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.

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.

CASSIS (Centre d'Analyse Scientifique de Spectres Infrarouges et Submillimetriques), written in Java, is suited for broad-band spectral surveys to speed up the scientific analysis of high spectral resolution observations. It uses a local spectroscopic database made of the two molecular spectroscopic databases JPL and CDMS, as well as the atomic spectroscopic database NIST. Its tools include a LTE model and the RADEX (ascl:1010.075) model connected to the LAMDA (ascl:1010.077) molecular collisional database. CASSIS can build a line list fitting the various transitions of a given species and to directly produce rotational diagrams from these lists. CASSIS is fully integrated into HIPE (ascl:1111.001), the Herschel Interactive Processing Environment, as a plug-in.

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 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.

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.

CatBoost is a machine learning method based on gradient boosting over decision trees and can be used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. It supports both numerical and categorical features and computation on CPU and GPU, and is fast and scalable. Visualization tools are also included in CatBoost.

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).

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.

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.

catwoman models asymmetric transit lightcurves. Written in Python, it calculates light curves for any radially symmetric stellar limb darkening law, and where planets are modeled as two semi-circles of different radii. Catwoman is built on the batman library (ascl:1510.002) and uses its integration algorithm.

The caustic technique is a powerful method to infer cluster mass profiles to clustrocentric distances well beyond the virial radius. It relies in the measure of the escape velocity of the sistem using only galaxy redshift information. This method was introduced by Diaferio & Geller (1997) and Diaferio (1999). This code allows the caustic mass estimation for galaxy clusters, as well as outlier identification as a side effect. However, a pre-cleaning of interlopers is recommended, using e.g., the shifting-gapper technique.

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.

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

CBiRd (Code for Bias tracers In Redshift space) provides correlators in the Effective Field Theory of Large-Scale Structure (EFTofLSS) in a ready-to-use pipeline for cosmological analysis of galaxy-redshift surveys data. It provides a core calculation package (C++BiRd), a Python implementation of a Taylor expansion of the power spectrum around a reference cosmology for efficient evaluation (TBiRd), and libraries to correct for observational systematics. CBiRd also provides MCMC samplers (MCBiRd) for a power spectrum and bispectrum analysis of galaxy-redshift surveys data based on emcee (ascl:1303.002), and can provide an earlybird pass to explore the cosmos with LSS surveys.

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

CCDLAB provides graphical user interface functionality for FITS image viewing and data reduction based on the JPFITS FITS-file interface. It can view, manipulate, and save FITS primary image data and image extensions, view and manipulate FITS image headers, and view FITS Bintable extensions. The code enables batch processing, viewing, and saving of FITS images and searching FITS files on disk. CCDLAB also provides general image reduction techniques, source detection and characterization, and can create World Coordinate Solutions automatically or manually for FITS images.

CCDPACK contains programs to debias, remove dark current, flatfield, register, resample and normalize data from single- or multiple-CCD instruments. The basic reduction stages can be set up using an X based GUI that controls an automated reduction system so one can to start working without any detailed knowledge of the package (or indeed of CCD reduction). Registration is performed using graphical, script based or automated techniques that keep the amount of work to a minimum. CCDPACK uses the Starlink environment (ascl:1110.012).

Ccdproc is an affiliated package for the AstroPy package for basic data reductions of CCD images. The ccdproc package provides many of the necessary tools for processing of ccd images built on a framework to provide error propagation and bad pixel tracking throughout the reduction process.

CCDtoRGB produces red‐green‐blue (RGB) composites from three‐band astronomical images, ensuring an object with a specified astronomical color has a unique color in the RGB image rather than burnt‐out white stars. Use of an arcsinh stretch shows faint objects while simultaneously preserving the structure of brighter objects in the field, such as the spiral arms of large galaxies.

CCFpams allows the measurement of stellar temperature, metallicity and gravity within a few seconds and in a completely automated fashion. Rather than performing comparisons with spectral libraries, the technique is based on the determination of several cross-correlation functions (CCFs) obtained by including spectral features with different sensitivity to the photospheric parameters. Literature stellar parameters of high signal-to-noise (SNR) and high-resolution HARPS spectra of FGK Main Sequence stars are used to calibrate the stellar parameters as a function of CCF areas.

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.

This suite contains two packages for computing cosmological quantities on the GPU: aperture_mass, which calculates the aperture mass map for a given dataset using the filter proposed by Schirmer et al (2007) (an NFW profile with exponential cut-offs at zero and large radii), and angular_correlation, which calculates the 2-pt angular correlation function using data and a flat distribution of randomly generated galaxies. A particular estimator is chosen, but the user has the flexibility to explore other estimators.

CCSNMultivar aids the analysis of core-collapse supernova gravitational waves. It includes multivariate regression of Fourier transformed or time domain waveforms, hypothesis testing for measuring the influence of physical parameters, and the Abdikamalov et. al. catalog for example use. CCSNMultivar can optionally incorporate additional uncertainty due to detector noise and approximate waveforms from anywhere within the parameter space.

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.

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.

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

celerite provides fast and scalable Gaussian Process (GP) Regression in one dimension and is implemented in C++, Python, and Julia. The celerite API is designed to be familiar to users of george and, like george, celerite is designed to efficiently evaluate the marginalized likelihood of a dataset under a GP model. This is then be used alongside a non-linear optimization or posterior inference library for the best results.

celerite has been superceded by celerite2 (ascl:2310.001).

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

The R package Celestial contains common astronomy conversion routines, particularly the HMS and degrees schemes, and a large range of functions for calculating properties of different cosmologies (as used by the cosmocalc website). This includes distances, ages, growth rate/factor and densities (e.g., Omega evolution and critical energy density). It also includes functions for calculating thermal properties of the CMB and Planck's equations and virial properties of halos in different cosmologies, and standard NFW and weak-lensing formulas and low level orbital routines for calculating Roche properties, Vis-Viva and free-fall times.

CELib (Chemical Evolution Library) simulates chemical evolution of galaxy formation under the simple stellar population (SSP) approximation and can be used by any simulation code that uses the SSP approximation, such as particle-base and mesh codes as well as semi-analytical models. Initial mass functions, stellar lifetimes, yields from type II and Ia supernovae, asymptotic giant branch stars, and neutron star mergers components are included and a variety of models are available for use. The library allows comparisons of the impact of individual models on the chemical evolution of galaxies by changing control flags and parameters of the library.

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

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.

Ceph_code fits multi-band Cepheid light-curves using templates derived from OGLE observations. The templates include short period stars (<10 day) and overtone stars.

The Collection of Extraction Routines for Echelle Spectra (CERES) constructs automated pipelines for the reduction, extraction, and analysis of echelle spectrograph data. This modular code includes tools for handling the different steps of the processing: CCD reductions, tracing of the echelle orders, optimal and simple extraction, computation of the wave-length solution, estimation of radial velocities, and rough and fast estimation of the atmospheric parameters. The standard output of pipelines constructed with CERES is a FITS cube with the optimally extracted, wavelength calibrated and instrumental drift-corrected spectrum for each of the science images. Additionally, CERES includes routines for the computation of precise radial velocities and bisector spans via the cross-correlation method, and an automated algorithm to obtain an estimate of the atmospheric parameters of the observed star.

The Cesam code is a consistent set of programs and routines which perform calculations of 1D quasi-hydrostatic stellar evolution including microscopic diffusion of chemical species and diffusion of angular momentum. The solution of the quasi-static equilibrium is performed by a collocation method based on piecewise polynomials approximations projected on a B-spline basis; that allows stable and robust calculations, and the exact restitution of the solution, not only at grid points, even for the discontinuous variables. Other advantages are the monitoring by only one parameter of the accuracy and its improvement by super-convergence. An automatic mesh refinement has been designed for adjusting the localisations of grid points according to the changes of unknowns. For standard models, the evolution of the chemical composition is solved by stiffly stable schemes of orders up to four; in the convection zones mixing and evolution of chemical are simultaneous. The solution of the diffusion equation employs the Galerkin finite elements scheme; the mixing of chemicals is then performed by a strong turbulent diffusion. A precise restoration of the atmosphere is allowed for.

CEvNS calculates Coherent Elastic Neutrino-Nucleus Scattering (CEvNS) cross sections and recoil spectra. It includes (among other things) the Standard Model contribution to the CEvNS cross section, along with the contribution from Simplified Models with new vector or scalar mediators. It also covers neutrino magnetic moments and non-standard contact neutrino interactions (NSI).

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/.

CFITSIO is a library of C and Fortran subroutines for reading and writing data files in FITS (Flexible Image Transport System) data format. CFITSIO provides simple high-level routines for reading and writing FITS files that insulate the programmer from the internal complexities of the FITS format. CFITSIO also provides many advanced features for manipulating and filtering the information in FITS files.

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.

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.

CGS3DR is data reduction software for the UKIRT CGS3 mid-infrared grating spectrometer instrument. It includes a command-line interface and a GUI. The software, originally on VMS, was ported to Unix. It uses Starlink (ascl:1110.012) infrastructure libraries.

CGS4DR is data reduction software for the CGS4 instrument at UKIRT. The software can be used offline to reprocess CGS4 data. CGS4DR allows a wide variety of data reduction configurations, and can interlace oversampled data frames; reduce known bias, dark, flat, arc, object and sky frames; remove the sky, residual sky OH-lines (λ < 2.3 μm) and thermal emission (λ ≥ 2.3 μm) from data; and add data into groups for improved signal-to-noise. It can also extract and de-ripple a spectrum and offers a variety of ways to plot data, in addition to other useful features. CGS4DR is distributed as part of the Starlink software collection (ascl:1110.012).

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.

ChaNGa (Charm N-body GrAvity solver) performs collisionless N-body simulations. It can perform cosmological simulations with periodic boundary conditions in comoving coordinates or simulations of isolated stellar systems. It also can include hydrodynamics using the Smooth Particle Hydrodynamics (SPH) technique. It uses a Barnes-Hut tree to calculate gravity, with hexadecapole expansion of nodes and Ewald summation for periodic forces. Timestepping is done with a leapfrog integrator with individual timesteps for each particle.

Charm (cosmic history agnostic reconstruction method) reconstructs the cosmic expansion history in the framework of Information Field Theory. The reconstruction is performed via the iterative Wiener filter from an agnostic or from an informative prior. The charm code allows one to test the compatibility of several different data sets with the LambdaCDM model in a non-parametric way.

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

Cheetah models starspots in photometric data (lightcurves) by calculating the modulation of a light curve due to starspots. The main parameters of the program are the linear and quadratic limb darkening coefficients, stellar inclination, spot locations and sizes, and the intensity ratio of the spots to the stellar photosphere. Cheetah uses uniform spot contrast and the minimum number of spots needed to produce a good fit and ignores bright regions for the sake of simplicity.

Chem-I-Calc evaluates the chemical information content of resolved star spectroscopy. It takes advantage of the Fisher information matrix and the Cramér-Rao inequality to quickly calculate the Cramér-Rao lower bounds (CRLBs), which give the best theoretically achievable precision from a set of observations.

chemcomp models and enables the study of the formation of planets in 1D protoplanetary disks. It includes disk physics for viscous disk evolution, pebble growth and evolution applying the two populations model, evaporation and condensation at evaporation lines, and chemical compositions. Written in Python, chemcomp also includes planet physics for type-I and type-II migration, thermal and dynamical torques, and pebble and gas accretion.

Chempy models Galactic chemical evolution (GCE); it is a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of 5-10 parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: e.g. the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF) and the incidence of supernova of type Ia (SN Ia). Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets, performing essentially as a chemical evolution fitting tool. Chempy can be used to confront predictions from stellar nucleosynthesis with complex abundance data sets and to refine the physical processes governing the chemical evolution of stellar systems.

ChempyMulti (ascl:1909.006) is available as an update to the ChempyScoring package.