Results 1301-1350 of 2075 (2041 ASCL, 34 submitted)
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
GizmoAnalysis reads and analyzes N-body simulations run with the Gizmo code (ascl:1410.003). Written in Python 3, we developed it primarily to analyze FIRE simulations, though it is useable 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; generates region files for input to MUSIC (ascl:1311.011) to generate cosmological zoom-in initial conditions; computes rates of supernovae and stellar winds, including their nucleosynthetic yields, as used in FIRE simulations. Includes a Jupyter notebook tutorial.
GizmoAnalysis reads and analyzes N-body simulations run with the Gizmo code (ascl:1410.003). Written in Python, we developed it primarily to analyze FIRE simulations, though it is useable 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; generates region files for input to MUSIC (ascl:1311.011) to generate cosmological zoom-in initial conditions; computes rates of supernovae and stellar winds, including their nucleosynthetic yields, as used in FIRE simulations. Includes a Jupyter notebook tutorial.
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).
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.
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, a user-friendly, open-source, dynamical-spacetime GRMHD code, and is highly scalable, to tens of thousands of cores.
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:
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
GenPK generates the 3D matter power spectra for each particle species from a Gadget snapshot. Written in C++, it requires both FFTW3 and GadgetReader.
GENGA (Gravitational ENcounters with Gpu Acceleration) integrates planet and planetesimal dynamics in the late stage of planet formation and stability analyses of planetary systems. It uses mixed variable integration when the motion is a perturbed Kepler orbit and combines this with a direct N-body Bulirsch-Stoer method during close encounters. It supports three simulation modes: 1.) integration of up to 2048 massive bodies; 2.) integration with up to a million test particles; and 3.) parallel integration of a large number of individual planetary systems.
This general complex polynomial root solver, implemented in Fortran and further optimized for binary microlenses, uses a new algorithm to solve polynomial equations and is 1.6-3 times faster than the ZROOTS subroutine that is commercially available from Numerical Recipes, depending on application. The largest improvement, when compared to naive solvers, comes from a fail-safe procedure that permits skipping the majority of the calculations in the great majority of cases, without risking catastrophic failure in the few cases that these are actually required.
Gemini is a toolkit for analytical models of two-point correlations and inhomogeneous structure formation. It extends standard Press-Schechter theory to inhomogeneous situations, allowing a realistic, analytical calculation of halo correlations and bias.
The Gemini IRAF package processes observational data obtained with the Gemini telescopes. It is an external package layered upon IRAF and supports data from numerous instruments, including FLAMINGOS-2, GMOS-N, GMOS-S, GNIRS, GSAOI, NIFS, and NIRI. The Gemini IRAF package is organized into sub-packages; it contains a generic tools package, "gemtools", along with instrument-specific packages. The raw data from the Gemini facility instruments are stored as Multi-Extension FITS (MEF) files. Therefore, all the tasks in the Gemini IRAF package, intended for processing data from the Gemini facility instruments, are capable of handling MEF files.
Geant4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics.
gdr2_completeness queries Gaia DR2 TAP services and divides the queries into sub-queries chunked into arbitrary healpix bins. Downloaded data are formatted into arrays. Internal completeness is calculated by dividing the total starcount and starcounts with an applied cut (e.g., radial velocity measurement and good parallax). Independent determination of the external GDR2 completeness per healpix (level 6) and G magnitude bin (3 coarse bins: 8-12,12-15,15-18) is inferred from a crossmatch with 2MASS data. The overall completeness of a specific GDR2 sample can be approximated by multiplying the internal with the external completeness map, which is useful when data are compared to models thereof. Jupyter notebooks showcasing both utilities enable the user to easily construct the overall completeness for arbitrary samples of the GDR2 catalogue.
GBTIDL is an interactive package for reduction and analysis of spectral line data taken with the Robert C. Byrd Green Bank Telescope (GBT). The package, written entirely in IDL, consists of straightforward yet flexible calibration, averaging, and analysis procedures (the "GUIDE layer") modeled after the UniPOPS and CLASS data reduction philosophies, a customized plotter with many built-in visualization features, and Data I/O and toolbox functionality that can be used for more advanced tasks. GBTIDL makes use of data structures which can also be used to store intermediate results. The package consumes and produces data in GBT SDFITS format. GBTIDL can be run online and have access to the most recent data coming off the telescope, or can be run offline on preprocessed SDFITS files.
GBKFIT performs galaxy kinematic modeling. It can be used to extract morphological and kinematical properties of galaxies by fitting models to spatially resolved kinematic data. The software can also take beam smearing into account by using the knowledge of the line and point spread functions. GBKFIT can take advantage of many-core and massively parallel architectures such as multi-core CPUs and Graphics Processing Units (GPUs), making it suitable for modeling large-scale surveys of thousands of galaxies within a very seasonable time frame. GBKFIT features an extensible object-oriented architecture that supports arbitrary models and optimization techniques in the form of modules; users can write custom modules without modifying GBKFIT’s source code. The software is written in C++ and conforms to the latest ISO standards.
GBART is an improved version of the code for determining the orbital elements for spectroscopic binaries originally written by Bertiau & Grobben (1968).
GaussPy+ is a fully automated Gaussian decomposition package for emission line spectra. It is based on GaussPy (ascl:1907.019) and offers several improvements, including automating preparatory steps and providing an accurate noise estimation, improving the fitting routine, and providing a routine to refit spectra based on neighboring fit solutions. GaussPy+ handles complex emission and low to moderate signal-to-noise values.
GaussPy implements the Autonomous Gaussian Decomposition (AGD) algorithm, which uses computer vision and machine learning techniques to provide optimized initial guesses for the parameters of a multi-component Gaussian model automatically and efficiently. The speed and adaptability of AGD allow it to interpret large volumes of spectral data efficiently. Although it was initially designed for applications in radio astrophysics, AGD can be used to search for one-dimensional Gaussian (or any other single-peaked spectral profile)-shaped components in any data set. To determine how many Gaussian functions to include in a model and what their parameters are, AGD uses a technique called derivative spectroscopy. The derivatives of a spectrum can efficiently identify shapes within that spectrum corresponding to the underlying model, including gradients, curvature and edges.
GaussFit solves least squares and robust estimation problems; written originally for reduction of NASA Hubble Space Telescope data, it includes a complete programming language designed especially to formulate estimation problems, a built-in compiler and interpreter to support the programming language, and a built-in algebraic manipulator for calculating the required partial derivatives analytically. The code can handle nonlinear models, exact constraints, correlated observations, and models where the equations of condition contain more than one observed quantity. Written in C, GaussFit includes an experimental robust estimation capability so data sets contaminated by outliers can be handled simply and efficiently.
GAUSSCLUMPS decomposes a spectral map into Gaussian-shape clumps. The clump-finding algorithm decomposes a spectral data cube by iteratively removing 3-D Gaussians as representative clumps. GAUSSCLUMPS was originally a separate code distribution but is now a contributed package in GILDAS (ascl:1305.010). A reimplementation can also be found in CUPID (ascl:1311.007).
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