Results 451-500 of 2195 (2158 ASCL, 37 submitted)
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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.
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