written in C++ and Fortran, and is based on the BoxLib software framework developed by CCSE.

[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:1206.008]
Catena: Ensemble of stars orbit integration

Catena integrates the orbits of an ensemble of stars using the chain-regularization method (Mikkola & Aarseth) with an embedded Runge-Kutta integration method of 9(8)th order (Prince & Dormand).

[ascl: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: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.

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