Results 901-1000 of 2551 (2505 ASCL, 46 submitted)
GenPK generates the 3D matter power spectra for each particle species from a Gadget snapshot. Written in C++, it requires both FFTW3 and GadgetReader.
Relativistic radiative transfer problems require the calculation of photon trajectories in curved spacetime. Programmed in Fortran, Geokerr uses a novel technique for rapid and accurate calculation of null geodesics in the Kerr metric. The equations of motion from the Hamilton-Jacobi equation are reduced directly to Carlson's elliptic integrals, simplifying algebraic manipulations and allowing all coordinates to be computed semi-analytically for the first time.
George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.
The GetData Project is the reference implementation of the Dirfile Standards, a filesystem-based, column-oriented database format for time-ordered binary data. Dirfiles provide a fast, simple format for storing and reading data, suitable for both quicklook and analysis pipelines. GetData provides a C API and bindings exist for various other languages. GetData is distributed under the terms of the GNU Lesser General Public License.
GetDist analyzes Monte Carlo samples, including correlated samples from Markov Chain Monte Carlo (MCMC). It offers a point and click GUI for selecting chain files, viewing plots, marginalized constraints, and LaTeX tables, and includes a plotting library for making custom publication-ready 1D, 2D, 3D-scatter, triangle and other plots. Its convergence diagnostics include correlation length and diagonalized Gelman-Rubin statistics, and the optimized kernel density estimation provides an automated optimal bandwidth choice for 1D and 2D densities with boundary and bias correction. It is available as a standalong package and with CosmoMC (ascl:1106.025).
getimages performs background derivation and image flattening for high-resolution images obtained with space observatories. It is based on median filtering with sliding windows corresponding to a range of spatial scales from the observational beam size up to a maximum structure width X. The latter is a single free parameter of getimages that can be evaluated manually from the observed image. The median filtering algorithm provides a background image for structures of all widths below X. The same median filtering procedure applied to an image of standard deviations derived from a background-subtracted image results in a flattening image. Finally, a flattened image is computed by dividing the background-subtracted by the flattening image. Standard deviations in the flattened image are now uniform outside sources and filaments. Detecting structures in such radically simplified images results in much cleaner extractions that are more complete and reliable. getimages also reduces various observational and map-making artifacts and equalizes noise levels between independent tiles of mosaicked images. The code (a Bash script) uses FORTRAN utilities from getsources (ascl:1507.014), which must be installed.
getsf extracts sources and filaments in astronomical images by separating their structural components, and is designed to handle multi-wavelength sets of images and very complex filamentary backgrounds. The method spatially decomposes the original images and separates the structural components of sources and filaments from each other and from their backgrounds, flattening their resulting images. It spatially decomposes the flattened components, combines them over wavelengths, and detects the positions of sources and skeletons of filaments. Finally, getsf measures the detected sources and filaments and creates the output catalogs and images. This universal and fully automated method has a single user-definable free parameter, which reduces to a minimum dependence of its results on the human factor.
getsources is a powerful multi-scale, multi-wavelength source extraction algorithm. It analyzes fine spatial decompositions of original images across a wide range of scales and across all wavebands, cleans those single-scale images of noise and background, and constructs wavelength-independent single-scale detection images that preserve information in both spatial and wavelength dimensions. getsources offers several advantages over other existing methods of source extraction, including the filtering out of irrelevant spatial scales to improve detectability, especially in the crowded regions and for extended sources, the ability to combine data over all wavebands, and the full automation of the extraction process.
The N-body code gevolution complies with general relativity principles at every step; it calculates all six metric degrees of freedom in Poisson gauge. N-body particles are evolved by solving the geodesic equation written in terms of a canonical momentum to remain valid for relativistic particles. gevolution can be extended to include different kinds of dark energy or modified gravity models, going beyond the usually adopted quasi-static approximation. A weak field expansion is the central element of gevolution; this permits the code to treat settings in which no strong gravitational fields appear, including arbitrary scenarios with relativistic sources as long as gravitational fields are not very strong. The framework is well suited for cosmology, but may also be useful for astrophysical applications with moderate gravitational fields where a Newtonian treatment is insufficient.
GFARGO is a GPU version of FARGO (ascl:1102.017). It is written in C and C for CUDA and runs only on NVIDIA’s graphics cards. Though it corresponds to the standard, isothermal version of FARGO, not all functionalities of the CPU version have been translated to CUDA. The code is available in single and double precision versions, the latter compatible with FERMI architectures. GFARGO can run on a graphics card connected to the display, allowing the user to see in real time how the fields evolve.
GGADT uses anomalous diffraction theory (ADT) to compute the differential scattering cross section (or the total cross sections as a function of energy) for a specified grain of arbitrary geometry (natively supports spheres, ellipsoids, and clusters of spherical monomers). It is written in Fortran 95. ADT is valid when the grain is large compared to the wavelength of incident light. GGADT can calculate either the integrated cross sections (absorption, scattering, extinction) as a function of energy, or it can calculate the differential scattering cross section as a function of scattering angle.
GGchem is a fast thermo-chemical equilibrium code with or without equilibrium condensation down to 100K. It can handle up to 40 elements (H, ..., Zr, and W), up to 1155 molecules, and up to 200 condensates (solids and liquids) from NIST-JANAF and SUPCRTBL. It offers a customized selection of elements, molecules, and condensates. The Fortran-90 code is very fast, and has a stable iterative solution scheme based on Newton-Raphson.
Ggm contains useful utilities for Gaussian gradient filtering of astronomical FITS images. It applies the Gaussian gradient magnitude filter to an input fits image, using a particular scale, sigma, in pixels. ggm cosmetically hides point sources in fits images by filling point sources with random values from the surrounding pixel region. It also provides an interactive tool to combine FITS images filtered on different scales.
GGobi is an open source visualization program for exploring high-dimensional data. It provides highly dynamic and interactive graphics such as tours, as well as familiar graphics such as the scatterplot, barchart and parallel coordinates plots. Plots are interactive and linked with brushing and identification.
GIBIS is a pixel-level simulator of the Gaia mission. It is intended to simulate how the Gaia instruments will observe the sky, using realistic simulations of the astronomical sources and of the instrumental properties. It is a branch of the global Gaia Simulator under development within the Gaia DPAC CU2 Group (Data Simulations). Access is currently restricted to Gaia DPAC teams.
Observations of disk galaxies at z~2 have demonstrated that turbulence driven by gravitational instability can dominate the energetics of the disk. GIDGET is a 1D simulation code, which we have made publicly available, that economically evolves these galaxies from z~2 to z~0 on a single CPU in a matter of minutes, tracking column density, metallicity, and velocity dispersions of gaseous and multiple stellar components. We include an H$_2$ regulated star formation law and the effects of stellar heating by transient spiral structure. We use this code to demonstrate a possible explanation for the existence of a thin and thick disk stellar population and the age-velocity dispersion correlation of stars in the solar neighborhood: the high velocity dispersion of gas in disks at z~2 decreases along with the cosmological accretion rate, while at lower redshift, the dynamically colder gas forms the low velocity dispersion stars of the thin disk.
GILDAS is a collection of software oriented toward (sub-)millimeter radioastronomical applications (either single-dish or interferometer). It has been adopted as the IRAM standard data reduction package and is jointly maintained by IRAM & CNRS. GILDAS contains many facilities, most of which are oriented towards spectral line mapping and many kinds of 3-dimensional data. The code, written in Fortran-90 with a few parts in C/C++ (mainly keyboard interaction, plotting, widgets), is easily extensible.
GIM2D (Galaxy IMage 2D) is an IRAF/SPP package written to perform detailed bulge/disk decompositions of low signal-to-noise images of distant galaxies in a fully automated way. GIM2D takes an input image from HST or ground-based telescopes and outputs a galaxy-subtracted image as well as a catalog of structural parameters.
Ginga is a viewer for astronomical data FITS (Flexible Image Transport System) files; the viewer centers around a FITS display widget which supports zooming and panning, color and intensity mapping, a choice of several automatic cut levels algorithms and canvases for plotting scalable geometric forms. In addition to this widget, the FITS viewer provides a flexible plugin framework for extending the viewer with many different features. A fairly complete set of "standard" plugins are provided for expected features of a modern viewer: panning and zooming windows, star catalog access, cuts, star pick/fwhm, thumbnails, and others. This viewer was written by software engineers at Subaru Telescope, National Astronomical Observatory of Japan, and is in use at that facility.
GIPSY is an acronym of Groningen Image Processing SYstem. It is a highly interactive software system for the reduction and display of astronomical data. It supports multi-tasking using a versatile user interface, it has an advanced data structure, a powerful script language and good display facilities based on the X Window system.
GIPSY consists of a number of components which can be divided into a number of classes:
GiRaFFE leverages the Einstein Toolkit's (ascl:1102.014) highly-scalable infrastructure to create large-scale simulations of magnetized plasmas in strong, dynamical spacetimes on adaptive-mesh refinement (AMR) grids. It is based on IllinoisGRMHD (ascl:2004.003), a user-friendly, open-source, dynamical-spacetime GRMHD code, and is highly scalable, to tens of thousands of cores.
GIST (Galaxy IFU Spectroscopy Tool) provides a convenient all-in-one framework for the scientific analysis of fully reduced, (integral-field) spectroscopic data, conducting all the steps from the preparation of input data to the scientific analysis and to the production of publication-quality plots. In its basic set-up, the GIST pipeline extracts stellar kinematics, performs an emission-line analysis, and derives stellar population properties from full spectral fitting and via the measurement of absorption line-strength indices by exploiting pPXF (ascl:1210.002)and GandALF routines. The pipeline is not specific to any instrument or analysis technique, and includes a dedicated visualization routine with a sophisticated graphical user interface for fully interactive plotting of all measurements, spectra, fits, and residuals, as well as star formation histories and the weight distribution of the models.
GIZMO is a flexible, multi-method magneto-hydrodynamics+gravity code that solves the hydrodynamic equations using a variety of different methods. It introduces new Lagrangian Godunov-type methods that allow solving the fluid equations with a moving particle distribution that is automatically adaptive in resolution and avoids the advection errors, angular momentum conservation errors, and excessive diffusion problems that seriously limit the applicability of “adaptive mesh” (AMR) codes, while simultaneously avoiding the low-order errors inherent to simpler methods like smoothed-particle hydrodynamics (SPH). GIZMO also allows the use of SPH either in “traditional” form or “modern” (more accurate) forms, or use of a mesh. Self-gravity is solved quickly with a BH-Tree (optionally a hybrid PM-Tree for periodic boundaries) and on-the-fly adaptive gravitational softenings. The code is descended from P-GADGET, itself descended from GADGET-2 (ascl:0003.001), and many of the naming conventions remain (for the sake of compatibility with the large library of GADGET work and analysis software).
GizmoAnalysis reads and analyzes N-body simulations run with the Gizmo code (ascl:1410.003). Written in Python, it was developed primarily to analyze FIRE simulations, though it is usable with any Gizmo snapshot files. It offers the following functionality: reads snapshot files and converts particle data to physical units; provides a flexible dictionary class to store particle data and compute derived quantities on the fly; plots images and properties of particles; and generates region files for input to MUSIC (ascl:1311.011) to generate cosmological zoom-in initial conditions. GizmoAnalysis also computes rates of supernovae and stellar winds, including their nucleosynthetic yields, as used in FIRE simulations. The software package includes a tutorial in a Jupyter notebook.
GLACiAR (GaLAxy survey Completeness AlgoRithm) estimates the completeness and selection functions in galaxy surveys. Tailored for multiband imaging surveys aimed at searching for high-redshift galaxies through the Lyman Break technique, the code can nevertheless be applied broadly. GLACiAR generates artificial galaxies that follow Sérsic profiles with different indexes and with customizable size, redshift and spectral energy distribution properties, adds them to input images, and measures the recovery rate.
GLADIS (GLobal Accretion Disk Instability Simulation) computes the time-dependent evolution of a black hole accretion disk, in one-dimensional, axisymmetric, vertically integrated scheme. The code solves two partial-differential equations of hydrodynamics for surface density and temperature evolution, i.e., given by viscous diffusion and energy conservation. Accretion disks can be subject to radiation-pressure instability if the stress tensor is proportional to the total (gas plus radiation) pressure. In the gas-pressure dominated case there is no instability. An intermediate case is provided in the code by the square root of the gas and total pressures. GLADIS is parallelized with MPI, and sample .ini and run command files are provided with the code.
glafic is a public software package for analyzing gravitational lensing. It offers many features including computations of various lens properties for many mass models, solving the lens equation using an adaptive grid algorithm, simulations of lensed extended images with PSF convolved, and efficient modeling of observed strong lens systems.
GLASS models strong gravitational lenses. It produces an ensemble of possible models that fit the observed input data and conform to certain constraints specified by the user. GLASS makes heavy use of the numerical routines provided by the numpy and scipy packages as well as the linear programming package GLPK. This latter package, and its Python interface, is provided with GLASS and installs automatically in the GLASS build directory.
GLEAM (Galaxy Line Emission and Absorption Modeling) fits Gaussian models to emission and absorption lines in large samples of 1D galaxy spectra. The code is tailored to work well without much human interaction on optical and infrared spectra in a wide range of instrument setups and signal-to-noise regimes. gleam will create a fits table with Gaussian line measurements, including central wavelength, width, height and amplitude, as well as estimates for the continuum under the line and the line flux, luminosity, equivalent width and velocity width. gleam will also, optionally, make plots of the spectrum with fitted lines overlaid.
GLESP is a pixelization scheme for the cosmic microwave background (CMB) radiation maps. This scheme is based on the Gauss-Legendre polynomials zeros and allows one to create strict orthogonal expansion of the map.
Glimpse, also known as Glimpse2D, is a weak lensing mass-mapping tool that relies on a robust sparsity-based regularization scheme to recover high resolution convergence from either gravitational shear alone or from a combination of shear and flexion. Including flexion allows the supplementation of the shear on small scales in order to increase the sensitivity to substructures and the overall resolution of the convergence map. To preserve all available small scale information, Glimpse avoids any binning of the irregularly sampled input shear and flexion fields and treats the mass-mapping problem as a general ill-posed inverse problem, regularized using a multi-scale wavelet sparsity prior. The resulting algorithm incorporates redshift, reduced shear, and reduced flexion measurements for individual galaxies and is made highly efficient by the use of fast Fourier estimators.
Glnemo2 is an interactive 3D visualization program developed in C++ using the OpenGL library and Nokia QT 4.X API. It displays in 3D the particles positions of the different components of an nbody snapshot. It quickly gives a lot of information about the data (shape, density area, formation of structures such as spirals, bars, or peanuts). It allows for in/out zooms, rotations, changes of scale, translations, selection of different groups of particles and plots in different blending colors. It can color particles according to their density or temperature, play with the density threshold, trace orbits, display different time steps, take automatic screenshots to make movies, select particles using the mouse, and fly over a simulation using a given camera path. All these features are accessible from a very intuitive graphic user interface.
Glnemo2 supports a wide range of input file formats (Nemo, Gadget 1 and 2, phiGrape, Ramses, list of files, realtime gyrfalcON simulation) which are automatically detected at loading time without user intervention. Glnemo2 uses a plugin mechanism to load the data, so that it is easy to add a new file reader. It's powered by a 3D engine which uses the latest OpenGL technology, such as shaders (glsl), vertex buffer object, frame buffer object, and takes in account the power of the graphic card used in order to accelerate the rendering. With a fast GPU, millions of particles can be rendered in real time. Glnemo2 runs on Linux, Windows (using minGW compiler), and MaxOSX, thanks to the QT4API.
Understanding diffuse Galactic radio emission is interesting both in its own right and for minimizing foreground contamination of cosmological measurements. Cosmic Microwave Background experiments have focused on frequencies > 10 GHz, whereas 21 cm tomography of the high redshift universe will mainly focus on < 0.2 GHz, for which less is currently known about Galactic emission. Motivated by this, we present a global sky model derived from all publicly available total power large-area radio surveys, digitized with optical character recognition when necessary and compiled into a uniform format, as well as the new Villa Elisa data extending the 1.4 GHz map to the entire sky. We quantify statistical and systematic uncertainties in these surveys by comparing them with various global multi-frequency model fits. We find that a principal component based model with only three components can fit the 11 most accurate data sets (at 10, 22, 45 & 408 MHz and 1.4, 2.3, 23, 33, 41, 61, 94 GHz) to an accuracy around 1%-10% depending on frequency and sky region. The data compilation and software returning a predicted all-sky map at any frequency from 10 MHz to 100 GHz are publicly available in the archive file at the link below.
globalemu emulates the Global or sky averaged 21-cm signal and the associated neutral fraction history. The code can train a network on your own Global 21-cm signal or neutral fraction simulations using the built-in globalemu pre-processing techniques. It also features a GUI that can be invoked from the command line and used to explore how the structure of the Global 21-cm signal varies with the values of the astrophysical inputs.
The Lomb-Scargle periodogram is a common tool in the frequency analysis of unequally spaced data equivalent to least-squares fitting of sine waves. GLS is a solution for the generalization to a full sine wave fit, including an offset and weights (χ2 fitting). Compared to the Lomb-Scargle periodogram, GLS is superior as it provides more accurate frequencies, is less susceptible to aliasing, and gives a much better determination of the spectral intensity.
Glue, written in Python, links visualizations of scientific datasets across many files, allowing for interactive, linked statistical graphics of multiple files. It supports many file formats including common image formats (jpg, tiff, png), ASCII tables, astronomical image and table formats (FITS, VOT, IPAC), and HDF5. Custom data loaders can also be easily added. Glue is highly scriptable and extendable.
GMCALab solves Blind Source Separation (BSS) problems from multichannel/multispectral/hyperspectral data. In essence, multichannel data provide different observations of the same physical phenomena (e.g. multiple wavelengths), which are modeled as a linear combination of unknown elementary components or sources. Written as a set of Matlab toolboxes, it provides a generic framework that can be extended to tackle different matrix factorization problems.
GMM (Gaussian Mixture Modeling) tests the existence of bimodality in globular cluster color distributions. GMM uses three indicators to distinguish unimodal and bimodal distributions: the kurtosis of the distribution, the separation of the peaks, and the probability of obtaining the same χ2 from a unimodal distribution.
gnm is an implementation of the affine-invariant sampler for Markov chain Monte Carlo (MCMC) that uses the Gauss-Newton-Metropolis (GNM) Algorithm. The GNM algorithm is specialized in sampling highly non-linear posterior probability distribution functions of the form exp(-||f(x)||^2/2). The code includes dynamic hyper-parameter optimization to increase performance of the sampling; other features include the Jacobian tester and an error bars creator.
Gnuastro (GNU Astronomy Utilities) manipulates and analyzes astronomical data. It is an official GNU package of a large collection of programs and C/C++ library functions. Command-line programs perform arithmetic operations on images, convert FITS images to common types like JPG or PDF, convolve an image with a given kernel or matching of kernels, perform cosmological calculations, crop parts of large images (possibly in multiple files), manipulate FITS extensions and keywords, and perform statistical operations. In addition, it contains programs to make catalogs from detection maps, add noise, make mock profiles with a variety of radial functions using monte-carlo integration for their centers, match catalogs, and detect objects in an image among many other operations. The command-line programs share the same basic command-line user interface for the comfort of both the users and developers. Gnuastro is written to comply fully with the GNU coding standards and integrates well with all Unix-like operating systems. This enables astronomers to expect a fully familiar experience in the source code, building, installing and command-line user interaction that they have seen in all the other GNU software that they use. Gnuastro's extensive library is included for users who want to build their own unique programs.
GoFish exploits the known rotation of a protoplanetary disk to shift all emission to a common line center in order to stack them, increasing the signal-to-noise of the spectrum, detecting weaker lines, or super-sampling the spectrum to better resolve the line profile.
GOSSIP fits the electro-magnetic emission of an object (the SED, Spectral Energy Distribution) against synthetic models to find the simulated one that best reproduces the observed data. It builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a chi-square minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions.
gotetra uses phase-space tesselation techniques to extract information about cosmological N-body simulations. The key applications of this Go-based code are the measurement of splashback shells around halos and the generation of high resolution images of density fields. The package includes routines to generates 3D and 2D (projected) density fields from a particle snapshot generated by a cosmological N-body simulation, measure density along lines of sight from the center of halos, and compresse the position space data from cosmological N-body simulations. Included are two helper libraries with functions for calculating cosmological quantities and computing a number of useful mathematical functions.
GOTHIC (Graph-bOosTed iterated HIll Climbing) detects whether a given image of a galaxy has characteristic features of a double nuclei galaxy (DNG). Galaxy interactions and mergers play a crucial role in the hierarchical growth of structure in the universe; galaxy mergers can lead to the formation of elliptical galaxies and larger disk galaxies, as well as drive galaxy evolution through star formation and nuclear activity. During mergers, the nuclei of the individual galaxies come closer and finally form a double nuclei galaxy. Although mergers are common, the detection of double-nuclei galaxies (DNGs) is rare and fairly serendipitous. Their properties can help us understand the formation of supermassive black hole (SMBH) binaries, dual active galactic nuclei (DAGN) and the associated feedback effects. GOTHIC provides an automatic and systematic way to survey data for the discovery of double nuclei galaxies.
The two-point correlation function is a simple statistic that quantifies the clustering of a given distribution of objects. In studies of the large scale structure of the Universe, it is an important tool containing information about the matter clustering and the evolution of the Universe at different cosmological epochs. A classical application of this statistic is the galaxy-galaxy correlation function to find constraints on the parameter Omega_m or the location of the baryonic acoustic oscillation peak. This calculation, however, is very expensive in terms of computer power and Graphics Processing Units provide one solution for efficient analysis of the increasingly larger galaxy surveys that are currently taking place.
GP2PCF is a public code in CUDA for performing this computation; with a single GPU board it is possible to achieve 120-fold speedups with respect to a standard implementation in C running on a single CPU. With respect to other solutions such as k-trees the improvement is of a factor of a few retaining full precision. The speedup is comparable to running in parallel in a cluster of O(100) cores.
The University of Manchester GPC library is a flexible and highly robust polygon set operations library for use with C, C#, Delphi, Java, Perl, Python, Haskell, Lua, VB.Net and other applications. It supports difference, intersection, exclusive-or and union clip operations, and polygons may be comprised of multiple disjoint contours. Contour vertices may be given in any order - clockwise or anticlockwise, and contours may be convex, concave or self-intersecting, and may be nested (i.e. polygons may have holes). Output may take the form of either polygon contours or tristrips, and hole and external contours are differentiated in the result. GPC is free for non-profit and educational use; a Commercial Use License is required for commercial use.
Internet Archive link provided for archival purposes; per its website, GPC is no longer distributed or available as of August 2020.
GPCAL performs instrumental polarization calibration in very long baseline interferometry (VLBI) data. It enhances the calibration accuracy by enabling users to fit the model to multiple calibrators data simultaneously and to take into account the calibrators linear polarization structures instead of using the conventional similarity assumption. GPCAL is based on AIPS (ascl:9911.003) and uses ParselTongue (ascl:1208.020) to run AIPS tasks.
Written in Python, gPhoton calibrates and sky-projects the ~1.1 trillion ultraviolet photon events detected by the microchannel plates on the Galaxy Evolution Explorer Spacecraft (GALEX), archives these events in a publicly accessible database at the Mikulski Archive for Space Telescopes (MAST), and provides tools for working with the database to extract scientific results, particularly over short time domains. The software includes a re-implementation of core functionality of the GALEX mission calibration pipeline to produce photon list files from raw spacecraft data as well as a suite of command line tools to generate calibrated light curves, images, and movies from the MAST database.
The GPI data pipeline allows users to reduce and calibrate raw GPI data into spectral and polarimetric datacubes, and to apply various PSF subtraction methods to those data. Written in IDL and available in a compiled version, the software includes an integrated calibration database to manage reference files and an interactive data viewer customized for high contrast imaging that allows exploration and manipulation of data.
GPU-D is a GPU-accelerated implementation of the inverse ray-shooting technique used to generate cosmological microlensing magnification maps. These maps approximate the source plane magnification patterns created by an ensemble of stellar-mass compact objects within a foreground macrolens galaxy. Unlike other implementations, GPU-D solves the gravitational lens equation without any approximation. Due to the high computational intensity and high degree of parallelization inherent in the algorithm, it is ideal for brute-force implementation on GPUs. GPU-D uses CUDA for GPU acceleration and require NVIDIA devices to run.
The maximum entropy method (MEM) is a well known deconvolution technique in radio-interferometry. This method solves a non-linear optimization problem with an entropy regularization term. Other heuristics such as CLEAN are faster but highly user dependent. Nevertheless, MEM has the following advantages: it is unsupervised, it has a statistical basis, it has a better resolution and better image quality under certain conditions. GPUVMEM presents a high performance GPU version of non-gridding MEM.
GR1D is based on the Eulerian formulation of GR hydrodynamics (GRHD) put forth by Romero-Ibanez-Gourgoulhon and employs radial-gauge, polar-slicing coordinates in which the 3+1 equations simplify substantially. GR1D is intended for the simulation of stellar collapse to neutron stars and black holes and will also serve as a testbed for modeling technology to be incorporated in multi-D GR codes. Its GRHD part is coupled to various finite-temperature microphysical equations of state in tabulated form that we make available with GR1D.
The chemistry and radiative cooling library Grackle provides options for primordial chemistry and cooling, photo-heating and photo-ionization from UV backgrounds, and support for user-provided arrays of volumetric and specific heating rates for astrophysical simulations and models. The library provides functions to update chemistry species; solve radiative cooling and update internal energy; and calculate cooling time, temperature, pressure, and ratio of specific heats (gamma), and has interfaces for C, C++, Fortran, and Python codes.
The GRACOS (GRAvitational COSmology) code, a parallel implementation of the particle-particle/particle-mesh (P3M) algorithm for distributed memory clusters, uses a hybrid method for both computation and domain decomposition. Long-range forces are computed using a Fourier transform gravity solver on a regular mesh; the mesh is distributed across parallel processes using a static one-dimensional slab domain decomposition. Short-range forces are computed by direct summation of close pairs; particles are distributed using a dynamic domain decomposition based on a space-filling Hilbert curve. A nearly-optimal method was devised to dynamically repartition the particle distribution so as to maintain load balance even for extremely inhomogeneous mass distributions. Tests using $800^3$ simulations on a 40-processor beowulf cluster showed good load balance and scalability up to 80 processes. There are limits on scalability imposed by communication and extreme clustering which may be removed by extending the algorithm to include adaptive mesh refinement.
This paper describes the generation of initial conditions for numerical simulations in cosmology with multiple levels of resolution, or multiscale simulations. We present the theory of adaptive mesh refinement of Gaussian random fields followed by the implementation and testing of a computer code package performing this refinement called GRAFIC-2.
We present a non-parametric technique to infer the projected-mass distribution of a gravitational lens system with multiple strong-lensed images. The technique involves a dynamic grid in the lens plane on which the mass distribution of the lens is approximated by a sum of basis functions, one per grid cell. We used the projected mass densities of Plummer spheres as basis functions. A genetic algorithm then determines the mass distribution of the lens by forcing images of a single source, projected back onto the source plane, to coincide as well as possible. Averaging several tens of solutions removes the random fluctuations that are introduced by the reproduction process of genomes in the genetic algorithm and highlights those features common to all solutions. Given the positions of the images and the redshifts of the sources and the lens, we show that the mass of a gravitational lens can be retrieved with an accuracy of a few percent and that, if the sources sufficiently cover the caustics, the mass distribution of the gravitational lens can also be reliably retrieved. A major advantage of the algorithm is that it makes full use of the information contained in the radial images, unlike methods that minimise the residuals of the lens equation, and is thus able to accurately reconstruct also the inner parts of the lens.
Gramsci (GRAph Made Statistics for Cosmological Information) computes the general N-point spatial correlation functions of any discrete point set embedded within an Euclidean space of ℝ^n. It uses kd-trees and graph databases to count all possible N-tuples in binned configurations within a given length scale, e.g. all pairs of points or all triplets of points with side lengths. Gramsci can run in serial, OpenMP, MPI and hybrid parallel schemes. It is useful for performing domain decomposition of input catalogs, especially if the catalogs are large or the Rmax value is too large.
GRAND-HOD (GeneRalized ANd Differentiable Halo Occupation Distribution) takes a generalized Halo Occupation Distribution (HOD) prescription as input and outputs the corresponding mock galaxy catalogs in binary files. The code is differentiable and incorporates various generalizations to the standard HOD. It is written for the Abacus simulations, but the main functionalities can be easily adapted for other halo catalogs with the appropriate properties.
GRAPUS (GRAvitational instability PopUlation Synthesis) executes population synthesis modeling of self-gravitating disc fragmentation and tidal downsizing in protostellar discs. It reads in pre-run 1D viscous disc models of self-gravitating discs and computes where fragmentation will occur and the initial fragment mass. GRAPUS then allows these fragment embryos to evolve under various forces, including quasistatic collapse of the embryo, growth and sedimentation of the dust inside the embryo, and the formation of solid cores. The software also evolves migration due to embryo-disc interactions and tidal disruption of the embryo, and can optionally determine gravitational interactions with neighboring embryos.
GRASIL (which stands for GRAphite and SILicate) computes the spectral evolution of stellar systems taking into account the effects of dust, which absorbs and scatters optical and UV photons and emits in the IR-submm region. It may be used as well to do “standard” no-dust stellar spectral synthesis. The code is very well calibrated and applied to interpret galaxies at different redshifts. GRASIL can be downloaded or run online using the GALSYNTH WEB interface.
GRASP (General-purpose Relativistic Atomic Structure Package) calculates atomic structure, including energy levels, radiative rates (A-values) and lifetimes; it is a fully relativistic code based on the jj coupling scheme. This code has been superseded by GRASP2K (ascl:1611.007).
GRASP2K is a revised and greatly expanded version of GRASP (ascl:1609.008) and is adapted for 64-bit computer architecture. It includes new angular libraries, can transform from jj- to LSJ-coupling, and coefficients of fractional parentage have been extended to j=9/2, making calculations feasible for the lanthanides and actinides. GRASP2K identifies each atomic state by the total energy and a label for the configuration state function with the largest expansion coefficient in LSJLSJ intermediate coupling.
GraviDy performs N-body 3D visualizations; it is a GPU, direct-summation N-body integrator based on the Hermite scheme and includes relativistic corrections for sources of gravitational radiation. The software is modular, allowing users to readily introduce new physics, and exploits available computational resources. The software can be used in parallel on multiple CPUs and GPUs, with a considerable speed-up benefit. The single-GPU version is between one and two orders of magnitude faster than the single-CPU version.
Modern applications of strong gravitational lensing require the ability to use precise and varied observational data to constrain complex lens models. Two sets of computational methods for lensing calculations are discussed. The first is a new algorithm for solving the lens equation for general mass distributions. This algorithm makes it possible to apply arbitrarily complicated models to observed lenses. The second is an evaluation of techniques for using observational data including positions, fluxes, and time delays of point-like images, as well as maps of extended images, to constrain models of strong lenses. The techniques presented here are implemented in a flexible and user-friendly software package called gravlens, which is made available to the community.
GRay is a massive parallel ordinary differential equation integrator that employs the "stream processing paradigm." It is designed to efficiently integrate billions of photons in curved spacetime according to Einstein's general theory of relativity. The code is implemented in CUDA C/C++.
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.
GRID-core is a core-finding method using the contours of the local gravitational potential to identify core boundaries. The GRID-core method applied to 2D surface density and 3D volume density are in good agreement for bound cores. We have implemented a version of the GRID-core algorithm in IDL, suitable for core-finding in observed maps. The required input is a two-dimensional FITS file containing a map of the column density in a region of a cloud.
GRIM (General Relativistic Implicit Magnetohydrodynamics) evolves a covariant extended magnetohydrodynamics model derived by treating non-ideal effects as a perturbation of ideal magnetohydrodynamics. Non-ideal effects are modeled through heat conduction along magnetic field lines and a difference between the pressure parallel and perpendicular to the field lines. The model relies on an effective collisionality in the disc from wave-particle scattering and velocity-space (mirror and firehose) instabilities. GRIM, which runs on CPUs as well as on GPUs, combines time evolution and primitive variable inversion needed for conservative schemes into a single step using only the residuals of the governing equations as inputs. This enables the code to be physics agnostic as well as flexible regarding time-stepping schemes.
GriSPy (Grid Search in Python) uses a regular grid search algorithm for quick fixed-radius nearest-neighbor lookup. It indexes a set of k-dimensional points in a regular grid providing a fast approach for nearest neighbors queries. Optional periodic boundary conditions can be provided for each axis individually. GriSPy implements three types of queries: bubble, shell and the nth-nearest, and offers three different metrics of interest in astronomy: the Euclidean and two distance functions in spherical coordinates of varying precision, haversine and Vincenty. It also provides a custom distance function. GriSPy is particularly useful for large datasets where a brute-force search is not practical.
Grizli produces quantitative and comprehensive modeling and fitting of slitless spectroscopic observations, which typically involve overlapping spectra of hundreds or thousands of objects in exposures taken with one or more separate grisms and at multiple dispersion position angles. This type of analysis provides complete and uniform characterization of the spectral properties (e.g., continuum shape, redshifts, line fluxes) of all objects in a given exposure taken in the slitless spectroscopic mode.
grmonty is a Monte Carlo radiative transport code intended for calculating spectra of hot, optically thin plasmas in full general relativity. The code models hot accretion flows in the Kerr metric, it incorporates synchrotron emission and absorption and Compton scattering. grmonty can be readily generalized to account for other radiative processes and an arbitrary spacetime.
Growl calculates the linear growth factor Da and its logarithmic derivative dln D/dln a in expanding Friedmann-Robertson-Walker universes with arbitrary matter and vacuum densities. It permits rapid and stable numerical evaluation.
grtrans calculates ray tracing radiative transfer in the Kerr metric, including the full treatment of polarised radiative transfer and parallel transport along geodesics, for comparing theoretical models of black hole accretion flows and jets with observations. The code is written in Fortran 90 and parallelizes with OpenMP; the full code and several components have Python interfaces. grtrans includes Geokerr (ascl:1011.015) and requires cfitsio (ascl:1010.001) and pyfits (ascl:1207.009).
The GSD library reads data written in the James Clerk Maxwell Telescope GSD format. This format uses the General Single-Dish Data model and was used at the JCMT until 2005. The library provides an API to open GSD files and read their contents. The content of the data files is self-describing and the library can return the type and name of any component. The library is used by SPECX (ascl:1310.008), JCMTDR (ascl:1406.019) and COADD (ascl:1411.020). The SMURF (ascl:1310.007) package can convert GSD heterodyne data files to ACSIS format using this library.
gsf applies Gaussian Mixture Models in the stellar kinematic space of normalized angular momentum and binding energy on NIHAO high resolution galaxies to separate the stars into multiple components. The gsf analysis package assumes that the simulation snapshot has been pre-processed with a halo finder. It is based on pynbody (ascl:1305.002) and the scikit-learnpython package for Machine Learning; after loading, orienting, and transforming a simulation snapshot to physical units, it runs the clustering algorithm and performs the direct N-body gravity force using all the particles in the given halo.
GSGS does phase retrieval on images given an estimate of the pupil phase (from a non-redundant mask or other interferometric approach), the pupil geometry, and the in-focus image. The code uses a modified Gerchberg-Saxton algorithm that iterates between pupil plane and image plane to measure the pupil phase.
GSpec analyzes the Fermi mission's Gamma-ray Burst Monitor (GBM) data via a user-interactive GUI. The software provides a seamless interface to XSPEC (ascl:9910.005). It allows users to create their own Python scripts using the included libraries, and to define additional data reduction techniques, such as background fitting/estimation and data binning, as Python-based plugins. It is part of a larger effort to produce a set of GBM data tools to allow the broader community to analyze all aspects of GBM data, including the continuous data that GBM produces. GSpec is similar to RMfit (ascl:1409.011), a GUI-based spectral analysis code that specializes in the analysis of GBM trigger data, and is intended to eventually replace that IDL package.
GWecc computes the pulsar timing array (PTA) signals induced by eccentric supermassive binaries. Written in C++, it computes the plus/cross polarizations as well as Earth and pulsar terms of the PTA signal given the binary parameters and the sky locations of the binary and the pulsar. A python wrapper is included through which GWecc can be used to simulate, search for and constrain gravitational wave-emitting eccentric supermassive binaries using packages such as ENTERPRISE (ascl:1912.015) and libstempo (ascl:2002.017).
GWFrames eliminates all rotational behavior, thus simplifying the waveform as much as possible and allowing direct generalizations of methods for analyzing nonprecessing systems. In the process, the angular velocity of a waveform is introduced, which also has important uses, such as supplying a partial solution to an important inverse problem.
The Python package GWpy analyzes and characterizes gravitational wave data. It provides a user-friendly, intuitive interface to the common time-domain and frequency-domain data produced by the LIGO and Virgo observatories and their analyses. The core Python infrastructure is influenced by, and extends the functionality of, the Astropy (ascl:1304.002) package, and its methodology has been derived from, and augmented by, the LIGO Algorithm Library Suite (LALSuite), a large collection of primarily C99 routines for analysis and manipulation of data from gravitational-wave detectors. These packages use the SWIG program to produce Python wrappings for all C modules, allowing the GWpy package to leverage both the completeness, and the speed, of these libraries.
GYOTO, a general relativistic ray-tracing code, aims at computing images of astronomical bodies in the vicinity of compact objects, as well as trajectories of massive bodies in relativistic environments. This code is capable of integrating the null and timelike geodesic equations not only in the Kerr metric, but also in any metric computed numerically within the 3+1 formalism of general relativity. Simulated images and spectra have been computed for a variety of astronomical targets, such as a moving star or a toroidal accretion structure. The underlying code is open source and freely available. It is user-friendly, quickly handled and very modular so that extensions are easy to integrate. Custom analytical metrics and astronomical targets can be implemented in C++ plug-in extensions independent from the main code.
GYRE is an oscillation code that solves the stellar pulsation equations (both adiabatic and non-adiabatic) using a novel Magnus Multiple Shooting numerical scheme devised to overcome certain weaknesses of the usual relaxation and shooting schemes. The code is accurate (up to 6th order in the number of grid points), robust, and makes efficient use of multiple processor cores and/or nodes.
gyrfalcON (GalaxY simulatoR using falcON) is a full-fledged N-body code using Dehnen’s force algorithm of complexity O(N) (falcON); this algorithm is approximately 10 times faster than an optimally coded tree code. The code features individual adaptive time steps and individual (but fixed) softening lengths. gyrfalcON is included in and requires NEMO to run.
HADES analyzse dust levels in simulated CMB galactic dust maps with realistic experimental noise and lensing configurations. It allows detection of dust via its anisotropy properties in CMB B-modes. It also includes techniques for computing null-tests and a rudimentary technique for dedusting.
HaloAnalysis reads and analyzes halo/galaxy catalogs, generated from Rockstar (ascl:1210.008) or AHF (ascl:1102.009), and merger trees generated from Consistent Trees (ascl:1210.011). Written in Python, it offers the following functionalities: reads halo/galaxy/tree catalogs from multiple file formats; assigns baryonic particles and galaxy properties to dark-matter halos; combines and re-generates halo/galaxy/tree files in hdf5 format; analyzes properties of halos/galaxies; and selects halos to generate zoom-in initial conditions. The code includes a tutorial in the form of a Jupyter notebook.
HALOFIT provides an explanatory framework for galaxy bias and clustering and has been incorporated into CMB packages such as CMBFAST (ascl:9909.004) and CAMB (ascl:1102.026). It attains a reasonable level of precision, though the halo model does not match N-body data perfectly. The code is written in Fortran 77. HALOFIT tends to underpredict the power on the smallest scales in standard LCDM universes (although HALOFIT was designed to work for a much wider range of power spectra); its accuracy can be improved by using a supplied correction.
We perform N-body simulations of theories with infinite-volume extra dimensions, such as the Dvali-Gabadadze-Porrati (DGP) model and its higher-dimensional generalizations, where 4D gravity is mediated by massive gravitons. The longitudinal mode of these gravitons mediates an extra scalar force, which we model as a density-dependent modification to the Poisson equation. This enhances gravitational clustering, particularly on scales that have undergone mild nonlinear processing. While the standard non-linear fitting algorithm of Smith et al. overestimates this power enhancement on non-linear scales, we present a modified fitting formula that offers a remarkably good fit to our power spectra. Due to the uncertainty in galaxy bias, our results are consistent with precision power spectrum determinations from galaxy redshift surveys, even for graviton Compton wavelengths as small as 300 Mpc. Our model is sufficiently general that we expect it to capture the phenomenology of a wide class of related higher-dimensional gravity scenarios.
HALOGEN generates approximate synthetic halo catalogs. Written in C, it decomposes the problem of generating cosmological tracer distributions (eg. halos) into four steps: generating an approximate density field, generating the required number of tracers from a CDF over mass, placing the tracers on field particles according to a bias scheme dependent on local density, and assigning velocities to the tracers based on velocities of local particles. It also implements a default set of four models for these steps. HALOGEN uses 2LPTic (ascl:1201.005) and CUTE (ascl:1505.016); the software is flexible and can be adapted to varying cosmologies and simulation specifications.
HaloGen computes all auto and cross spectra and halo model trispectrum in simple configurations. This modular halo model code computes 3d power spectra, and the corresponding projected 2d power spectra in the Limber and flat sky approximations. The observables include matter density, galaxy lensing, CMB lensing, thermal Sunyaev-Zel'dovich, cosmic infrared background, tracers with any dn/dz, b(z) and HOD.
Halogen, written in C, generates multimass spherically symmetric initial conditions for N-body simulations. A large family of radial density profiles is supported. The initial conditions are sampled from the full distribution function.
halomod calculates cosmological halo model and HOD quantities. It is built on HMF (ascl:1412.006); it retains that code's features and provides extended components for the halo model, including numerous halo bias models, including scale-dependent bias, basic concentration-mass-redshift relations, and several plug-and-play halo-exclusion models. halomod includes built-in HOD parameterizations and halo profiles, support for WDM models, and all basic quantities such as 3D correlations and power spectra, and also several derived quantities such as effective bias and satellite fraction. In addition, it offers a simple routine for populating a halo catalog with galaxies via a HOD. halomod is flexible and modular, making it easily extendable.
Halotools builds and tests models of the galaxy-halo connection and analyzes catalogs of dark matter halos. The core functions of the package include fast generation of synthetic galaxy populations using HODs, abundance matching, and related methods; efficient algorithms for calculating galaxy clustering, lensing, z-space distortions, and other astronomical statistics; a modular, object-oriented framework for designing galaxy evolution models; and end-to-end support for reducing halo catalogs and caching them as hdf5 files.
HAM solves non-relativistic hyperbolic partial differential equations in conservative form using high-resolution shock-capturing techniques. This version of HAM has been configured to solve the magnetohydrodynamic equations of motion in axisymmetry to evolve a shearing box model.
The Hammurabi code is a publicly available C++ code for generating mock polarized observations of Galactic synchrotron emission with telescopes such as LOFAR, SKA, Planck, and WMAP, based on model inputs for the Galactic magnetic field (GMF), the cosmic-ray density distribution, and the thermal electron density. The Hammurabi code allows one to perform simulations of several different data sets simultaneously, providing a more reliable constraint of the magnetized ISM.
HAOS-DIPER works with and manipulates data for neutral atoms and atomic ions to understand radiation emitted by some space plasmas, notably the solar atmosphere and stellar atmospheres. HAOS-DIPER works with quantum numbers for atomic levels, enabling it to perform tasks otherwise difficult or very tedious, including a variety of data checks, calculations based upon the atomic numbers, and searching and manipulating data based upon these quantum numbers. HAOS-DIPER handles conditions from LTE to coronal-like conditions, in a manner controlled by one system variable !REGIME, and has some capability for estimating data for which no accurate parameters are available and for accounting for the effects of missing atomic levels.
hardCORE calculates the minimum, maximum, and marginal core radius fractions (CRFmin, CRFmax, CRFmarg) for a solid exoplanet using only its mass and radius. Written in Python, the code is an efficient tool that is extremely fast to execute and perform inversions.
HARM uses a conservative, shock-capturing scheme for evolving the equations of general relativistic magnetohydrodynamics. The fluxes are calculated using the Harten, Lax, & van Leer scheme. A variant of constrained transport, proposed earlier by Tóth, is used to maintain a divergence-free magnetic field. Only the covariant form of the metric in a coordinate basis is required to specify the geometry. On smooth flows HARM converges at second order.
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