Results 2001-2100 of 2617 (2565 ASCL, 52 submitted)
RICH (Racah Institute Computational Hydrodynamics) is a 2D hydrodynamic code based on Godunov's method. The code, largely based on AREPO (ascl:1909.010), acts on an unstructured moving mesh. It differs from AREPO in the interpolation and time advancement scheme as well as a novel parallelization scheme based on Voronoi tessellation. Though not universally true, in many cases a moving mesh gives better results than a static mesh: where matter moves one way and a sound wave is traveling in the other way (such that relative to the grid the wave is not moving), a static mesh gives better results than a moving mesh. RICH is designed in an object oriented, user friendly way that facilitates incorporation of new algorithms and physical processes.
RID (Relativistic Image Doubling in water Cherenkov detectors) uses Monte Carlo simulations to find the relative fraction of charged, relativistic particles entering a HAWC-like Water Cherenkov Detector that can cause a Relativistic Image Doubling (RID) effect visible to at least one of the internal detectors. The technique is available in C++ and Fortran; RID also includes python code for the horizontal incidence of the muon inside the tank.
RJObject provides a general approach to trans-dimensional Bayesian inference problems, using trans-dimensional MCMC embedded within a Nested Sampling algorithm. This allows exploration of the posterior distribution and calculattion of the marginal likelihood (summed over N) even if the problem contains a phase transition or other difficult features such as multimodality.
RLOS (Relativistic Line Of Sight) uses hydrocode output data, such as that from PLUTO (ascl:1010.045), to create synthetic images depicting what a model relativistic astrophysical jet looks like to a stationary observer. The approximate time-delayed imaging algorithm used is implemented within existing line-of-sight code. The software has the potential to study a variety of dynamical astrophysical phenomena in collaboration with other imaging and simulation tools.
RM-CLEAN reads in dirty Q and U cubes, generates rmtf based on the frequencies given in an ASCII file, and cleans the RM spectra following the algorithm given by Brentjens (2007). The output cubes contain the clean model components and the CLEANed RM spectra. The input cubes must be reordered with mode=312, and the output cubes will have the same ordering and thus must be reordered after being written to disk. RM-CLEAN runs as a MIRIAD (ascl:1106.007) task and a Python wrapper is included with the code.
RM-Tools analyzes radio polarization data, specifically the use of Faraday rotation measure synthesis and Stokes QU model fitting. It contains routines for both single-pixel 1D polarized spectra as well as 3D polarization cubes. RM-Tools is intended to serve as a toolkit for studies of polarized radio sources and measurements of their Faraday rotation. RM-Tools is the core package for the pipelines used for the POlarized Sky Survey of the Universe's Magnetism (POSSUM) and the polarization component of the Very Large Array Sky Survey (VLASS). The package is maintained by the Canadian Initiative for Radio Astronomy Data Analysis (CIRADA; cirada.org).
RMextract calculates Ionospheric Faraday Rotation for a given epoch, location and line of sight. This Python code extracts TEC, vTEC, Earthmagnetic field and Rotation Measures from GPS and WMM data for radio interferometry observations.
Rmfit uses a forward-folding technique to obtain the best-fit parameters for a chosen model given user-selected source and background time intervals from data files containing observed count rates and a corresponding detector response matrix. rmfit displays lightcurves and spectra using a graphical interface that enables user-defined integrated or time-resolved spectral fits and binning in either time or energy. Originally developed for the analysis of BATSE Gamma-Ray Burst (GRB) spectroscopy, rmfit is a tool for the spectroscopy of transient sources; it accommodates the Fermi GBM and LAT data and Swift BAT.
RMHB is a hierarchical Bayesian code for reverberation mapping (RM) that combines results of a sparsely sampled broad line region (BLR) light curve and a large sample of active galactic nuclei (AGN) to infer properties of the sample of the AGN. The key idea of RM is to measure the time lag τ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of τ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass MBH. A major difficulty with RM campaigns is the large amount of data needed to measure τ. RMHB allows a clear interpretation of a posterior distribution for hyperparameters describing the sample of AGN.
This program determines stellar population parameters (e.g. age, metallicity, IMF slope,...), using as input a pair of line-strength indices, through the interpolation in SSP model predictions. Both linear and bivariate fits are computed to perform the interpolation.
ROA (Running Optimal Average) describes time series data. This model uses a Gaussian window function that moves through the data giving stronger weights to points close to the center of the Gaussian. Therefore, the width of the window function, delta, controls the flexibility of the model, with a small delta providing a very flexible model. The function also calculates the effective number of parameters, as a very flexible model will correspond to large number of parameters while a rigid model (low delta) has a low effective number of parameters. Knowing the effective number of parameters can be used to optimize the window width, e.g., using the Bayesian information criterion (BIC). An error envelope, which expands appropriately where there are gaps in the data, is also calculated for the model.
ROBAST (ROOT-based simulator for ray tracing) is a non-sequential ray-tracing simulation library developed for wide use in optical simulations of gamma-ray and cosmic-ray telescopes. The library is written in C++ and fully utilizes the geometry library of the ROOT analysis framework, and can build the complex optics geometries typically used in cosmic ray experiments and ground-based gamma-ray telescopes.
Robbie automates cataloging sources, finding variables, and identifying transients in the image domain. It works in a batch processing paradigm with a modular design so components can be swapped out or upgraded to adapt to different input data while retaining a consistent and coherent methodological approach. Robbie is based on commonly used and open software, including AegeanTools (ascl:1212.009) and STILS/TOPCAT (ascl:1101.010).
ROBOSPECT, written in C, automatically measures and deblends line equivalent widths for absorption and emission spectra. ROBOSPECT should not be used for stars with spectra in which there is no discernible continuum over large wavelength regions, nor for the most carbon-enhanced stars for which spectral synthesis would be favored. Although ROBOSPECT was designed for metal-poor stars, it is capable of fitting absorption and emission features in a variety of astronomical sources.
The DR25 Kepler Robovetter is a robotic decision-making code that dispositions each Threshold Crossing Event (TCE) from the final processing (DR 25) of the Kepler data into Planet Candidates (PCs) and False Positives (FPs). The Robovetter provides four major flags to designate each FP TCE as Not Transit-Like (NTL), a Stellar Eclipse (SS), a Centroid Offset (CO), and/or an Ephemeris Match (EM). It produces a score ranging from 0.0 to 1.0 that indicates the Robovetter's disposition confidence, where 1.0 indicates strong confidence in PC, and 0.0 indicates strong confidence in FP. Finally, the Robovetter provides comments in a text string that indicate the specific tests each FP TCE fails and provides supplemental information on all TCEs as necessary.
Roche is a visualization and analysis tool for drawing the Roche-lobe geometry of evolving binaries. Roche can be used as a standalone program reading data from the command line or from a file generated by SeBa (ascl:1201.003). Eventually Roche will be able to read data from any other binary evolution program. Roche requires Starlab (ascl:1010.076) version 4.1.1 or later and the pgplot (ascl:1103.002) libraries. Roche creates a series of images, based on the SeBa output file SeBa.data, displaying the evolutionary state of a binary.
Rockstar (Robust Overdensity Calculation using K-Space Topologically Adaptive Refinement) identifies dark matter halos, substructure, and tidal features. The approach is based on adaptive hierarchical refinement of friends-of-friends groups in six phase-space dimensions and one time dimension, which allows for robust (grid-independent, shape-independent, and noise-resilient) tracking of substructure. Our method is massively parallel (up to 10^5 CPUs) and runs on the largest current simulations (>10^10 particles) with high efficiency (10 CPU hours and 60 gigabytes of memory required per billion particles analyzed). Rockstar offers significant improvement in substructure recovery as compared to several other halo finders.
RODRIGUES (RATT Online Deconvolved Radio Image Generation Using Esoteric Software) is a web-based radio telescope simulation and reduction tool. From a technical perspective it is a web based parameterized docker container scheduler with a result set viewer.
ROGER (Reconstructing Orbits of Galaxies in Extreme Regions) predicts the dynamical properties of galaxies using the projected phase-space information. Written in R, it offers a choice of machine learning methods to classify the dynamical properties of galaxies. An interface for online use of the software is available at https://mdelosrios.shinyapps.io/roger_shiny/.
ROHSA (Regularized Optimization for Hyper-Spectral Analysis) reveals the statistical properties of interstellar gas through atomic and molecular lines. It uses a Gaussian decomposition algorithm based on a multi-resolution process from coarse to fine grid to decompose any kind of hyper-spectral observations into a sum of coherent Gaussian. Optimization is performed on the whole data cube at once to obtain a solution with spatially smooth parameters.
RoLo (Roche Lobe) calculates the radius and potential of the Roche Lobe for any specified direction, and also gives some other commonly used quantities (such as the Lagrange points). The calculator is valid for any mass ratio q between 0.01 and 100. The coordinates are spherical-polar (R, theta, phi) centered on one star (M1), with the x-axis (theta=pi/2, phi=0) pointing towards the other star (M2). The mass ratio is defined as q=M2/M1. Distances are given in units of the binary separation, a. A circular orbit is assumed.
The RPFITS data file format records synthesis visibility data obtained from the Australia Telescope Compact Array (ATCA) at Narrabri, NSW. It is also used for single-dish spectral line data obtained from Parkes and Mopra, including Parkes multibeam data. RPFITS superficially resembles random group FITS, but differs in important respects, making it incompatible with standard FITS software such as FITSIO (ascl:1010.001) and FTOOLS (ascl:9912.002) and, in particular, it precludes the use of fv (ascl:1205.005). The RPFITS Fortran library contains routines for reading and writing RPFITS files. A header file, RPFITS.h, is provided to facilitate usage by C and C++ applications. Also included is rpfhdr, a utility for viewing RPFITS headers (it also works for standard FITS), and rpfex for extracting selected scans from an RPFITS file.
rPICARD (Radboud PIpeline for the Calibration of high Angular Resolution Data) reduces data from different VLBI arrays, including high-frequency and low-sensitivity arrays, and supports continuum, polarization, and phase-referencing observations. Built on the CASA (ascl:1107.013) framework, it uses CASA for CLEAN imaging and self-calibration, and can be run non-interactively after only a few non-default input parameters are set. rPICARD delivers high-quality calibrated data and large bandwidth data can be processed within reasonable computing times.
RPPPS (Re-analysing Pipeline for Parkes Pulsar Survey) uses Linux shell scripts, C language, and python code and two parallel strategies to reorganize the PRESTO (ascl:1107.017) pulsar search pipeline to run multiple processes in parallel, thus accelerating the search for pulsars. Though originally designed for reprocessing PMPS data, the code has also been successfully used with FAST (Five-hundred-meter Aperture Spherical radio Telescope) drift scan data. The pipeline is only CPU-based and can be easily and quickly deployed in computing nodes for testing purposes or data processes.
RRATtrap is a single-pulse sifting algorithm to identify Rotating Radio Transients (RRATs) and transients using output from the PRESTO (ascl:1107.017) routine single_pulse_search.py. It can be integrated into pulsar survey data analysis pipelines and, in addition to finding RRATs, it can also identify Fast Radio Bursts.
rsigma calculates the resonant disturbing function, R(sigma), for a massless particle in an arbitrary orbit perturbed by a planet in circular orbit. This function defines the strength of the resonance (its semi-amplitude) and the location of the stable equilibrium points (the minima). It depends on the variable sigma called critical angle and on the particle's orbital elements a, e, i and the argument of the perihelion. R(sigma) is numerically calculated and the code is valid for arbitrary eccentricities and inclinations, including retrograde orbits.
The parallel one-dimensional moving-mesh hydrodynamics code RT1D reproduces the multidimensional dynamics from Rayleigh-Taylor instability in supernova remnants.
rtpipe (real-time pipeline) analyzes radio interferometric data with an emphasis on searching for transient or variable astrophysical sources. The package combines single-dish concepts such as dedispersion and filters with interferometric concepts, including images and the uv-plane. In contrast to time-domain data recorded with large single-dish telescopes, visibilities from interferometers can precisely localize sources anywhere in the entire field of view. rtpipe opens interferometers to the study of fast transient sky, including sources like pulsars, stellar flares, rotating radio transients, and fast radio bursts. Key portions of the search pipeline, such as image generation and dedispersion, have been accelerated. That, in combination with its multi-threaded, multi-node design, makes rtpipe capable of searching millisecond timescale data in real time on small compute clusters.
runDM calculates the running of the couplings of Dark Matter (DM) to the Standard Model (SM) in simplified models with vector mediators. By specifying the mass of the mediator and the couplings of the mediator to SM fields at high energy, the code can calculate the couplings at low energy, taking into account the mixing of all dimension-6 operators. runDM can also extract the operator coefficients relevant for direct detection, namely low energy couplings to up, down and strange quarks and to protons and neutrons.
The RV program produces a report listing the components, in a given direction, of the observer's velocity on a given date. This allows an observed radial velocity to be referred to an appropriate standard of rest -- typically either the Sun or an LSR.
As a secondary function, RV computes light time components to the Sun, thus allowing the times of phenomena observed from a terrestrial observatory to be referred to a heliocentric frame of reference. n.b. It will of course, in addition, be necessary to express the observations in the appropriate timescale as well as applying light time corrections. In particular, it is likely that an observed UTC will need to be converted to TDB as well as being corrected to the Sun.)
rvfit, developed in IDL 7.0, fits non-precessing keplerian radial velocity (RV) curves for double-line and single-line binary stars or exoplanets. It fits a simple keplerian model to the observed RV and computes the seven parameters (six for a single-line system) from the model. Some parameters can be fixed beforehand if they are known, for instance, if photometric observations are available. The fit is done using an Adaptive Simulated Annealing algorithm optimized for this specific task. Simulated Annealing methods are powerful heuristic algorithms to minimize functions in multiparametric spaces.
The RVLIN package for IDL is a set of routines that quickly fits an arbitrary number of Keplerian curves to radial velocity data. It can handle data from multiple telescopes (i.e. it solves for the offset), constraints on P, e, and time of peri passage, and can incorporate transit timing data. The code handles fixed periods and circular orbits in combination and transit time constraints, including for multiple transiting planets.
RVSAO is a set of programs to obtain redshifts and radial velocities from digital spectra. RVSAO operates in the IRAF (Tody 1986, 1993) environment. The heart of the system is xcsao, which implements the cross-correlation method, and is a direct descendant of the system built by Tonry and Davis (1979). emsao uses intelligent heuristics to search for emission lines in spectra, then fits them to obtain a redshift. sumspec shifts and sums spectra to build templates for cross-correlation. linespec builds synthetic spectra given a list of spectral lines. bcvcorr corrects velocities for the motion of the earth. We discuss in detail the parameters necessary to run xcsao and emsao properly. We discuss the reliability and error associated with xcsao derived redshifts. We develop an internal error estimator, and we show how large, stable surveys can be used to develop more accurate error estimators. We develop a new methodology for building spectral templates for galaxy redshifts. We show how to obtain correlation velocities using emission line templates. Emission line correlations are substantially more efficient than the previous standard technique, automated emission line fitting. We compare the use of RVSAO with new methods, which use Singular Value Decomposition and $chi^2$ fitting techniques.
RVSpecFit determines radial velocities and stellar atmospheric parameters from spectra by direct pixel fitting by interpolated stellar templates. The code doesn't require spectrum normalization and can deal with non-flux calibrated spectra. RVSpecFit is able to fit multiple spectra simultaneously.
The s2 package can represent any arbitrary function defined on the sphere. Both real space map and harmonic space spherical harmonic representations are supported. Basic sky representations have been extended to simulate full sky noise distributions and Gaussian cosmic microwave background realisations. Support for the representation and convolution of beams is also provided. The code requires HEALPix (ascl:1107.018) and CFITSIO (ascl:1010.001).
Many problems in astronomy and astrophysics require a computation of the spherical harmonic transforms. This is in particular the case whenever data to be analyzed are distributed over the sphere or a set of corresponding mock data sets has to be generated. In many of those contexts, rapidly improving resolutions of both the data and simulations puts increasingly bigger emphasis on our ability to calculate the transforms quickly and reliably.
The scalable spherical harmonic transform library S2HAT consists of a set of flexible, massively parallel, and scalable routines for calculating diverse (scalar, spin-weighted, etc) spherical harmonic transforms for a class of isolatitude sky grids or pixelizations. The library routines implement the standard algorithm with the complexity of O(n^3/2), where n is a number of pixels/grid points on the sphere, however, owing to their efficient parallelization and advanced numerical implementation, they achieve very competitive performance and near perfect scalability. S2HAT is written in Fortran 90 with a C interface. This software is a derivative of the spherical harmonic transforms included in the HEALPix package and is based on both serial and MPI routines of its version 2.01, however, since version 2.5 this software is fully autonomous of HEALPix and can be compiled and run without the HEALPix library.
S2LET provides high performance routines for fast wavelet analysis of signals on the sphere. It uses the SSHT code built on the MW sampling theorem to perform exact spherical harmonic transforms on the sphere. The resulting wavelet transform implemented in S2LET is theoretically exact, i.e. a band-limited signal can be recovered from its wavelet coefficients exactly and the wavelet coefficients capture all the information. S2LET also supports the HEALPix sampling scheme, in which case the transforms are not theoretically exact but achieve good numerical accuracy. The core routines of S2LET are written in C and have interfaces in Matlab, IDL and Java. Real signals can be written to and read from FITS files and plotted as Mollweide projections.
We present a new, three-dimensional (3D) plotting library with advanced features, and support for standard and enhanced display devices. The library - S2PLOT - is written in C and can be used by C, C++ and FORTRAN programs on GNU/Linux and Apple/OSX systems. S2PLOT draws objects in a 3D (x,y,z) Cartesian space and the user interactively controls how this space is rendered at run time. With a PGPLOT inspired interface, S2PLOT provides astronomers with elegant techniques for displaying and exploring 3D data sets directly from their program code, and the potential to use stereoscopic and dome display devices. The S2PLOT architecture supports dynamic geometry and can be used to plot time-evolving data sets, such as might be produced by simulation codes. In this paper, we introduce S2PLOT to the astronomical community, describe its potential applications, and present some example uses of the library.
s3PCF computes the 3-point correlation function (3PCF) in the squeezed limit given galaxy positions and pair positions. The code is currently written specifically for the Abacus simulations, but the main functionalities can be also easily adapted for other galaxy catalogs with the appropriate properties.
Saada transforms a set of heterogeneous FITS files or VOtables of various categories (images, tables, spectra, etc.) in a powerful database deployed on the Web. Databases are located on your host and stay independent of any external server. This job doesn’t require writing code. Saada can mix data of various categories in multiple collections. Data collections can be linked each to others making relevant browsing paths and allowing data-mining oriented queries. Saada supports 4 VO services (Spectra, images, sources and TAP) . Data collections can be published immediately after the deployment of the Web interface.
The Sheffield Advanced Code (SAC) is a fully non-linear MHD code designed for simulations of linear and non-linear wave propagation in gravitationally strongly stratified magnetized plasma. It was developed primarily for the forward modelling of helioseismological processes and for the coupling processes in the solar interior, photosphere, and corona; it is built on the well-known VAC platform that allows robust simulation of the macroscopic processes in gravitationally stratified (non-)magnetized plasmas. The code has no limitations of simulation length in time imposed by complications originating from the upper boundary, nor does it require implementation of special procedures to treat the upper boundaries. SAC inherited its modular structure from VAC, thereby allowing modification to easily add new physics.
SACC (Save All Correlations and Covariances) is a format and reference library for general storage
of summary statistic measurements for the Dark Energy Science Collaboration (DESC) within and from the Large Synoptic Survey Telescope (LSST) project's Dark Energy Science Collaboration.
SAGE (Semi-Analytic Galaxy Evolution) models galaxy formation in a cosmological context. SAGE has been rebuilt to be modular and customizable. The model runs on any dark matter cosmological N-body simulation whose trees are organized in a supported format and contain a minimum set of basic halo properties.
SALT (Spectral Adaptive Lightcurve Template) is a package for Type Ia Supernovae light curve fitting. Its main purpose is to provide a distance estimator but it can also be used for photometric redshifts, and spectroscopic + photometric identification. This code is also known by the name snfit.
The SAMI (Sydney-AAO Multi-object Integral field spectrograph) pipeline reduces data from the Sydney-AAO Multi-object Integral field spectrograph (SAMI) for the SAMI Galaxy Survey. The python code organizes SAMI data and, along with the AAO 2dfdr package, carries out all steps in the data reduction, from raw data to fully calibrated datacubes. The principal steps are: data management, use of 2dfdr to produce row-stacked spectra, flux calibration, correction for telluric absorption, removal of atmospheric dispersion, alignment of dithered exposures, and drizzling onto a regular output grid. Variance and covariance information is tracked throughout the pipeline. Some quality control routines are also included.
samiDB is an archive, database, and query engine to serve the spectra, spectral hypercubes, and high-level science products that make up the SAMI Galaxy Survey. Based on the versatile Hierarchical Data Format (HDF5), samiDB does not depend on relational database structures and hence lightens the setup and maintenance load imposed on science teams by metadata tables. The code, written in Python, covers the ingestion, querying, and exporting of data as well as the automatic setup of an HTML schema browser. samiDB serves as a maintenance-light data archive for Big Science and can be adopted and adapted by science teams that lack the means to hire professional archivists to set up the data back end for their projects.
The Search And Non-Destroy (SAND) is a VLBI data reduction pipeline composed of a set of Python programs based on the AIPS interface provided by ObitTalk. It is designed for the massive data reduction of multi-epoch VLBI monitoring research. It can automatically investigate calibrated visibility data, search all the radio emissions above a given noise floor and do the model fitting either on the CLEANed image or directly on the uv data. It then digests the model-fitting results, intelligently identifies the multi-epoch jet component correspondence, and recognizes the linear or non-linear proper motion patterns. The outputs including CLEANed image catalogue with polarization maps, animation cube, proper motion fitting and core light curves. For uncalibrated data, a user can easily add inline modules to do the calibration and self-calibration in a batch for a specific array.
SAOImage DS9 is an astronomical imaging and data visualization application. DS9 supports FITS images and binary tables, multiple frame buffers, region manipulation, and many scale algorithms and colormaps. It provides for easy communication with external analysis tasks and is highly configurable and extensible via XPA and SAMP. DS9 is a stand-alone application. It requires no installation or support files. Versions of DS9 currently exist for Solaris, Linux, MacOSX, and Windows. All versions and platforms support a consistent set of GUI and functional capabilities. DS9 supports advanced features such as multiple frame buffers, mosaic images, tiling, blinking, geometric markers, colormap manipulation, scaling, arbitrary zoom, rotation, pan, and a variety of coordinate systems. DS9 also supports FTP and HTTP access. The GUI for DS9 is user configurable. GUI elements such as the coordinate display, panner, magnifier, horizontal and vertical graphs, button bar, and colorbar can be configured via menus or the command line. DS9 is a Tk/Tcl application which utilizes the SAOTk widget set. It also incorporates the X Public Access (XPA) mechanism to allow external processes to access and control its data, GUI functions, and algorithms.
Sapporo mimics the behavior of GRAPE hardware and uses the GPU to perform high-precision gravitational N-body simulations. It makes use of CUDA and therefore only works on NVIDIA GPUs. N-body codes currently running on GRAPE-6 can switch to Sapporo by a simple relinking of the library. Sapporo's precision is comparable to that of GRAPE-6, even though internally the GPU hardware is limited to single precision arithmetics. This limitation is effectively overcome by emulating double precision for calculating the distance between particles.
SARA-PPD is a proof of concept MATLAB implementation of an acceleration strategy for a recently proposed primal-dual distributed algorithm. The algorithm optimizes resolution by accounting for the correct noise statistics, leverages natural weighting in the definition of the minimization problem for image reconstruction, and optimizes sensitivity by enabling accelerated convergence through a preconditioning strategy incorporating sampling density information. This algorithm offers efficient processing of large-scale data sets that will be acquired by next generation radio-interferometers such as the Square Kilometer Array.
SARAH builds and analyzes SUSY and non-SUSY models. It calculates all vertices, mass matrices, tadpoles equations, one-loop corrections for tadpoles and self-energies, and two-loop RGEs for a given model. SARAH writes model files for a variety of other software packages for dark matter studies, includes many SUSY and non-SUSY models, and makes implementing new models efficient and straightforward. Written in Mathematica, SARAH can also use output from Vevacious (ascl:1904.019) to check for the global minimum for a given model and parameter point.
The Science Analysis System (SAS) is an extensive suite of software tasks developed to process the data collected by the XMM-Newton Observatory. The SAS extracts standard (spectra, light curves) and/or customized science products, and allows reproductions of the reduction pipelines run to get the PPS products from the ODFs files. SAS includes a powerful and extensive suite of FITS file manipulation packages based on the Data Access Layer library.
SASRST, a small collection of Python scripts, attempts to reproduce the semi-analytical one-dimensional equilibrium and non-equilibrium radiative shock tube solutions of Lowrie & Rauenzahn (2007) and Lowrie & Edwards (2008), respectively. The included code calculates the solution for a given set of input parameters and also plots the results using Matplotlib. This software was written to provide validation for numerical radiative shock tube solutions produced by a radiation hydrodynamics code.
satcand applies theoretical constraints of orbital stability and tidal migration to KOI exomoon candidates. The package can evaluate the tidal migration within a Sun-Earth-Moon system, plot angular velocity over time, and calculate the migration time scale (T1) and the total migration time scale, among other things. In addition to the theoretical constraints, observational constraints can be applied.
SATMC is a general purpose, MCMC-based SED fitting code written for IDL and Python. Following Bayesian statistics and Monte Carlo Markov Chain algorithms, SATMC derives the best fit parameter values and returns the sampling of parameter space used to construct confidence intervals and parameter-parameter confidence contours. The fitting may cover any range of wavelengths. The code is designed to incorporate any models (and potential priors) of the user's choice. The user guide lists all the relevant details for including observations, models and usage under both IDL and Python.
A Savitzky–Golay filter is often applied to data to smooth the data without greatly distorting the signal; however, almost all data inherently comes with noise, and the noise properties can differ from point to point. This python script improves upon the traditional Savitzky-Golay filter by accounting for error covariance in the data. The inputs and arguments are modeled after scipy.signal.savgol_filter.
SBGAT (Small Body Geophysical Analysis Tool) generates simulated data originating from small bodies shape models, combined with advanced shape-modification properties. It uses polyhedral shape models from which can be computed mass properties such as volume, center of mass, and inertia, synthetic observations such as lightcurves and radar, and which can be used within dynamical models, such as spherical harmonics and polyhedron gravity modeling. SBGAT can generate spherical harmonics expansions from constant-density polyhedra (and export them to JSON) and evaluate the spherical harmonics expansions. It can also generate YORP coefficients, multi-threaded Polyhedron Gravity Model gravity and potential evaluations, and synthetic light-curve and radar observations for single/primary asteroids.
SBGAT has two distinct packages: a dynamic library SBGAT Core that contains the data structure and algorithm backbone of SBGAT, and SBGAT Gui, which wraps the former inside a VTK, Qt user interface to facilitate user/data interaction. SBGAT Core can be used without the SBGAT Gui wrapper.
sbpy, an Astropy affiliated package, supplements functionality provided by Astropy (ascl:1304.002) with functions and methods that are frequently used for planetary astronomy with a clear focus on asteroids and comets. It offers access tools for various databases for orbital and physical data, spectroscopy analysis tools and models, photometry models for resolved and unresolved observations, ephemerides services, and other tools useful for small-body planetary astronomy.
Astrometric and photometric calibrations have remained the most tiresome step in the reduction of large imaging surveys. SCAMP has been written to address this problem. The program efficiently computes accurate astrometric and photometric solutions for any arbitrary sequence of FITS images in a completely automatic way. SCAMP is released under the GNU General Public License.
ScamPy "paints" an observed population of cosmological objects on top of the DM-halo/subhalo hierarchy obtained from DM-only simulations. The method combines the Halo Occupation Distribution (HOD) method with sub-halo abundance matching (SHAM); the two processes together are dubbed Sub-halo clustering and abundance matching (SCAM). The procedure requires applying the two methods in sequence; by applying the HOD scheme, the host sub-haloes are selected, and the SHAM algorithm associates an observable property of choice to each sub-halo. The provided python interface allows users to load and populate DM halos and sub-halos obtained by FoF and SUBFIND algorithms applied to DM snapshots at any redshift. The software is highly-optimized and flexible.
Scanamorphos is an IDL program to build maps from scan observations made with bolometer arrays. Scanamorphos can post-process scan observations performed with the Herschel photometer arrays. This post-processing mainly consists in subtracting the total low-frequency noise (both its thermal and non-thermal components), masking cosmic ray hit residuals, and projecting the data onto a map. Although it was developed for Herschel, it is also applicable with minimal adjustment to scan observations made with other bolometer arrays provided they entail sufficient redundancy; it was successfully applied to P-Artemis, an instrument operating on the APEX telescope. Scanamorphos does not assume any particular noise model and does not apply any Fourier-space filtering to the data. It is an empirical tool using only the redundancy built in the observations, taking advantage of the fact that each portion of the sky is sampled at multiple times by multiple bolometers. The user is allowed to optionally visualize and control results at each intermediate step, but the processing is fully automated.
SCARLET performs source separation (aka "deblending") on multi-band images. It is geared towards optical astronomy, where scenes are composed of stars and galaxies, but it is straightforward to apply it to other imaging data. Separation is achieved through a constrained matrix factorization, which models each source with a Spectral Energy Distribution (SED) and a non-parametric morphology, or multiple such components per source. The code performs forced photometry (with PSF matching if needed) using an optimal weight function given by the signal-to-noise weighted morphology across bands. The approach works well if the sources in the scene have different colors and can be further strengthened by imposing various additional constraints/priors on each source. Because of its generic utility, this package provides a stand-alone implementation that contains the core components of the source separation algorithm. However, the development of this package is part of the LSST Science Pipeline; the meas_deblender package contains a wrapper to implement the algorithms here for the LSST stack.
SCEPtER (Stellar CharactEristics Pisa Estimation gRid) estimates the stellar mass and radius given a set of observable quantities; the results are obtained by adopting a maximum likelihood technique over a grid of pre-computed stellar models. The code is quite flexible since different observables can be used, depending on their availability, as well as different grids of models.
schNell computes basic map-level noise properties for generic networks of gravitational wave interferometers, primarily the noise power spectrum "N_ell", but this lightweight python module that can also be used for, for example, antenna patterns, overlap functions, and inverse variance maps, among other tasks. The code has three main classes; detectors contain information about each individual detector of the network, such as their positions, noise properties, and orientation. NoiseCorrelations describes the noise-level correlation between pairs of detectors, and the MapCalculators class combines a list of Detectors into a network (potentially together with a NoiseCorrelation object) and computes the corresponding map-level noise properties arising from their correlations.
schwimmbad provides a uniform interface to parallel processing pools and enables switching easily between local development (e.g., serial processing or with multiprocessing) and deployment on a cluster or supercomputer (via, e.g., MPI or JobLib). The utilities provided by schwimmbad require that tasks or data be “chunked” and that code can be “mapped” onto the chunked tasks.
SciDB is a DMAS (Data Management and Analytics Software System) optimized for data management of big data and for big analytics. SciDB is organized around multidimensional array storage, a generalization of relational tables, and is designed to be scalable up to petabytes and beyond. Complex analytics are simplified with SciDB because arrays and vectors are first-class objects with built-in optimized operations. Spatial operators and time-series analysis are easy to express. Interfaces to common scientific tools like R as well as programming languages like C++ and Python are provided.
SCIMES identifies relevant molecular gas structures within dendrograms of emission using the spectral clustering paradigm. It is useful for decomposing objects in complex environments imaged at high resolution.
SCINTOOLS (SCINtillation TOOLS) simulates and analyzes pulsar scintillation data. The code can be used for processing observed dynamic spectra, computing secondary spectra and ACFs, measuring scintillation arcs, simulating dynamic spectra, and modeling pulsar transverse velocities through scintillation arcs or diffractive timescales.
The Semi-automated multi-COmponent Universal Spectral-line fitting Engine (SCOUSE) is a spectral line fitting algorithm that fits Gaussian files to spectral line emission. It identifies the spatial area over which to fit the data and generates a grid of spectral averaging areas (SAAs). The spatially averaged spectra are fitted according to user-provided tolerance levels, and the best fit is selected using the Akaike Information Criterion, which weights the chisq of a best-fitting solution according to the number of free-parameters. A more detailed inspection of the spectra can be performed to improve the fit through an iterative process, after which SCOUSE integrates the new solutions into the solution file.
scousepy is a Python implementation of spectral line-fitting IDL code SCOUSE (ascl:1601.003). It fits a large amount of complex astronomical spectral line data in a systematic way.
SDAR (Slow-Down Algorithmic Regularization) simulates the long-term evolution of few-body systems such as binaries and triples. The algorithm used provides a few orders of magnitude faster performance than the classical N-body method. The secular evolution of hierarchical systems, e.g. Kozai-Lidov oscillation, can be well reproduced. The code is written in the C++ language and can be used either as a stand-alone tool or a library to be plugged in other N-body codes. The high precision of the floating point to 62 digits is also supported.
Dual Active Nuclei Galaxies (DAGNs) are rare occurrences in the sky. Until now, most AGNs have been described to be found serendipitously, or by manual observation. In recent years, there has been an increasing interest in such dual AGNs and their astrophysical properties. Their study is important to the understanding of galaxy formation, star formation and these objects are the precursors to Gravitational Wave Sources.
Hence, we have devised a pipeline, that along with systematic data collection, can detect such dual AGN candidates. A novel algorithm 'Graph-Boosted Gradient Ascent' has been devised to detect whether an R-band image of a galaxy is a potential candidate for a DAGN or not. The pipeline can be cloned to a user's machine, and by joining the AstrIRG_DAGN group on SciServer, astronomers can collectively contribute to the mining of DAGNs.
Seaborn provides a high-level interface for drawing attractive statistical graphics. Written in Python, it builds on matplotlib and integrates closely with pandas data structures. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API allows the user to focus on what the different elements of the plots mean, rather than on the details of how to draw them.
SearchCal builds an evolutive catalog of stars suitable as calibrators within any given user-defined angular distance and magnitude around a scientific target. SearchCal can select suitable bright calibration stars (V ≤ 10; K ≤ 5.0) for obtaining the ultimate precision of current interferometric instruments like the VLTI and faint calibration stars up to K ~ 15 around the scientific target. Star catalogs available at the CDS are searched via web requests and provide the useful astrometric and photometric informations for selecting calibrators. The missing photometries are computed with an accuracy of about 0.1 mag. The stellar angular diameter is estimated with a precision of about 10% through newly determined surface-brightness versus color-index relations based on the I, J, H and K magnitudes. For each star the squared visibility is computed taking into account the central wavelength and the maximum baseline of the predicted observations.
The stellar and binary evolution package SeBa is fully integrated into the kira integrator, although it can also be used as a stand-alone module for non-dynamical applications. Due to the interaction between stellar evolution and stellar dynamics, it is difficult to solve for the evolution of both systems in a completely self-consistent way. The trajectories of stars are computed using a block timestep scheme, as described earlier. Stellar and binary evolution is updated at fixed intervals (every 1/64 of a crossing time, typically a few thousand years). Any feedback between the two systems may thus experience a delay of at most one timestep. Internal evolution time steps may differ for each star and binary, and depend on binary period, perturbations due to neighbors, and the evolutionary state of the star. Time steps in this treatment vary from several milliseconds up to (at most) a million years.
Prior to recombination photons, electrons, and atomic nuclei rapidly scattered and behaved, almost, like a single tightly-coupled photon-baryon plasma. In order to solve the cosmological perturbation equations during that time, Cosmic Microwave Background (CMB) codes use the so-called tight-coupling approximation in which the problematic terms (i.e. the source of the stiffness) are expanded in inverse powers of the Thomson Opacity. Most codes only keep the terms linear in the inverse Thomson Opacity. We have developed a second-order tight-coupling code to test the validity of the usual first-order tight-coupling code. It is based on the publicly available code CAMB.
SecularMultiple computes the secular (orbit-averaged) gravitational dynamics of hierarchical multiple systems composed of nested binary orbits (simplex-type systems) with any configuration and any number of bodies. A particle can represent a binary or a body. The structure of the system is determined by linking to other particles with the attributes child1 and child2, and tidal interactions and relativistic corrections are included in an ad hoc fashion. SecularMultiple also includes routines for external perturbations such as flybys and supernovae.
SEDBYS (Spectral Energy Distribution Builder for Young Stars) provides command-line tools and uses existing functions from standard packages such as Astropy (ascl:1304.002) to collate archival photometric and spectroscopic data. It also builds and inspects SEDS, and automatically collates the necessary software references.
SEDkit constructs and analyzes simple spectral energy distributions (SED). This collection of pure Python modules creates individual SEDs or SED catalogs from spectra and/or photometry and calculates fundamental parameters (fbol, Mbol, Lbol, Teff, mass, log(g)).
SEDobs uses state-of-the-art theoretical galaxy SEDs (spectral energy distributions) to create simulated observations of distant galaxies. It used BC03 and M05 theoretical models and allows the user to configure the simulated observation that are needed. For a given simulated galaxy, the user is able to simulate multi-spectral and multi-photometric observations.
sedop is a Monte-Carlo minimization code designed to optimally construct spectral energy distributions (SEDs) for sources of ultraviolet and X-ray radiation employed in numerical simulations of reionization and radiative feedback.
SEDPY performs a variety of tasks for astronomical spectral energy distributions. It can generate synthetic photometry through any filter, provides detailed modeling of extinction curves, and offers basic aperture photometry algorithms. SEDPY can also store and interpolate model SEDs, convolve absolute or apparent fluxes, and calculate rest-frame magnitudes.
SEEK (Signal Extraction and Emission Kartographer) processes time-ordered-data from single dish radio telescopes or from the simulation pipline HIDE (ascl:1607.019), removes artifacts from Radio Frequency Interference (RFI), automatically applies flux calibration, and recovers the astronomical radio signal. With its companion code HIDE (ascl:1607.019), it provides end-to-end simulation and processing of radio survey data.
The Python package segueSelect automatically models the SDSS/SEGUE selection fraction -- the fraction of stars with good spectra -- as a continuous function of apparent magnitude for each plate. The selection function can be determined for any desired sample cuts in signal-to-noise ratio, u-g, r-i, and E(B-V). The package requires Pyfits (ascl:1207.009) and, for coordinate transformations, galpy (ascl:1411.008). It can calculate the KS probability that the spectropscopic sample was drawn from the underlying photometric sample with the model selection function, plot the cumulative distribution function in r-band apparent magnitude of the spectroscopic sample (red) and the photometric sample+selection-function-model for this plate, and, if galpy is installed, can transform velocities into the Galactic coordinate frame. The code can also determine the selection function for SEGUE K stars.
The self-lensing binary code with Markov chain code was used to analyze the self-lensing binary system KOI-3278. It includes the MCMC modeling and the key figures.
SENR (Simple, Efficient Numerical Relativity) provides the algorithmic framework that combines the C codes generated by NRPy+ (ascl:1807.025) into a functioning numerical relativity code. It is part of the numerical relativity code package SENR/NRPy+. The package extends previous implementations of the BSSN reference-metric formulation to a much broader class of curvilinear coordinate systems, making it suitable for modeling physical configurations with approximate or exact symmetries, such as modeling black hole dynamics.
SEP (Source Extraction and Photometry) makes the core algorithms of Source Extractor (ascl:1010.064) available as a library of standalone functions and classes. These operate directly on in-memory arrays (no FITS files or configuration files). The code is derived from the Source Extractor code base (written in C) and aims to produce results compatible with Source Extractor whenever possible. SEP consists of a C library with no dependencies outside the standard library and a Python module that wraps the C library in a Pythonic API. The Python wrapper operates on NumPy arrays with NumPy as its only dependency. It is generated using Cython.
From Source Extractor, SEP includes background estimation, image segmentation (including on-the-fly filtering and source deblending), aperture photometry in circular and elliptical apertures, and source measurements such as Kron radius, "windowed" position fitting, and half-light radius. It also adds the following features that are not available in Source Extractor: optimized matched filter for variable noise in source extraction; circular annulus and elliptical annulus aperture photometry functions; local background subtraction in shape consistent with aperture in aperture photometry functions; exact pixel overlap mode in all aperture photometry functions; and masking of elliptical regions on images.
Subpixel Event Repositioning (SER) techniques significantly improve the already unprecedented spatial resolution of Chandra X-ray imaging with the Advanced CCD Imaging Spectrometer (ACIS). Chandra CCD SER techniques are based on the premise that the impact position of events can be refined, based on the distribution of charge among affected CCD pixels. Unlike ACIS SER models that are restricted to corner split (3- and 4-pixel) events and assume that such events take place at the split pixel corners, this IDL code uses two-pixel splits as well, and incorporates more realistic estimates of photon impact positions.
SEREN is an astrophysical Smoothed Particle Hydrodynamics code designed to investigate star and planet formation problems using self-gravitating hydrodynamics simulations of molecular clouds, star-forming cores, and protostellar disks.
SEREN is written in Fortran 95/2003 with a modular philosophy for adding features into the code. Each feature can be easily activated or deactivated by way of setting options in the Makefile before compiling the code. This has the added benefit of allowing unwanted features to be removed at the compilation stage resulting in a smaller and faster executable program. SEREN is written with OpenMP directives to allow parallelization on shared-memory architecture.
SERPent is an automated reduction and RFI-mitigation procedure that uses the SumThreshold methodology. It was originally developed for the LOFAR pipeline. SERPent is written in Parseltongue, enabling interaction with the Astronomical Image Processing Software (AIPS) program. Moreover, SERPent is a simple "out of the box" Python script, which is easy to set up and is free of compilers.
Sérsic is an implementation of the exact deprojection of Sérsic surface brightness profiles described in Baes and Gentile (2011). This code depends on the mpmath python library for an implementation of the Meijer G function required by the Baes and Gentile (hereafter B+G) formulas for rational values of the Sérsic index. Sérsic requires rational Sérsic indices, but any irrational number can be approximated arbitrarily well by some rational number. The code also depends on scipy, but the dependence is mostly for testing. The implementation of the formulas and the formulas themselves have undergone comprehensive testing.
SERVAL calculates radial velocities (RVs) from stellar spectra. The code uses least-squares fitting algorithms to derive the RVs and additional spectral diagnostics. Forward modeling in pixel space is used to properly weight pixel errors, and the stellar templates are reconstructed from the observations themselves to make optimal use of the RV information inherent in the stellar spectra.
The SETI Encryption code, written in Python, creates a message for use in testing the decryptability of a simulated incoming interstellar message. The code uses images in a portable bit map (PBM) format, then writes the corresponding bits into the message, and finally returns both a PBM image and a text (TXT) file of the entire message. The natural constants (c, G, h) and the wavelength of the message are defined in the first few lines of the code, followed by the reading of the input files and their conversion into 757 strings of 359 bits to give one page. Each header of a page, i.e. the little-endian binary code translation of the tempo-spatial yardstick, is calculated and written on-the-fly for each page.
SExSeg forces SExtractor (ascl:1010.064) to run using a pre-defined segmentation map (the definition of objects and their borders). The defined segments double as isophotal apertures. SExSeg alters the detection image based on a pre-defined segmenation map while preparing your "analysis image" by subtracting the background in a separate SExtractor run (using parameters you specify). SExtractor is then run in "double-image" mode with the altered detection image and background-subtracted analysis image.
This new software optimally detects, de-blends, measures and classifies sources from astronomical images: SExtractor (Source Extractor). A very reliable star/galaxy separation can be achieved on most images using a neural network trained with simulated images. Salient features of SExtractor include its ability to work on very large images, with minimal human intervention, and to deal with a wide variety of object shapes and magnitudes. It is therefore particularly suited to the analysis of large extragalactic surveys.
sf3dmodels models star-forming regions; it brings together analytical models in order to compute their physical properties in a 3-dimensional grid. The package can couple different models in a single grid to recreate complex star forming systems such as those being revealed by current instruments. The output data can be read with LIME (ascl:1107.012) or RADMC-3D (ascl:1108.016) to carry out radiative transfer calculations of the modeled region.
SFH is an efficient IDL tool that quickly computes accurate predictions for the baryon budget history in a galactic halo.
SFoF is a friends-of-friends galaxy cluster detection algorithm that operates in either spectroscopic or photometric redshift space. The linking parameters, both transverse and along the line-of-sight, change as a function of redshift to account for selection effects.
SGNAPS allows the user to plot a one-dimensional spectrum, together with the corresponding two-dimensional and a reference spectrum (for example the sky spectrum). This makes it possible to check on the reality of spectral features that are present in the one-dimensional spectrum, which could be due to bad sky subtraction or fringing residuals. It is also possible to zoom in and out all three spectra, edit the one-dimensional spectrum, smooth it with a simple square window function, measure the signal to noise over a selected wavelength interval, and fit the position of a selected spectral line. SGNAPS also allows the astronomer to obtain quick redshift estimates by providing a tool to fit or mark the position of a spectral line, and a function that will compute a list of possible redshifts based on a list of known lines in galaxy spectra. SGNAPS is derived from the plotting tools of VIPGI and contains almost all of their capabilities.
NOTE: SGNAPS functionality has been transitioned to EZ.
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