Results 401-500 of 3033 (2961 ASCL, 72 submitted)
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.
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.
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.
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.
The neural network-based emulator Chemulator advances the gas temperature and chemical abundances of a single position in an astrophysical gas. It is accurate on a single timestep and stable over many iterations with decreased accuracy, though performs less well at low visual extinctions. The code is useful for applications such as large scale ISM modeling; by retraining the emulator for a given parameter space, Chemulator could also perform more specialized applications such as planetary atmosphere modeling.
CHIANTI consists of a critically evaluated set of atomic data necessary to calculate the emission line spectrum of astrophysical plasmas. The data consists of atomic energy levels, atomic radiative data such as wavelengths, weighted oscillator strengths and A values, and electron collisional excitation rates. A set of programs that use these data to calculate the spectrum in a desired wavelength range as a function of temperature and density are also provided. These programs have been written in Interactive Data Language (IDL) and descriptions of these various programs are provided on the website.
ChiantiPy is an object-orient Python package for calculating astrophysical spectra using the CHIANTI atomic database for astrophysical spectroscopy. It provides access to the database and the ability to calculate various physical quantities for the interpretation of astrophysical spectra.
Chimenea implements an heuristic algorithm for automated imaging of multi-epoch radio-synthesis data. It generates a deep image via an iterative Clean subroutine performed on the concatenated visibility set and locates steady sources in the field of view. The code then uses this information to apply constrained and then unconstrained (i.e., masked/open-box) Cleans to the single-epoch observations. This obtains better results than if the single-epoch data had been processed independently without prior knowledge of the sky-model. The chimenea pipeline is built upon CASA (ascl:1107.013) subroutines, interacting with the CASA environment via the drive-casa (ascl:1504.006) interface layer.
CHIMERA simulates core collapse supernovas; it is three-dimensional and accounts for the differing energies of neutrinos. This massively parallel multiphysics code conserves total energy (gravitational, internal, kinetic, and neutrino) to within 0.5 B, given a conservative gravitational potential. CHIMERA has three main components: a hydro component, a neutrino transport component, and a nuclear reaction network component. It also includes a Poisson solver for the gravitational potential and a sophisticated equation of state.
CHIP (Caltech High-res IRS Pipeline) reduces high signal-to-noise short-high and long-high Spitzer-IRS spectra, especially that taken with dedicated background exposures. Written in IDL, it is independent of other Spitzer reduction tools except IRSFRINGE (ascl:1602.016).
A self-contained Fortran-77 program for goodness of fit tests for histograms with weighted entries as well as with unweighted entries is presented. The code calculates test statistic for case of histogram with normalized weights of events and for case of unnormalized weights of events.
CHLOE is an image analysis unsupervised learning algorithm that detects peculiar galaxies in datasets of galaxy images. The algorithm first computes a large set of numerical descriptors reflecting different aspects of the visual content, and then weighs them based on the standard deviation of the values computed from the galaxy images. The weighted Euclidean distance of each galaxy image from the median is measured, and the peculiarity of each galaxy is determined based on that distance.
Cholla (Computational Hydrodynamics On ParaLLel Architectures) models the Euler equations on a static mesh and evolves the fluid properties of thousands of cells simultaneously using GPUs. It can update over ten million cells per GPU-second while using an exact Riemann solver and PPM reconstruction, allowing computation of astrophysical simulations with physically interesting grid resolutions (>256^3) on a single device; calculations can be extended onto multiple devices with nearly ideal scaling beyond 64 GPUs.
Chombo provides a set of tools for implementing finite difference methods for the solution of partial differential equations on block-structured adaptively refined rectangular grids. Both elliptic and time-dependent modules are included. Chombo supports calculations in complex geometries with both embedded boundaries and mapped grids, and also supports particle methods. Most parallel platforms are supported, and cross-platform self-describing file formats are included.
The Chombo package is a product of the community of Collaborators working with the Applied Numerical Algorithms Group (ANAG), part of the Computational Research Division at LBNL.
CHORIZOS is a multi-purpose Bayesian code developed in IDL to compare photometric data with model spectral energy distributions (SEDs). The user can select the SED family (e.g. Kurucz) and choose the behavior of each parameter (e.g. Teff) to be fixed, constrained to a given range, or unconstrained. The code calculates the likelihood for the full specified parameter ranges, thus allowing for the identification of multiple solutions and the evaluation of the full correlation matrix for the derived parameters of a single solution.
Transit light curves for stellar continua have only one minimum and a "U" shape. By contrast, transit curves for optically thin chromospheric emission lines can have a "W" shape because of stellar limb-brightening. We calculate light curves for an optically thin shell of emission and fit these models to time-resolved observations of Si IV absorption by the planet HD209458b. We find that the best fit Si IV absorption model has R_p,SIV/R_*= 0.34+0.07-0.12, similar to the Roche lobe of the planet. While the large radius is only at the limit of statistical significance, we develop formulae applicable to transits of all optically thin chromospheric emission lines.
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.
ChromaStarServer (formerly GrayStarServer) is a stellar atmospheric modeling and spectrum synthesis code of pedagogical accuracy that is accessible in any web browser on commonplace computational devices and that runs on a timescale of a few seconds.
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.
CIAO is a data analysis system written for the needs of users of the Chandra X-ray Observatory. Because Chandra data is 4-dimensional (2 spatial, time, energy) and each dimension has many independent elements, CIAO was built to handle N-dimensional data without concern about which particular axes were being analyzed. Apart from a few Chandra instrument tools, CIAO is mission independent. CIAO tools read and write several formats, including FITS images and tables (which includes event files) and IRAF imh files. CIAO is a powerful system for the analysis of many types of data.
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.
The CIGALE code has been developed to study the evolution of galaxies by comparing modelled galaxy spectral energy distributions (SEDs) to observed ones from the far ultraviolet to the far infrared. It extends the SED fitting algorithm written by Burgarella et al. (2005, MNRAS 360, 1411). While the previous code was designed to fit SEDs in the optical and near infrared, CIGALE is able to fit SEDs up to the far infrared using Dale & Helou (2002, ApJ 576, 159). CIGALE Bayesian and CIGALE Monte Carlo Markov Chain are available.
CINE calculates infrared pumping efficiencies that can be applied to the most common molecules found in cometary comae such as water, hydrogen cyanide or methanol. One of the main mechanisms for molecular excitation in comets is the fluorescence by the solar radiation followed by radiative decay to the ground vibrational state. This command-line tool calculates the effective pumping rates for rotational levels in the ground vibrational state scaled by the heliocentric distance of the comet. Fluorescence coefficients are useful for modeling rotational emission lines observed in cometary spectra at sub-millimeter wavelengths. Combined with computational methods to solve the radiative transfer equations based, e.g., on the Monte Carlo algorithm, this model can retrieve production rates and rotational temperatures from the observed emission spectrum.
CircleCraters is a projection independent crater counting plugin for QGIS. It has the flexibility to crater count in a GIS environment on Windows, OS X, or Linux, and uses three-click input to define crater rims as a circle.
CISM_DX is a community-developed suite of integrated data, models, and data and model explorers, for research and education. The data and model explorers are based on code written for OpenDX and Octave; OpenDX provides the visualization infrastructures as well as the process for creating user interfaces to the model and data, and Octave allows for extensive data manipulation and reduction operations. The CISM-DX package extends the capabilities of the core software programs to meet the needs of space physics researchers.
Citlalicue allows you to create synthetic stellar light curves (transits, stellar variability and white noise) and detrend light curves using Gaussian Processes (GPs). Transits are implemented using PyTransit (ascl:1505.024). Python notebooks are provided to demonstrate using Citlalicue for both functions.
CJAM calculates first and second velocity moments using the Jeans Anisotropic MGE (JAM) models of Cappellari (2008) and Cappellari (2012). These models have been extended to calculate all three (x, y, z) first moments and all six (xx, yy, zz, xy, xz, yz) second moments. CJAM, written in C, is based on the IDL implementation of the line-of-sight calculations by Michele Cappellari.
Cloud Killer recovers surface albedo maps by using reflected light photometry to map the clouds and surface of unresolved exoplanets. For light curves with negligible photometric uncertainties, the minimal top-of-atmosphere albedo at a location is a good estimate of its surface albedo. On synthetic data, it shows little bias, good precision, and accuracy, but slightly underestimated uncertainties; exoplanets with large, changing cloud structures observed near quadrature phases are good candidates for Cloud Killer cloud removal.
ClaRAN (Classifying Radio sources Automatically with Neural networks) classifies radio source morphology based upon the Faster Region-based Convolutional Neutral Network (Faster R-CNN). It is capable of associating discrete and extended components of radio sources in an automated fashion. ClaRAN demonstrates the feasibility of applying deep learning methods for cross-matching complex radio sources of multiple components with infrared maps. The promising results from ClaRAN have implications for the further development of efficient cross-wavelength source identification, matching, and morphology classifications for future radio surveys.
Boltzmann codes are used extensively by several groups for constraining cosmological parameters with Cosmic Microwave Background and Large Scale Structure data. This activity is computationally expensive, since a typical project requires from 10'000 to 100'000 Boltzmann code executions. The code CLASS (Cosmic Linear Anisotropy Solving System) incorporates improved approximation schemes leading to a simultaneous gain in speed and precision. We describe here the three approximations used by CLASS for basic LambdaCDM models, namely: a baryon-photon tight-coupling approximation which can be set to first order, second order or to a compromise between the two; an ultra-relativistic fluid approximation which had not been implemented in public distributions before; and finally a radiation streaming approximation taking reionisation into account.
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).
CLE, written in Fortran 77, synthesizes Stokes profiles of forbidden lines such as Fe XIII 1074.7nm, formed in magnetic dipole transitions under coronal conditions. The lines are assumed to be optically thin, excited by (anisotropic) photospheric radiation and thermal particle collisions.
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.
CLOC computes cluster order statistics, i.e. the luminosity distribution of the Nth most luminous cluster in a population. It is flexible and requires few assumptions, allowing for parametrized variations in the initial cluster mass function and its upper and lower cutoffs, variations in the cluster age distribution, stellar evolution and dust extinction, as well as observational uncertainties in both the properties of star clusters and their underlying host galaxies. It uses Markov chain Monte Carlo methods to search parameter space to find best-fitting values for the parameters describing cluster formation and disruption, and to obtain rigorous confidence intervals on the inferred values.
We developed a new quick pseudo-3D photoionization code based on Cloudy (G. Ferland) and IDL (RSI) tools. The code is running the 1D photoionization code Cloudy various times, changing at each run the input parameters (e.g. inner radius, density law) according to an angular law describing the morphology of the object. Then a cube is generated by interpolating the outputs of Cloudy. In each cell of the cube, the physical conditions (electron temperature and density, ionic fractions) and the emissivities of lines are determined. Associated tools (VISNEB and VELNEB_3D) are used to rotate the nebula and to compute surface brightness maps and emission line profiles, given a velocity law and taking into account the effect of the thermal broadening and eventually the turbulence. Integrated emission line profiles are computed, given aperture shapes and positions (seeing and instrumental width effects are included). The main advantage of this tool is the short time needed to compute a model (a few tens minutes).
Cloudy_3D has been superseded by pycloudy (ascl:1304.020).
Cloudy is a large-scale spectral synthesis code designed to simulate fully physical conditions within an astronomical plasma and then predict the emitted spectrum. The code is freely available and is widely used in the analysis and interpretation of emission-line spectra.
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.
We describe an automatic, objective routine for analyzing the clumpy structure in a spectral line position-position-velocity data cube. The algorithm works by first contouring the data at a multiple of the rms noise of the observations, then searches for peaks of emission which locate the clumps, and then follows them down to lower intensities. No a proiri clump profile is assumed. By creating simulated data, we test the performance of the algorithm and show that a contour map most accurately depicts internal structure at a contouring interval equal to twice the rms noise of the map. Blending of clump emission leads to small errors in mass and size determinations and in severe cases can result in a number of clumps being misidentified as a single unit, flattening the measured clump mass spectrum. The algorithm is applied to two real data sets as an example of its use. The Rosette molecular cloud is a 'typical' star-forming cloud, but in the Maddalena molecular cloud high-mass star formation is completely absent. Comparison of the two clump lists generated by the algorithm show that on a one-to-one basis the clumps in the star-forming cloud have higher peak temperatures, higher average densities, and are more gravitationally bound than in the non-star-forming cloud. Collective properties of the clumps, such as temperature-size-line-width-mass relations appear very similar, however. Contrary to the initial results reported in a previous paper (Williams & Blitz 1993), we find that the current, more thoroughly tested analysis finds no significant difference in the clump mass spectrum of the two clouds.
CLUMPY is a public code for semi-analytical calculation of the gamma-ray flux astrophysical J-factor from dark matter annihilation/decay in the Galaxy, including dark matter substructures. The core of the code is the calculation of the line of sight integral of the dark matter density squared (for annihilations) or density (for decaying dark matter). The code can be used in three modes: i) to draw skymaps from the Galactic smooth component and/or the substructure contributions, ii) to calculate the flux from a specific halo (that is not the Galactic halo, e.g. dwarf spheroidal galaxies) or iii) to perform simple statistical operations from a list of allowed DM profiles for a given object. Extragalactic contributions and other tracers of DM annihilation (e.g. positrons, antiprotons) will be included in a second release.
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.
Cluster Toolkit calculates weak lensing signals from galaxy clusters and cluster cosmology. It offers 3D density and correlation functions, halo bias models, projected density and differential profiles, and radially averaged profiles. It also calculates halo mass functions, mass-concentration relations, Sunyaev-Zel’dovich (SZ) cluster signals, and cluster magnification. Cluster Toolkit consists of a Python front end wrapped around a well optimized back end in C.
Cluster-in-a-box provides a statistical model of sub-millimeter emission from embedded protostellar clusters and consists of three modules grouped in two scripts. The first (cluster_distribution) generates the cluster based on the number of stars, input initial mass function, spatial distribution and age distribution. The second (cluster_emission) takes an input file of observations, determines the mass-intensity correlation and generates outflow emission for all low-mass Class 0 and I sources. The output is stored as a FITS image where the flux density is determined by the desired resolution, pixel scale and cluster distance.
The cluster-lensing package calculates properties and weak lensing profiles of galaxy clusters. Implemented in Python, it includes cluster mass-richness and mass-concentration scaling relations, and NFW halo profiles for weak lensing shear, the differential surface mass density ΔΣ(r), and for magnification, Σ(r). Optionally the calculation will include the effects of cluster miscentering offsets.
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.
Clustering is a modified version of the single-pulse sifting algorithm RRATrap (ascl:2011.017) combined with DBSCAN codes to cluster single pulse events.
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.
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.
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.
This code is a quick and exact calculator of B-mode angular spectrum due to Faraday rotation by stochastic magnetic fields. Faraday rotation induced B-modes can provide a distinctive signature of primordial magnetic fields because of their characteristic frequency dependence and because they are only weakly damped on small scales, allowing them to dominate B-modes from other sources. By numerically solving the full CMB radiative transport equations, we study the B-mode power spectrum induced by stochastic magnetic fields that have significant power on scales smaller than the thickness of the last scattering surface. Constraints on the magnetic field energy density and inertial scale are derived from WMAP 7-year data, and are stronger than the big bang nucleosynthesis (BBN) bound for a range of parameters. Observations of the CMB polarization at smaller angular scales are crucial to provide tighter constraints or a detection.
This code is based on the cosmic string model described in this paper by Pogosian and Vachaspati, as well as on the CMBFAST code created by Uros Seljak and Matias Zaldarriaga. It contains an integrator for the vector contribution to the CMB temperature and polarization. The code is reconfigured to make it easier to use with or without active sources. To produce inflationary CMB spectra one simply sets the string tension to zero (gmu=0.0d0). For a non-zero value of tension only the string contribution is calculated.
An option is added to randomize the directions of velocities of consolidated segments as they evolve in time. In the original segment model, which is still the default version (irandomv=0), each segment is given a random velocity initially, but then continues to move in a straight line for the rest of its life. The new option (irandomv=1) allows to additionally randomize velocities of each segment at roughly each Hubble time. However, the merits of this new option are still under investigation. The default version (irandomv=0) is strongly recommended, since it actually gives reasonable unequal time correlators. For each Fourier mode, k, the string stress-energy components are now evaluated on a time grid sufficiently fine for that k.
CMBEASY is a software package for calculating the evolution of density fluctuations in the universe. Most notably, the Cosmic Microwave Background temperature anisotropies. It features a Markov Chain Monte Carlo driver and many routines to compute likelihoods of any given model. It is based on the CMBFAST package by Uros Seljak and Matias Zaldarriaga.
CMBFAST is the most extensively used code for computing cosmic microwave background anisotropy, polarization and matter power spectra. This package contains cosmological linear perturbation theory code to compute the evolution of various cosmological matter and radiation components, both today and at high redshift. The code has been tested over a wide range of cosmological parameters.
This code is no longer supported; please investigate using CAMB (ascl:1102.026) instead.
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).
CMBquick is a package for Mathematica in which tools are provided to compute the spectrum and bispectrum of Cosmic Microwave Background (CMB). It is unavoidably slow, but the main goal is not to design a tool which can be used for systematic exploration of parameters in cosmology, but rather a toy CMB code which is transparent and easily modified. Considering this, the name chosen is nothing but a joke which refers to the widely spread and used softwares CMBFAST, CAMB or CMBeasy (ascl:1007.004), which should be used for serious and heavy first order CMB computations, and which are indeed very fast.
The package CMBquick is unavoidably slow when it comes to compute the multipoles Cls, and most of it is due to the access time for variables which in Mathematica is approximately ten times slower than in C or Fortran. CMBquick is thus approximately 10 times slower than CAMB and cannot be used for the same reasons. It uses the same method as CAMB for computing the CMB spectrum, which is based on the line of sight approach. However the integration is performed in a different gauge with different time steps and k-spacing. It benefits from the power of Mathematica on numerical resolution of stiff differential systems, and the transfer functions can be obtained with exquisite accuracy.
The purpose of CMBquick is thus twofold. First, CMBquick is a slow but precise and pedagogical, tool which can be used to explore and modify the physical content of the linear and non-linear dynamics. Second, it is a tool which can help developing templates for nonlinear computations, which could then be hard coded once their correctness is checked. The number of equations for non-linear dynamics is quite sizable and CMBquick makes it easy (but slow) to manipulate the non-linear equations, to solve them precisely, and to plot them.
CMBview is a viewer for FITS files containing HEALPix sky maps. Sky maps are projected onto a 3d sphere which can be rotated and zoomed interactively with the mouse. Features include:
CMC-COSMIC models dense star clusters using Hénon's method using orbit-averaging collisional stellar dynamics. It includes all the relevant physics for modeling dense spherical star clusters, such as strong dynamical encounters, single and binary stellar evolution, central massive black holes, three-body binary formation, and relativistic dynamics, among others. CMC is parallelized using the Message Passing Interface (MPI), and is pinned to the COSMIC (ascl:2108.022) package for binary population synthesis, which itself was originally based on the version of BSE (ascl:1303.014). COSMIC is currently a submodule within CMC, ensuring that any cluster simulations or binary populations are integrated with the same physics.
The Caitlin M. Casey Infra Red Spectral Energy Distribution model (CMCIRSED) provides a simple SED fitting technique suitable for a wide range of IR data, from sources which have only three IR photometric points to sources with >10 photometric points. These SED fits produce accurate estimates to a source's integrated IR luminosity, dust temperature and dust mass. CMCIRSED is based on a single dust temperature greybody fit linked to a MIR power law, fitted simultaneously to data across ∼5–2000 μm.
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.
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.
A radiative transfer code designed to solve the radiative transfer and statistical equilibrium equations in spherical geometry. It has been designed for application to W-R stars, O stars, and Luminous Blue-Variables. CMFGEN allows fundamental parameters such as effective temperatures, stellar radii and stellar luminosities to be determined. It can provide constraints on mass-loss rates, and allow abundance determinations for a wide range of atomic species. Further it can provide accurate energy distributions, and hence ionizing fluxes, which can be used as input for codes which model the spectra of HII regions and ring nebular.
CMHOG (Connection Machine Higher Order Godunov) is a code for ideal compressible hydrodynamics based on the Lagrange-plus-remap version of the piecewise parabolic method (PPM) of Colella & Woodward (1984, J. Comp. Phys., 74, 1). It works in one-, two- or three-dimensional Cartesian coordinates with either an adiabatic or isothermal equation of state. A limited amount of extra physics has been added using operator splitting, including optically-thin radiative cooling, and chemistry for combustion simulations.
CO5BOLD - nickname COBOLD - is the short form of "COnservative COde for the COmputation of COmpressible COnvection in a BOx of L Dimensions with l=2,3''.
It is used to model solar and stellar surface convection. For solar-type stars only a small fraction of the stellar surface layers are included in the computational domain. In the case of red supergiants the computational box contains the entire star. Recently, the model range has been extended to sub-stellar objects (brown dwarfs).
CO5BOLD solves the coupled non-linear equations of compressible hydrodynamics in an external gravity field together with non-local frequency-dependent radiation transport. Operator splitting is applied to solve the equations of hydrodynamics (including gravity), the radiative energy transfer (with a long-characteristics or a short-characteristics ray scheme), and possibly additional 3D (turbulent) diffusion in individual sub steps. The 3D hydrodynamics step is further simplified with directional splitting (usually). The 1D sub steps are performed with a Roe solver, accounting for an external gravity field and an arbitrary equation of state from a table.
The radiation transport is computed with either one of three modules:
CO5BOLD is written in Fortran90. The parallelization is done with OpenMP directives.
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.
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.
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.
COBS (COnstrained B-Splines), written in R, creates constrained regression smoothing splines via linear programming and sparse matrices. The method has two important features: the number and location of knots for the spline fit are established using the likelihood-based Akaike Information Criterion (rather than a heuristic procedure); and fits can be made for quantiles (e.g. 25% and 75% as well as the usual 50%) in the response variable, which is valuable when the scatter is asymmetrical or non-Gaussian. This code is useful for, for example, estimating cluster ages when there is a wide spread in stellar ages at a chosen absorption, as a standard regression line does not give an effective measure of this relationship.
The COCO program converts star coordinates from one system to another. Both the improved IAU system, post-1976, and the old pre-1976 system are supported. COCO can perform accurate transformations between multiple coordinate systems. COCO’s user-interface is spartan but efficient and the program offers control over report resolution. All input is free-format, and defaults are provided where this is meaningful. COCO uses SLALIB (ascl:1403.025) and is distributed as part of the Starlink software collection (ascl:1110.012).
COCOA (Cluster simulatiOn Comparison with ObservAtions) creates idealized mock photometric observations using results from numerical simulations of star cluster evolution. COCOA is able to present the output of realistic numerical simulations of star clusters carried out using Monte Carlo or N-body codes in a way that is useful for direct comparison with photometric observations. The code can simulate optical observations from simulation snapshots in which positions and magnitudes of objects are known. The parameters for simulating the observations can be adjusted to mimic telescopes of various sizes. COCOA also has a photometry pipeline that can use standalone versions of DAOPHOT (ascl:1104.011) and ALLSTAR to produce photometric catalogs for all observed stars.
CoCoNuT is a general relativistic hydrodynamics code with dynamical space-time evolution. The main aim of this numerical code is the study of several astrophysical scenarios in which general relativity can play an important role, namely the collapse of rapidly rotating stellar cores and the evolution of isolated neutron stars. The code has two flavors: CoCoA, the axisymmetric (2D) magnetized version, and CoCoNuT, the 3D non-magnetized version.
The COCOPLOT (COlor COllapsed PLOTting) quick-look and context image code conveys spectral profile information from all of the spatial pixels in a 3D datacube as a single image using color. It can also identify and expose temporal behavior and display and highlight solar features. COCOPLOT thus aids in identifying regions of interest quickly. The software is available in Python and IDL, and can be used as a standalone package or integrated into other software.
COLAcode is a serial particle mesh-based N-body code illustrating the COLA (COmoving Lagrangian Acceleration) method; it solves for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). It differs from standard N-body code by trading accuracy at small-scales to gain computational speed without sacrificing accuracy at large scales. This is useful for generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing; such catalogs are needed to perform detailed error analysis for ongoing and future surveys of LSS.
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.
CoLoRe (Cosmological Lofty Realization) generates fast mock realizations of a given galaxy sample using a lognormal model or LPT for the matter density. Tt can simulate a variety of cosmological tracers, including photometric and spectroscopic galaxies, weak lensing, and intensity mapping. CoLoRe is a parallel C code, and its behavior is controlled primarily by the input param file.
ColorPro automatically obtains robust colors across images of varied PSF. To correct for the flux lost in images with poorer PSF, the "detection image" is blurred to match the PSF of these other images, allowing observation of how much flux is lost. All photometry is performed in the highest resolution frame (images being aligned given WCS information in the FITS headers), and identical apertures are used in every image. Usually isophotal apertures are used, as determined by SExtractor (ascl:1010.064). Using SExSeg (ascl:1508.006), object aperture definitions can be pre-defined and object detections from different image filters can be combined automatically into a single comprehensive "segmentation map." After producing the final photometric catalog, ColorPro can automatically run BPZ (ascl:1108.011) to obtain Bayesian Photometric Redshifts.
Colossus is a collection of Python modules for cosmology and dark matter halos calculations. It performs cosmological calculations with an emphasis on structure formation applications, implements general and specific density profiles, and provides a large range of models for the concentration-mass relation, including a conversion to arbitrary mass definitions.
COMB supports the simulation on the sphere of compact objects embedded in a stochastic background process of specified power spectrum. Support is provided to add additional white noise and convolve with beam functions. Functionality to support functions defined on the sphere is provided by the S2 code (ascl:1606.008); HEALPix (ascl:1107.018) and CFITSIO (ascl:1010.001) are also required.
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.
ComEst calculates the completeness of CCD images conducted in astronomical observations saved in the FITS format. It estimates the completeness of the source finder SExtractor (ascl:1010.064) on the optical and near-infrared (NIR) imaging of point sources or galaxies as a function of flux (or magnitude) directly from the image itself. It uses PyFITS (ascl:1207.009) and GalSim (ascl:1402.009) to perform the end-to-end estimation of the completeness and can also estimate the purity of the source detection.
COMET (Clustering Observables Modelled by Emulated perturbation Theory) provides emulated predictions of large-scale structure observables from models that are based on perturbation theory. It substantially speeds up these analytic computations without any relevant sacrifice in accuracy, enabling an extremely efficient exploration of large-scale structure likelihoods. At its core, COMET exploits an evolution mapping approach which gives it a high degree of flexibility and allows it to cover a wide cosmology parameter space at continuous redshifts up to z∼3z \sim 3z∼3. Among others, COMET supports parameters for cold dark matter density (ωc\omega_cωc), baryon density (ωb\omega_bωb), Scalar spectral index (nsn_sns), Hubble expansion rate (hhh) and Curvature density (ΩK\Omega_KΩK). The code can obtain the real-space galaxy power spectrum at one-loop order multipoles (monopole, quadrupole, hexadecapole) of the redshift-space, power spectrum at one-loop order, the linear matter power spectrum (with and without infrared resummation), Gaussian covariance matrices for the real-space power spectrum, and redshift-space multipoles and χ2\chi^2χ2's for arbitrary combinations of multipoles. COMET provides an easy-to-use interface for all of these computations.
Comet is a Python implementation of the VOEvent Transport Protocol (VTP). VOEvent is the IVOA system for describing transient celestial events. Details of transients detected by many projects, including Fermi, Swift, and the Catalina Sky Survey, are currently made available as VOEvents, which is also the standard alert format by future facilities such as LSST and SKA. The core of Comet is a multifunction VOEvent broker, capable of receiving events either by subscribing to one or more remote brokers or by direct connection from authors; it can then both process those events locally and forward them to its own subscribers. In addition, Comet provides a tool for publishing VOEvents to the global VOEvent backbone.
Commander 2 is a Gibbs sampling code for joint CMB estimation and component separation. The Commander framework uses a parametrized physical model of the sky to perform statistically-rigorous analyses of multi-frequency, multi-resolution CMB data on the full and partial (flat) sky, as well as cross-correlation analyses with large-scale structure datasets.
CoMover determines the probability that two stars are co-moving and thus gravitationally bound. It uses the sky position, proper motion, parallax and optionally the heliocentric radial velocity of a host star (with their respective measurement errors), and compares it to the observables of a potential companion (with their respective measurement errors). The sky position and proper motion of the potential companion star are required, and its heliocentric radial velocity and parallax are facultative inputs to refine its co-moving probability.
If all kinematic observables of the host star are provided, a single spatial-kinematic model is built, consisting of a single 6-dimensional multivariate Gaussian in Galactic coordinates (XYZ) and space velocities (UVW). The observables of the potential companion are then compared to this model and a given field-stars model with Bayes' theorem by marginalizing over any missing kinematic observables of the companion star with analytical integral solutions. The field stars are modeled using a 10-component multivariate Gaussian, accurate for stars within a few hundred parsecs of the Sun. In the case where a heliocentric radial velocity is missing for the host star, the single host-star multivariate Gaussian model is replaced with a series of host star models and numerically marginalized over by taking the numerical sum of the host-star model probabilities.
The software used to transform the tabular USNO/AE98 asteroid ephemerides into a Chebyshev polynomial representations, and evaluate them at an arbitrary time is available. The USNO/AE98 consisted of the ephemerides of fifteen of the largest asteroids, and were used in The Astronomical Almanac from 2000 through 2015. These ephemerides are outdated and no longer available, but the software used to store and evaluate them is still available and provides a robust method for storing compact ephemerides of solar system bodies.
The object of the software is to provide a compact binary representation of solar system bodies with eccentric orbits, which can produce the body's position and velocity at an arbitrary instant within the ephemeris' time span. It uses a modification of the Newhall (1989) algorithm to achieve this objective. The Newhall algorithm is used to store both the Jet Propulsion Laboratory DE and the Institut de mécanique céleste et de calcul des éphémérides INPOP high accuracy planetary ephemerides. The Newhall algorithm breaks an ephemeris into a number time contiguous segments, and each segment is stored as a set of Chebyshev polynomial coefficients. The length of the time segments and the maximum degree Chebyshev polynomial coefficient is fixed for each body. This works well for bodies with small eccentricities, but it becomes inefficient for a body in a highly eccentric orbit. The time segment length and maximum order Chebyshev polynomial coefficient must be chosen to accommodate the strong curvature and fast motion near pericenter, while the body spends most of its time either moving slowly near apocenter or in the lower curvature mid-anomaly portions of its orbit. The solution is to vary the time segment length and maximum degree Chebyshev polynomial coefficient with the body's position. The portion of the software that converts tabular ephemerides into a Chebyshev polynomial representation (CPR) performs this compaction automatically, and the portion that evaluates that representation requires only a modest increase in the evaluation time.
The software also allows the user to choose the required tolerance of the CPR. Thus, if less accuracy is required a more compact, somewhat quicker to evaluate CPR can be manufactured and evaluated. Numerical tests show that a fractional precision of 4e-16 may be achieved, only a factor of 4 greater than the 1e-16 precision of a 64-bit IEEE (2019) compliant floating point number.
The software is written in C and designed to work with the C edition of the Naval Observatory Vector Astrometry Software (NOVAS). The programs may be used to convert tabular ephemerides of other solar system bodies as well. The included READ.ME file provides the details of the software and how to use it.
IEEE Computer Society 2019, IEEE Standard for Floating-Point Arithmetic. IEEE STD 754-2019, IEEE, pp. 1–84
Newhall, X X 1989, 'Numerical Representation of Planetary Ephemerides,' Celest. Mech., 45, 305 - 310
Companion-Finder looks for planets and binary companions in time series spectra by searching for the spectral lines of stellar companions to other stars observed with high-precision radial-velocity surveys.
COMPAS (Compact Object Mergers: Population Astrophysics & Statistics) draws properties for a binary star system from a set of initial distributions and evolves it from zero-age main sequence to the end of its life as two compact remnants. Evolution prescriptions and model parameters are easily adjustable in the software. COMPAS has been used for inference from observations of gravitational-wave mergers, Galactic neutron stars, X-ray binaries, and luminous red novae.
ComputePk computes the power spectrum in cosmological simulations. It is MPI parallel and has been tested up to a 4096^3 mesh. It uses the FFTW library. It can read Gadget-3 and GOTPM outputs, and computes the dark matter component. The user may choose between NGP, CIC, and TSC for the mass assignment scheme.
ConeRot extracts velocity perturbations in protoplanetary disks from observed line centroids maps ν∘, by creating axially-symmetric centroid maps. It also derives 3D rotation curves in disk-centered cylindrical coordinates, and can estimate the disk orientation based on line data alone. It approximates the unit opacity surface of an axially symmetric disc by a series of cones whose orientations are fit to the observed velocity centroid in concentric radial domains, or regions, with the disc orientation and the rotation curve both optimized to fit ν∘ in each region. ConeRot extracts the perturbations directly from observations without strong assumptions about the underlying disk model and employs a reduced number of free parameters.
Consistent Trees generates merger trees and halo catalogs which explicitly ensure consistency of halo properties (mass, position, velocity, radius) across timesteps. It has demonstrated the ability to improve both the completeness (through detecting and inserting otherwise missing halos) and purity (through detecting and removing spurious objects) of both merger trees and halo catalogs. Consistent Trees is able to robustly measure the self-consistency of halo finders and to directly measure the uncertainties in halo positions, halo velocities, and the halo mass function for a given halo finder based on consistency between snapshots in cosmological simulations.
This program addresses the question of what resources are needed to produce a continuous data record of the entire sky down to a given limiting visual magnitude. Toward this end, the program simulates a small camera/telescope or group of small camera/telescopes collecting light from a large portion of the sky. From a given stellar density derived from a Bahcall - Soneira Galaxy model, the program first converts star densities at visual magnitudes between 5 and 20 to number of sky pixels needed to monitor each star simultaneously. From pixels, the program converts input CCD parameters to needed telescope attributes, needed data storage space, and the length of time needed to accumulate data of photometric quality for stars of each limiting visual magnitude over the whole sky. The program steps though photometric integrations one second at a time and includes the contribution from a bright background, read noise, dark current, and atmospheric absorption.
contaminante helps find the contaminant transiting source in NASA's Kepler, K2 or TESS data. When hunting for transiting planets, sometimes signals come from neighboring contaminants. This package helps users identify where the transiting signal comes from in their data. The code uses pixel level modeling of the TargetPixelFile data from NASA's astrophysics missions that are processed with the Kepler pipeline. The output of contaminante is a Python dictionary containing the source location and transit depth, and a contaminant location and depth. It can also output a figure showing where the main target is centered in all available TPFs, what the phase curve looks like for the main target, where the transiting source is centered in all available TPFs, if a transiting source is located outside the main target, or the transiting source phase curve, if a transiting source is located outside the main target.
Contbin bins X-ray data using contours on an adaptively smoothed map. The generated bins closely follow the surface brightness, and are ideal where the surface brightness distribution is not smooth, or the spectral properties are expected to follow surface brightness. Color maps can be used instead of surface brightness maps.
The IDL package convolve_image.pro transforms images between different instrumental point spread functions (PSFs). It can load an image file and corresponding kernel and return the convolved image, thus preserving the colors of the astronomical sources. Convolution kernels are available for images from Spitzer (IRAC MIPS), Herschel (PACS SPIRE), GALEX (FUV NUV), WISE (W1 - W4), Optical PSFs (multi- Gaussian and Moffat functions), and Gaussian PSFs; they allow the study of the Spectral Energy Distribution (SED) of extended objects and preserve the characteristic SED in each pixel.
ConvPhot measures colors between two images having different resolutions. ConvPhot is designed to work especially for faint galaxies, accurately measuring colors in relatively crowded fields. It makes full use of the spatial and morphological information contained in the highest quality images to analyze multiwavelength data with inhomogeneous image quality.
Copter is a software package for doing calculations in cosmological perturbation theory. Specifically, Copter includes code for computing statistical observables in the large-scale structure of matter using various forms of perturbation theory, including linear theory, standard perturbation theory, renormalized perturbation theory, and many others. Copter is written in C++ and makes use of the Boost C++ library headers.
CORA analyzes emission line spectra with low count numbers and fits them to a line using the maximum likelihood technique. CORA uses a rigorous application of Poisson statistics. From the assumption of Poissonian noise, the software derives the probability for a model of the emission line spectrum to represent the measured spectrum. The likelihood function is used as a criterion for optimizing the parameters of the theoretical spectrum and a fixed point equation is derived allowing an efficient way to obtain line fluxes. CORA has been applied to an X-ray spectrum with the Low Energy Transmission Grating Spectrometer (LETGS) on board the Chandra observatory.
CORBITS (Computed Occurrence of Revolving Bodies for the Investigation of Transiting Systems) computes the probability that any particular group of exoplanets can be observed to transit from a collection of conjectured exoplanets orbiting a star. The efficient, semi-analytical code computes the areas bounded by circular curves on the surface of a sphere by applying elementary differential geometry. CORBITS is faster than previous algorithms, based on comparisons with Monte Carlo simulations, and tests show that it is extremely accurate even for highly eccentric planets.
CoREAS is a Monte Carlo code for the simulation of radio emission from extensive air showers; it is an update of and successor code to REAS3 (ascl:1107.009). It implements the endpoint formalism for the calculation of electromagnetic radiation directly in CORSIKA (ascl:1202.006). As such, it is parameter-free, makes no assumptions on the emission mechanism for the radio signals, and takes into account the complete complexity of the electron and positron distributions as simulated by CORSIKA.
corner.py uses matplotlib to visualize multidimensional samples using a scatterplot matrix. In these visualizations, each one- and two-dimensional projection of the sample is plotted to reveal covariances. corner.py was originally conceived to display the results of Markov Chain Monte Carlo simulations and the defaults are chosen with this application in mind but it can be used for displaying many qualitatively different samples. An earlier version of corner.py was known as triangle.py.
Would you like to view a random code?