Results 1951-2000 of 2121 (2090 ASCL, 31 submitted)
Barcode (BAyesian Reconstruction of COsmic DEnsity fields) samples the primordial density fields compatible with a set of dark matter density tracers after cosmic evolution observed in redshift space. It uses a redshift space model based on the analytic solution of coherent flows within a Hamiltonian Monte Carlo posterior sampling of the primordial density field; this method is applicable to analytically derivable structure formation models, such as the Zel'dovich approximation, but also higher order schemes such as augmented Lagrangian perturbation theory or even particle mesh models. The algorithm is well-suited for analysis of the dark matter cosmic web implied by the observed spatial distribution of galaxy clusters, such as obtained from X-ray, SZ or weak lensing surveys, as well as that of the intergalactic medium sampled by the Lyman alpha forest. In these cases, virialized motions are negligible and the tracers cannot be modeled as point-like objects. Barcode can be used in all of these contexts as a baryon acoustic oscillation reconstruction algorithm.
BAOlab is an image processing package written in C that should run on nearly any UNIX system with just the standard C libraries. It reads and writes images in standard FITS format; 16- and 32-bit integer as well as 32-bit floating-point formats are supported. Multi-extension FITS files are currently not supported. Among its tools are ishape for size measurements of compact sources, mksynth for generating synthetic images consisting of a background signal including Poisson noise and a number of pointlike sources, imconvol for convolving two images (a “source” and a “kernel”) with each other using fast fourier transforms (FFTs) and storing the output as a new image, and kfit2d for fitting a two-dimensional King model to an image.
Using the 2-point correlation function, BAOlab aids the study of Baryon Acoustic Oscillations (BAO). The code generates a model-dependent covariance matrix which can change the results both for BAO detection and for parameter constraints.
BANYAN_Sigma calculates the membership probability that a given astrophysical object belongs to one of the currently known 27 young associations within 150 pc of the Sun, using Bayesian inference. This tool uses the sky position and proper motion measurements of an object, with optional radial velocity (RV) and distance (D) measurements, to derive a Bayesian membership probability. By default, the priors are adjusted such that a probability threshold of 90% will recover 50%, 68%, 82% or 90% of true association members depending on what observables are input (only sky position and proper motion, with RV, with D, with both RV and D, respectively). The algorithm is implemented in a Python package, in IDL, and is also implemented as an interactive web page.
Bandmerge takes in ASCII tables of positions and fluxes of detected astronomical sources in 2-7 different wavebands, and write out a single table of the merged data. The tool was designed to work with source lists generated by the Spitzer Science Center's MOPEX software, although it can be "fooled" into running on other data as well.
bamr is an MPI implementation of a Bayesian analysis of neutron star mass and radius data that determines the mass versus radius curve and the equation of state of dense matter. Written in C++, bamr provides some EOS models. This code requires O2scl (ascl:1408.019) be installed before compilation.
BAMBI (Blind Accelerated Multimodal Bayesian Inference) is a Bayesian inference engine that combines the benefits of SkyNet (ascl:1312.007) with MultiNest (ascl:1109.006). It operated by simultaneously performing Bayesian inference using MultiNest and learning the likelihood function using SkyNet. Once SkyNet has learnt the likelihood to sufficient accuracy, inference finishes almost instantaneously.
BAGEMASS calculates the posterior probability distribution for the mass and age of a star from its observed mean density and other observable quantities using a grid of stellar models that densely samples the relevant parameter space. It is written in Fortran and requires FITSIO (ascl:1010.001).
BACCHUS (Brussels Automatic Code for Characterizing High accUracy Spectra) derives stellar parameters (Teff, log g, metallicity, microturbulence velocity and rotational velocity), equivalent widths, and abundances. The code includes on the fly spectrum synthesis, local continuum normalization, estimation of local S/N, automatic line masking, four methods for abundance determinations, and a flagging system aiding line selection. BACCHUS relies on the grid of MARCS model atmospheres, Masseron's model atmosphere thermodynamic structure interpolator, and the radiative transfer code Turbospectrum (ascl:1205.004).
aXe is a spectroscopic data extraction software package that was designed to handle large format spectroscopic slitless images such as those from the Wide Field Camera 3 (WFC3) and the Advanced Camera for Surveys (ACS) on HST. aXe is a PyRAF/IRAF package that consists of several tasks and is distributed as part of the Space Telescope Data Analysis System (STSDAS). The various aXe tasks perform specific parts of the extraction and calibration process and are successively used to produce extracted spectra.
AUTOSTRUCTURE calculates atomic and ionic energy levels, radiative rates, autoionization rates, photoionization cross sections, plane-wave Born and distorted-wave excitation cross sections in LS- and intermediate-coupling using non- or (kappa-averaged) relativistic wavefunctions. These can then be further processed to form Auger yields, fluorescence yields, partial and total dielectronic and radiative recombination cross sections and rate coefficients, photoabsorption cross sections, and monochromatic opacities, among other properties.
AUTOSPEC provides fast, automated extraction of high quality 1D spectra from astronomical datacubes with minimal user effort. AutoSpec takes an integral field unit (IFU) datacube and a simple parameter file in order to extract a 1D spectra for each object in a supplied catalogue. A custom designed cross-correlation algorithm improves signal to noise as well as isolates sources from neighboring contaminants.
Automark models photon counts collected form observation of variable-intensity astronomical sources. It aims to mark the abrupt changes in the corresponding wavelength distribution of the emission automatically. In the underlying methodology, change points are embedded into a marked Poisson process, where photon wavelengths are regarded as marks and both the Poisson intensity parameter and the distribution of the marks are allowed to change.
AutoBayes automatically generates customized algorithms from compact, declarative specifications in the data analysis domain, taking a statistical model as input and creating documented and optimized C/C++ code. The synthesis process uses Bayesian networks to enable problem decompositions and guide the algorithm derivation. Program schemas encapsulate advanced algorithms and data structures, and a symbolic-algebraic system finds closed-form solutions for problems and emerging subproblems. AutoBayes has been used to analyze planetary nebulae images taken by the Hubble Space Telescope, and can be applied to other scientific data analysis tasks.
Autoastrom performs automated astrometric corrections on an astronomical image by automatically detecting objects in the frame, retrieving a reference catalogue, cross correlating the catalog with CCDPACK (ascl:1403.021) or MATCH, and using the ASTROM (ascl:1406.008) application to calculate a correction. It is distributed as part of the Starlink software collection (ascl:1110.012).
Auto-multithresh implements an automated masking algorithm for clean. It operates on the residual image within the minor cycle of clean to identify and mask regions of significant emission. It then cascades these significant regions down to lower signal to noise. It includes features to pad the mask to avoid sharp edges and to remove small regions that are unlikely to be significant emission. The algorithm described by this code was incorporated into the tclean task within CASA as auto-multithresh.
ATV displays and analyses astronomical images using the IDL image-processing language. It allows interactive control of the image scaling, color table, color stretch, and zoom, with support for world coordinate systems. It also does point-and-click aperture photometry, simple spectral extractions, and can produce publication-quality postscript output images.
The ATOOLS package of applications provides an interface to the AST library (ascl:1404.016), allowing quick experiments to be performed from the shell. It manipulates descriptions of coordinate frames and mappings in the form of AST objects and performs other functions, with each application within the package corresponding closely to one of the functions in the AST library.
Atmospheric Athena simulates hydrodynamic escape from close-in giant planets in 3D. It uses the Athena hydrodynamics code (ascl:1010.014) with a new ionizing radiative transfer implementation to self-consistently model photoionization driven winds from the planet. The code is fully compatible with static mesh refinement and MPI parallelization and can handle arbitrary planet potentials and stellar initial conditions.
ATLAS9 computes model atmospheres using a fixed set of pretabulated opacities, allowing one to work on huge numbers of stars and interpolate in large grids of models to determine parameters quickly. The code works with two different sets of opacity distribution functions (ODFs), one with “big” wavelength intervals covering the whole spectrum and the other with 1221 “little” wavelength intervals covering the whole spectrum. The ODFs use a 12-step representation; the radiation field is computed starting with the highest step and working down. If a lower step does not matter because the line opacity is small relative to the continuum at all depths, all the lower steps are lumped together and not computed to save time.
For a massless test particle and given a planetary system, atlas3bgeneral calculates all three body resonances in a given range of semimajor axes with all the planets taken by pairs. Planets are assumed in fixed circular and coplanar orbits and the test particle with arbitrary orbit. A sample input data file to calculate the three-body resonances is available for use with the Fortran77 source code.
For a massless test particle and given a planetary system, Atlas2bgeneral calculates all resonances in a given range of semimajor axes with all the planets taken one by one. Planets are assumed in fixed circular and coplanar orbits and the test particle with arbitrary orbit. A sample input data file to calculate the two-body resonances is available for use with the Fortran77 source code.
ATLAS12 is an opacity sampling model atmosphere program to allow computation of models with individual abundances using line data. ATLAS12 is able to compute the same models as ATLAS9 which uses pretabulated opacities, plus models with arbitrary abundances. ATLAS12 sampled fluxes are quite accurate for predicting the total flux except in the intermediate or narrow bandpass intervals because the sample size is too small.
ATLAS performs the tracking, projecting, power-spectrum-making, and ring-fitting needed to turn a set of Dopplergram images into a set of frequency shift measurements. This code is essentially a combination of three codes, FRACK (FORTRAN Tracking), PSPEC (Power SPECtrum), and MRF (Multi-Ridge Fitting), included in the ATLAS package. ATLAS reads in a list of longitude/latitude coordinates corresponding to the desired tile centers and a set of full-disk Dopplergram images and outputs frequency shift measurements from each wave mode of each tile. The code relies on both distributed-memory (MPI) and shared-memory (OpenMP) parallelism to scale up to around 1000 processes. Due to the immense volume of data produced by the tracking and projecting steps, the intermediate data products (tiles, power spectra) are never written out.
atlant is a public numerical code for fast calculations of cosmological recombination of primordial hydrogen-helium plasma is presented. This code is based on the three-level approximation (TLA) model of recombination and allows us to take into account some "fine'' physical effects of cosmological recombination simultaneously with using fudge factors.
ATHOS provides on-the-fly stellar parameter determination of FGK stars based on flux ratios from optical spectra. Once configured properly, it will measure flux ratios in the input spectra and deduce the stellar parameters effective temperature, iron abundance (a.k.a [Fe/H]), and surface gravity by employing pre-defined analytical relations. ATHOS can be configured to run in parallel in an arbitrary number of threads, thus enabling the fast and efficient analysis of huge datasets.
Written in FORTRAN, Athena3D, based on Athena (ascl:1010.014), is an implementation of a flux-conservative Godunov-type algorithm for compressible magnetohydrodynamics. Features of the Athena3D code include compressible hydrodynamics and ideal MHD in one, two or three spatial dimensions in Cartesian coordinates; adiabatic and isothermal equations of state; 1st, 2nd or 3rd order reconstruction using the characteristic variables; and numerical fluxes computed using the Roe scheme. In addition, it offers the ability to add source terms to the equations and is parallelized based on MPI.
athena is a 2d-tree code that estimates second-order correlation functions from input galaxy catalogues. These include shear-shear correlations (cosmic shear), position-shear (galaxy-galaxy lensing) and position-position (spatial angular correlation). Written in C, it includes a power-spectrum estimator implemented in Python; this script also calculates the aperture-mass dispersion. A test data set is available.
Athena is a grid-based code for astrophysical magnetohydrodynamics (MHD). It was developed primarily for studies of the interstellar medium, star formation, and accretion flows. The code has been designed to be easily extensible for use with static and adaptive mesh refinement. It combines higher-order Godunov methods with the constrained transport (CT) technique to enforce the divergence-free constraint on the magnetic field. Discretization is based on cell-centered volume-averages for mass, momentum, and energy, and face-centered area-averages for the magnetic field. Novel features of the algorithm include (1) a consistent framework for computing the time- and edge-averaged electric fields used by CT to evolve the magnetic field from the time- and area-averaged Godunov fluxes, (2) the extension to MHD of spatial reconstruction schemes that involve a dimensionally-split time advance, and (3) the extension to MHD of two different dimensionally-unsplit integration methods. Implementation of the algorithm in both C and Fortran95 is detailed, including strategies for parallelization using domain decomposition. Results from a test suite which includes problems in one-, two-, and three-dimensions for both hydrodynamics and MHD are given, not only to demonstrate the fidelity of the algorithms, but also to enable comparisons to other methods. The source code is freely available for download on the web.
ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.
AstroVis enables rapid visualization of large data files on platforms supporting the OpenGL rendering library. Radio astronomical observations are typically three dimensional and stored as data cubes. AstroVis implements a scalable approach to accessing these files using three components: a File Access Component (FAC) that reduces the impact of reading time, which speeds up access to the data; the Image Processing Component (IPC), which breaks up the data cube into smaller pieces that can be processed locally and gives a representation of the whole file; and Data Visualization, which implements an approach of Overview + Detail to reduces the dimensions of the data being worked with and the amount of memory required to store it. The result is a 3D display paired with a 2D detail display that contains a small subsection of the original file in full resolution without reducing the data in any way.
AstroTaverna is a plugin for Taverna Workbench that provides the means to build astronomy workflows using Virtual Observatory services discovery and efficient manipulation of VOTables (based on STIL tool set). It integrates SAMP-enabled software, allowing data exchange and communication among local VO tools, as well as the ability to execute Aladin scripts and macros.
AstroStat performs statistical analysis on data and is compatible with Virtual Observatory (VO) standards. It accepts data in a variety of formats and performs various statistical tests using a menu driven interface. Analyses, performed in R, include exploratory tests, visualizations, distribution fitting, correlation and causation, hypothesis testing, multivariate analysis and clustering. AstroStat is available in two versions with an identical interface and features: as a web service that can be run using any standard browser and as an offline application.
AstroSim is a Second Life based prototype application for synchronous collaborative visualization targeted at astronomers.
ASTRORAY employs a method of ray tracing and performs polarized radiative transfer of (cyclo-)synchrotron radiation. The radiative transfer is conducted in curved space-time near rotating black holes described by Kerr-Schild metric. Three-dimensional general relativistic magneto hydrodynamic (3D GRMHD) simulations, in particular performed with variations of the HARM code, serve as an input to ASTRORAY. The code has been applied to reproduce the sub-mm synchrotron bump in the spectrum of Sgr A*, and to test the detectability of quasi-periodic oscillations in its light curve. ASTRORAY can be readily applied to model radio/sub-mm polarized spectra of jets and cores of other low-luminosity active galactic nuclei. For example, ASTRORAY is uniquely suitable to self-consistently model Faraday rotation measure and circular polarization fraction in jets.
Astroquery allows users to access online astronomical data from a wide range of sources; it is an Astropy-affiliated package. Each web service has its own sub-package for interfacing with a particular data source.
Astropysics is a library containing a variety of utilities and algorithms for reducing, analyzing, and visualizing astronomical data. Best of all, it encourages the user to leverage the existing capabilities of Python to make this quick, easy, and as painless as cutting-edge science can even actually be. There do exist other Python packages with some of the capabilities of this project, but the goal of this project is to integrate all these tools together and make them interact in the most straightforward ways possible.
Astropy provides a common framework, core package of code, and affiliated packages for astronomy in Python. Development is actively ongoing, with major packages such as PyFITS, PyWCS, vo, and asciitable already merged in. Astropy is intended to contain much of the core functionality and some common tools needed for performing astronomy and astrophysics with Python.
AstroPoP reduces almost any CCD photometry and image polarimetry data. For photometry reduction, the code performs source finding, aperture and PSF photometry, astrometry calibration using different automated and non-automated methods and automated source identification and magnitude calibration based on online and local catalogs. For polarimetry, the code resolves linear and circular Stokes parameters produced by image beam splitter or polarizer polarimeters. In addition to the modular functions, ready-to-use pipelines based in configuration files and header keys are also provided with the code. AstroPOP was initially developed to reduce the IAGPOL polarimeter data installed at Observatório Pico dos Dias (Brazil).
Astropoltlib is a multi-language astronomical library of plots, a collection of templates useful for creating paper-quality figures. Most of the codes for producing the plots are written in IDL and/or Python; a very few are written in Mathematica. Any plot can be downloaded and customized to one's own needs.
astroplan is a flexible toolbox for observation planning and scheduling. It is powered by Astropy (ascl:1304.002); it works for Python beginners and new observers, and is powerful enough for observatories preparing nightly and long-term schedules as well. It calculates rise/set/meridian transit times, alt/az positions for targets at observatories anywhere on Earth, and offers built-in plotting convenience functions for standard observation planning plots (airmass, parallactic angle, sky maps). It can also determine the observability of sets of targets given an arbitrary set of constraints (i.e., altitude, airmass, moon separation/illumination, etc.).
Written in Python, AstroML is a library of statistical and machine learning routines for analyzing astronomical data in python, loaders for several open astronomical datasets, and a large suite of examples of analyzing and visualizing astronomical datasets. An optional companion library, astroML_addons, is available; it requires a C compiler and contains faster and more efficient implementations of certain algorithms in compiled code.
Astrometry.net is a reliable and robust system that takes as input an astronomical image and returns as output the pointing, scale, and orientation of that image (the astrometric calibration or World Coordinate System information). The system requires no first guess, and works with the information in the image pixels alone; that is, the problem is a generalization of the "lost in space" problem in which nothing—not even the image scale—is known. After robust source detection is performed in the input image, asterisms (sets of four or five stars) are geometrically hashed and compared to pre-indexed hashes to generate hypotheses about the astrometric calibration. A hypothesis is only accepted as true if it passes a Bayesian decision theory test against a null hypothesis. With indices built from the USNO-B catalog and designed for uniformity of coverage and redundancy, the success rate is >99.9% for contemporary near-ultraviolet and visual imaging survey data, with no false positives. The failure rate is consistent with the incompleteness of the USNO-B catalog; augmentation with indices built from the Two Micron All Sky Survey catalog brings the completeness to 100% with no false positives. We are using this system to generate consistent and standards-compliant meta-data for digital and digitized imaging from plate repositories, automated observatories, individual scientific investigators, and hobbyists.
Astrometrica is an interactive software tool for scientific grade astrometric data reduction of CCD images. The current version of the software is for the Windows 32bit operating system family. Astrometrica reads FITS (8, 16 and 32 bit integer files) and SBIG image files. The size of the images is limited only by available memory. It also offers automatic image calibration (Dark Frame and Flat Field correction), automatic reference star identification, automatic moving object detection and identification, and access to new-generation star catalogs (PPMXL, UCAC 3 and CMC-14), in addition to online help and other features. Astrometrica is shareware, available for use for a limited period of time (100 days) for free; special arrangements can be made for educational projects.
Over the past few years, the role of visualization for scientific purpose has grown up enormously. Astronomy makes an extended use of visualization techniques to analyze data, and scientific visualization has became a fundamental part of modern researches in Astronomy. With the evolution of high performance computers, numerical simulations have assumed a great role in the scientific investigation, allowing the user to run simulation with higher and higher resolution. Data produced in these simulations are often multi-dimensional arrays with several physical quantities. These data are very hard to manage and to analyze efficiently. Consequently the data analysis and visualization tools must follow the new requirements of the research. AstroMD is a tool for data analysis and visualization of astrophysical data and can manage different physical quantities and multi-dimensional data sets. The tool uses virtual reality techniques by which the user has the impression of travelling through a computer-based multi-dimensional model.
ASTROM performs "plate reductions" by taking user-provided star positions and the (x,y) coordinates of the corresponding star images and establishes the relationship between (x,y) and (ra,dec), thus enabling the coordinates of unknown stars to be determined. ASTROM is distributed with the Starlink software (ascl:1110.012) and uses SLALIB (ascl:1403.025).
AstroLines adjusts spectral line parameters (gf and damping constant) starting from an initial line list. Written in IDL and tailored to the APO Galactic Evolution Experiment (APOGEE), it runs a slightly modified version of MOOG (ascl:1202.009) to compare synthetic spectra with FTS spectra of the Sun and Arcturus.
AstroImageJ is generic ImageJ (ascl:1206.013) with customizations to the base code and a packaged set of astronomy specific plugins. It reads and writes FITS images with standard headers, displays astronomical coordinates for images with WCS, supports photometry for developing color-magnitude data, offers flat field, scaled dark, and non-linearity processing, and includes tools for precision photometry that can be used during real-time data acquisition.
The gyrokinetic simulation code AstroGK is developed to study fundamental aspects of kinetic plasmas and for applications mainly to astrophysical problems. AstroGK is an Eulerian slab code that solves the electromagnetic Gyrokinetic-Maxwell equations in five-dimensional phase space, and is derived from the existing gyrokinetics code GS2 by removing magnetic geometry effects. Algorithms used in the code are described. The code is benchmarked using linear and nonlinear problems. Serial and parallel performance scalings are also presented.
Astrodendro, written in Python, creates dendrograms for exploring and displaying hierarchical structures in observed or simulated astronomical data. It handles noisy data by allowing specification of the minimum height of a structure and the minimum number of pixels needed for an independent structure. Astrodendro allows interactive viewing of computed dendrograms and can also produce publication-quality plots with the non-interactive plotting interface.
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