SMURF reduces submillimeter single-dish continuum and heterodyne data. It is mainly targeted at data produced by the James Clerk Maxwell Telescope but data from other telescopes have been reduced using the package. SMURF is released as part of the bundle that comprises Starlink (ascl:1110.012) and most of the packages that use it. The two key commands are MAKEMAP for the creation of maps from sub millimeter continuum data and MAKECUBE for the creation of data cubes from heterodyne array instruments. The software can also convert data from legacy JCMT file formats to the modern form to allow it to be processed by MAKECUBE. SMURF is a core component of the ORAC-DR (ascl:1310.001) data reduction pipeline for JCMT.
SMMOL (Spherical Multi-level MOLecular line radiative transfer) is a molecular line radiative transfer code that uses Accelerated Lambda Iteration to solve the coupled level population and line transfer problem in spherical geometry. The code uses a discretized grid and a ray tracing methodology. SMMOL is designed for high optical depth regimes and can cope with maser emission as long as the spatial-velocity sampling is fine enough.
SMILI uses sparse sampling techniques and other regularization methods for interferometric imaging. The python-interfaced library is mainly designed for very long baseline interferometry, and has been under the active development primarily for the Event Horizon Telescope (EHT).
SMILE is interactive software for studying a variety of 2D and 3D models, including arbitrary potentials represented by a basis-set expansion, a spherical-harmonic expansion with coefficients being smooth functions of radius (splines), or a set of fixed point masses. Its main features include:
SMERFS (Stochastic Markov Evaluation of Random Fields on the Sphere) creates large realizations of random fields on the sphere. It uses a fast algorithm based on Markov properties and fast Fourier Transforms in 1d that generates samples on an n X n grid in O(n2 log n) and efficiently derives the necessary conditional covariance matrices.
Spectroscopy Made Easy (SME) is IDL software and a compiled external library that fits an observed high-resolution stellar spectrum with a synthetic spectrum to determine stellar parameters. The SME external library is available for Mac, Linux, and Windows systems. Atomic and molecular line data formatted for SME may be obtained from VALD. SME can solve for empirical log(gf) and damping parameters, using an observed spectrum of a star (usually the Sun) as a constraint.
SMARTIES calculates the optical properties of oblate and prolate spheroidal particles, with comparable capabilities and ease-of-use as Mie theory for spheres. This suite of MATLAB codes provides a fully documented implementation of an improved T-matrix algorithm for the theoretical modelling of electromagnetic scattering by particles of spheroidal shape. Included are scripts that cover a range of scattering problems relevant to nanophotonics and plasmonics, including calculation of far-field scattering and absorption cross-sections for fixed incidence orientation, orientation-averaged cross-sections and scattering matrix, surface-field calculations as well as near-fields, wavelength-dependent near-field and far-field properties, and access to lower-level functions implementing the T-matrix calculations, including the T-matrix elements which may be calculated more accurately than with competing codes.
SMART is an IDL-based software tool, developed by the IRS Instrument Team at Cornell University, that allows users to reduce and analyze Spitzer data from all four modules of the Infrared Spectrograph, including the peak-up arrays. The software is designed to make full use of the ancillary files generated in the Spitzer Science Center pipeline so that it can either remove or flag artifacts and corrupted data and maximize the signal-to-noise ratio in the extraction routines. It can be run in both interactive and batch modes. SMART includes visualization tools for assessing data quality, basic arithmetic operations for either two-dimensional images or one-dimensional spectra, extraction of both point and extended sources, and a suite of spectral analysis tools.
The effects of stochasticity on the luminosities of stellar populations are an often neglected but crucial element for understanding populations in the low mass or low star formation rate regime. To address this issue, we present SLUG, a new code to "Stochastically Light Up Galaxies". SLUG synthesizes stellar populations using a Monte Carlo technique that treats stochastic sampling properly including the effects of clustering, the stellar initial mass function, star formation history, stellar evolution, and cluster disruption. This code produces many useful outputs, including i) catalogs of star clusters and their properties, such as their stellar initial mass distributions and their photometric properties in a variety of filters, ii) two dimensional histograms of color-magnitude diagrams of every star in the simulation, iii) and the photometric properties of field stars and the integrated photometry of the entire simulated galaxy. After presenting the SLUG algorithm in detail, we validate the code through comparisons with starburst99 in the well-sampled regime, and with observed photometry of Milky Way clusters. Finally, we demonstrate the SLUG's capabilities by presenting outputs in the stochastic regime.
Stellar Locus Regression (SLR) is a simple way to calibrate colors at the 1-2% level, and magnitudes at the sub-5% level as limited by 2MASS, without the traditional use of standard stars. With SLR, stars in any field are "standards." This is an entirely new way to calibrate photometry. SLR exploits the simple fact that most stars lie along a well defined line in color-color space called the stellar locus. Cross-match point-sources in flattened images taken through different passbands and plot up all color vs color combinations, and you will see the stellar locus with little effort. SLR calibrates colors by fitting these colors to a standard line. Cross-match with 2MASS on top of that, and SLR will deliver calibrated magnitudes as well.
SLOPES computes six least-squares linear regression lines for bivariate datasets of the form (x_i,y_i) with unknown population distributions. Measurement errors, censoring (nondetections) or other complications are not treated. The lines are: the ordinary least-squares regression of y on x, OLS(Y|X); the inverse regression of x on y, OLS(X_Y); the angular bisector of the OLS lines; the orthogonal regression line; the reduced major axis, and the mean-OLS line. The latter four regressions treat the variables symmetrically, while the first two regressions are asymmetrical. Uncertainties for the regression coefficients of each method are estimated via asymptotic formulae, bootstrap resampling, and bivariate normal simulation. These methods, derivation of the regression coefficient uncertainties, and discussions of their use are provided in three papers listed below. The user is encouraged to read and reference these studies.
slimplectic is a python implementation of a numerical integrator that uses a fixed time-step variational integrator formalism applied to the principle of stationary nonconservative action. It allows nonconservative effects to be included in the numerical evolution while preserving the major benefits of normally conservative symplectic integrators, particularly the accurate long-term evolution of momenta and energy. slimplectic is appropriate for exploring cosmological or celestial N-body dynamics problems where nonconservative interactions, e.g. dynamical friction or dissipative tides, can play an important role.
Slim performs lossless compression on binary data files. Written in C++, it operates very rapidly and achieves better compression on noisy physics data than general-purpose tools designed primarily for text.
The semi-spectral linear MHD (SLiM) code follows the interaction of linear waves through an inhomogeneous three-dimensional solar atmosphere. The background model allows almost arbitrary perturbations of density, temperature, sound speed as well as magnetic and velocity fields. The code is useful in understanding the helioseismic signatures of various solar features, including sunspots.
SlicerAstro extends 3D Slicer, a multi-platform package for visualization and medical image processing, to provide a 3-D interactive viewer with 3-D human-machine interaction features, based on traditional 2-D input/output hardware, and analysis capabilities.
SLALIB is a library of routines that make accurate and reliable positional-astronomy applications easier to write. Most SLALIB routines are concerned with astronomical position and time, but a number have wider trigonometrical, numerical or general applications. A Fortran implementation of SLALIB under GPL licensing is available as part of Starlink (ascl:1110.012).
SL1M deconvolves radio synthesis images based on direct inversion of the measured visibilities that can deal with the non-coplanar base line effect and can be applied to telescopes with direction dependent gains. The code is more computationally demanding than some existing methods, but is highly parallelizable and scale well to clusters of CPUs and GPUs. The algorithm is also extremely flexible, allowing the solution of the deconvolution problem on arbitrarily placed pixels.
The SkyView Virtual telescope provides access to survey datasets ranging from radio through the gamma-ray regimes. Over 100 survey datasets are currently available. The SkyView library referenced here is used as the basis for the SkyView web site (at http://skvyiew.gsfc.nasa.gov) but is designed for individual use by researchers as well.
SkyView's approach to access surveys is distinct from most other toolkits. Rather than providing links to the original data, SkyView attempts to immediately re-render the source data in the user-requested reference frame, projection, scaling, orientation, etc. The library includes a set of geometry transformation and mosaicking tools that may be integrated into other applications independent of SkyView.
SkyNet is an efficient and robust neural network training code for machine learning. It is able to train large and deep feed-forward neural networks, including autoencoders, for use in a wide range of supervised and unsupervised learning applications, such as regression, classification, density estimation, clustering and dimensionality reduction. SkyNet is implemented in C/C++ and fully parallelized using MPI.
The general-purpose nuclear reaction network SkyNet evolves the abundances of nuclear species under the influence of nuclear reactions. SkyNet can be used to compute the nucleosynthesis evolution in all astrophysical scenarios where nucleosynthesis occurs. Any list of isotopes can be evolved and SkyNet supports various different types of nuclear reactions. SkyNet is modular, permitting new or existing physics, such as nuclear reactions or equations of state, to be easily added or modified.
SkyMaker is a program that simulates astronomical images. It accepts object lists in ASCII generated by the Stuff program to produce realistic astronomical fields. SkyMaker is part of the EFIGI development project.
Skyfield computes positions for the stars, planets, and satellites in orbit around the Earth. Its results should agree with the positions generated by the United States Naval Observatory and their Astronomical Almanac to within 0.0005 arcseconds (which equals half a “mas” or milliarcsecond). It computes geocentric coordinates or topocentric coordinates specific to your location on the Earth’s surface. Skyfield accepts AstroPy (ascl:1304.002) time objects as input and can return results in native AstroPy units but is not dependend on AstroPy nor its compiled libraries.
Skycorr is an instrument-independent sky subtraction code that uses physically motivated line group scaling in the reference sky spectrum by a fitting approach for an improved sky line removal in the object spectrum. Possible wavelength shifts between both spectra are corrected by fitting Chebyshev polynomials and advanced rebinning without resolution decrease. For the correction, the optimized sky line spectrum and the automatically separated sky continuum (without scaling) is subtracted from the input object spectrum. Tests show that Skycorr performs well (per cent level residuals) for data in different wavelength regimes and of different resolution, even in the cases of relatively long time lags between the object and the reference sky spectrum. Lower quality results are mainly restricted to wavelengths not dominated by airglow lines or pseudo continua by unresolved strong emission bands.
SkyCat is a tool that combines visualization of images and access to catalogs and archive data for astronomy. The tool, developed in Tcl/Tk, was originally conceived as a demo of the capabilities of the class library that was developed for the VLT. The Skycat sources currently consist of five packages:
Written in Fortran 90, Sky3D solves the static or dynamic equations on a three-dimensional Cartesian mesh with isolated or periodic boundary conditions and no further symmetry assumptions. Pairing can be included in the BCS approximation for the static case. The code can be easily modified to include additional physics or special analysis of the results and requires LAPACK and FFTW3.
SKIRT is a radiative transfer code based on the Monte Carlo technique. The name SKIRT, acronym for Stellar Kinematics Including Radiative Transfer, reflects the original motivation for its creation: it has been developed to study the effects of dust absorption and scattering on the observed kinematics of dusty galaxies. In a second stage, the SKIRT code was extended with a module to self-consistently calculate the dust emission spectrum under the assumption of local thermal equilibrium. This LTE version of SKIRT has been used to model the dust extinction and emission of various types of galaxies, as well as circumstellar discs and clumpy tori around active galactic nuclei. A new, extended version of SKIRT code can perform efficient 3D radiative transfer calculations including a self-consistent calculation of the dust temperature distribution and the associated FIR/submm emission with a full incorporation of the emission of transiently heated grains and PAH molecules.
SKID finds gravitationally bound groups in N-body simulations. The SKID program will group different types of particles depending on the type of input binary file. This could be either dark matter particles, gas particles, star particles or gas and star particles depending on what is in the input tipsy binary file. Once groups with at least a certain minimum number of members have been determined, SKID will remove particles which are not bound to the group. SKID must use the original positions of all the particles to determine whether or not particles are bound. This procedure which we call unbinding, is again dependent on the type of grouping we are dealing with. There are two cases, one for dark matter only or star particles only (case 1 unbinding), the other for inputs including gas (also stars in a dark matter environment this is case 2 unbinding).
Skid version 1.3 is a much improved version of the old denmax-1.1 version. The new name was given to avoid confusion with the DENMAX program of Gelb & Bertschinger, and although it is based on the same idea it represents a substantial evolution in the method.
SIXTE simulates X-Ray telescope observation; the software performs instrument performance analyses and produces simulated event files for mission and analysis studies. SIXTE strives to find a compromise between exactness of the simulation and speed. Using calibration files such as the PSF, RMF and ARF makes efficient simulations possible at comparably high speed, even though they include nonlinear effects such as pileup. Setups for some current and future missions, such as XMM-Newton and Athena, are included in the package; others can be added by the user with relatively little effort through specifying the main instrument characteristics in a flexible, human-readable XML-based format. Properties of X-ray sources to be simulated are described in a detector-independent format, i.e., the same input can be used for simulating observations with all available instruments, and the same input can also be used for simulations with the SIMX simulator. The input files are easily generated from standard data such as XSPEC (ascl:9910.005) spectral models or FITS images with tools provided with the SIXTE distribution. The input data scale well from single point sources up to very complicated setups.
SITools2 is a CNES generic tool performed by a joint effort between CNES and scientific laboratories. SITools provides a self-manageable data access layer deployed on already existing scientific laboratory databases. This new version of SITools is a JAVA-based framework, under open source license, that provides a portable archive system, highly configurable, easy to use by laboratories, with a plugin mechanism so developers can add their own applications.
SIR is a general-purpose code capable of dealing with gradients of the physical quantities with height. It admits one and two-component model atmospheres. It allows the recovery of the stratification of the temperature, the magnetic field vector, and the line of sight velocity through the atmosphere, and the micro- and macroturbulence velocities - which are assumed to be constant with depth. It is based on the response functions, which enter a Marquardt nonlinear least-squares algorithm in a natural way. Response functions are calculated at the same time as the full radiative transfer equation for polarized light is integrated, which determines values of many free parameters in a reasonable computation time. SIR demonstrates high stability, accuracy, and uniqueness of results, even when simulated observations present signal-to-noise ratios of the order of the lowest acceptable values in real observations.
SIP (Systematics-Insensitive Periodograms) extends the generative model used to create traditional sine-fitting periodograms for finding the frequency of a sinusoid by including systematic trends based on a set of eigen light curves in the generative model in addition to using a sum of sine and cosine functions over a grid of frequencies, producing periodograms with vastly reduced systematic features. Acoustic oscillations in giant stars and measurement of stellar rotation periods can be recovered from the SIP periodograms without detrending. The code can also be applied to detection other periodic phenomena, including eclipsing binaries and short-period exoplanet candidates.
SofteningLength: Because Newton's law of Gravitation diverges as the relative separations |r'-r| tends to zero, it is common to add a positive constant λ also known as the "softening length", i.e. :
SingLe determines the appropriate value of this Softening Length λ for a given disc local structure (thickness 2h and vertical stratification ρ), in the axially symmetric, flat disc limit, preserving at best the Newtonian character of the gravitational potential and associated forces. Mass density ρ(z) is assumed to be locally expandable in the z-direction according to:
The SINFONI pipeline reduces data from the Very Large Telescope's SINFONI (Spectrograph for INtegral Field Observations in the Near Infrared) instrument. It can evaluate the detector linearity and generate a corresponding non linear pixel map, create a master dark and a hot-pixel map, a master flat and a map of pixels which have intensities greater than a given threshold. It can also compute the optical distortions and slitlets distances, and perform wavelength calibration, PSF, telluric standard and other science data reduction, and can coadd bad pixel maps, collapse a cube to an image over a given wavelength range, perform cube arithmetics, among other useful tasks.
SIMX simulates a photon-counting detector's response to an input source, including a simplified model of any telescope. The code is not a full ray-trace, but a convolution tool that uses standard descriptions of telescope PSF (via either a simple Gaussian parameter, an energy-dependent encircled-energy function, or an image of the PSF) and the detector response (using the OGIP response function) to model how sources will appear. simx uses a predefined set of PSFs, vignetting information, and instrumental responses and outputs to make the simulation. It is designed to be a 'approximation' tool to estimate issues such as source confusion, background effects, pileup, and other similar issues.
simuTrans models transit light curves affected by gravity-darkened stars. The code defines a star on a grid by modeling the brightness of each point as blackbody emission, then sets a series of parameters and uses emcee (ascl:1303.002) to explore the posterior probability distribution for the remaining fitted parameters and determine their best-fit values.
The R-package SimSpin measures the kinematics of a galaxy simulation as if it had been observed using an IFU. The functions included in the package can produce a kinematic data cube and measure the "observables" from this data cube, specifically the observable spin parameter λr. This package, once installed, is fully documented and tested.
SimpLens illustrates some of the theoretical ideas important in gravitational lensing in an interactive way. After setting parameters for elliptical mass distribution and external mass, SimpLens displays the mass profile and source position, the lens potential and image locations, and indicate the image magnifications and contours of virtual light-travel time. A lens profile can be made shallower or steeper with little change in the image positions and with only total magnification affected.
This is an implementation of a fairly simple-minded luminosity distance fitter, intended for use with supernova data. The calculational technique is based on evaluating the $chi^2$ of the model fit on a grid and marginalization over various nuisance parameters. Of course, the nature of these things is that this code has gotten steadily more complex, so perhaps the simple moniker is no longer justified.
SimFast 21 generates a simulation of the cosmological 21cm signal. While limited to low spatial resolution, the next generation low-frequency radio interferometers that target 21 cm observations during the era of reionization and prior will have instantaneous fields-of-view that are many tens of square degrees on the sky. Predictions related to various statistical measurements of the 21 cm brightness temperature must then be pursued with numerical simulations of reionization with correspondingly large volume box sizes, of order 1000 Mpc on one side. The authors pursued a semi-numerical scheme to simulate the 21 cm signal during and prior to Reionization by extending a hybrid approach where simulations are performed by first laying down the linear dark matter density field, accounting for the non-linear evolution of the density field based on second-order linear perturbation theory as specified by the Zel'dovich approximation, and then specifying the location and mass of collapsed dark matter halos using the excursion-set formalism. The location of ionizing sources and the time evolving distribution of ionization field is also specified using an excursion-set algorithm. They account for the brightness temperature evolution through the coupling between spin and gas temperature due to collisions, radiative coupling in the presence of Lyman-alpha photons and heating of the intergalactic medium, such as due to a background of X-ray photons. The method is capable of producing the required large volume simulations with adequate resolution in a reasonable time so a large number of realizations can be obtained with variations in assumptions related to astrophysics and background cosmology that govern the 21 cm signal.
SimCADO is a python package which allows the user to simulate observations with any NIR/Vis imaging system. The package was originally designed to simulate images for the European extremely large telescope (ELT) and MICADO, however with the proper input it is capable of simulating observations from many different Telescope + Instrument configurations.
The documentation can be found here: https://simcado.readthedocs.io/en/latest/
The SIM5 library contains routines for relativistic raytracing and radiation transfer in GR. Written C with a Python interface, it has a special focus on raytracing from accretion disks, tori, hot spots or any other 3D configuration of matter in Kerr geometry, but it can be used with any other metric as well. It handles both optically thick and thin sources as well as transport of polarization of the radiation and calculates the propagation of light rays from the source to an observer through a curved spacetime. It supports parallelization and runs on GPUs.
The ESO's VLT/SPHERE instrument includes a unique long-slit spectroscopy (LSS) mode coupled with Lyot coronagraphy in its infrared dual-band imager and spectrograph (IRDIS) for spectral characterization of young, giant exoplanets detected by direct imaging. The SILSS pipeline is a combination of the official SPHERE pipeline and additional custom IDL routines developed within the SPHERE consortium for the speckle subtraction and spectral extraction of a companion's spectrum; it offers a complete end-to-end pipeline, from raw data (science+calibrations) to a final spectrum of the companion. SILSS works on both the low-resolution (LRS) and medium-resolution (MRS) data, and allows correction for some of the known biases of the instrument. Documentation is included in the header of the main routine of the pipeline.
SIGPROC is a package designed to standardize the initial analysis of the many types of fast-sampled pulsar data. Currently recognized machines are the Wide Band Arecibo Pulsar Processor (WAPP), the Penn State Pulsar Machine (PSPM), the Arecibo Observatory Fourier Transform Machine (AOFTM), the Berkeley Pulsar Processors (BPP), the Parkes/Jodrell 1-bit filterbanks (SCAMP) and the filterbank at the Ooty radio telescope (OOTY). The SIGPROC tools should help users look at their data quickly, without the need to write (yet) another routine to read data or worry about big/little endian compatibility (byte swapping is handled automatically).
SiFTO is an empirical method for modeling Type Ia supernova (SN Ia) light curves by manipulating a spectral template. We make use of high-redshift SN data when training the model, allowing us to extend it bluer than rest-frame U. This increases the utility of our high-redshift SN observations by allowing us to use more of the available data. We find that when the shape of the light curve is described using a stretch prescription, applying the same stretch at all wavelengths is not an adequate description. SiFTO therefore uses a generalization of stretch which applies different stretch factors as a function of both the wavelength of the observed filter and the stretch in the rest-frame B band. SiFTO has been compared to other published light-curve models by applying them to the same set of SN photometry, and it's been demonstrated that SiFTO and SALT2 perform better than the alternatives when judged by the scatter around the best-fit luminosity distance relationship. When SiFTO and SALT2 are trained on the same data set the cosmological results agree.
Self-Interacting Dark Matter (SIDM) is a hypothetical model for cold dark matter in the Universe. A strong interaction between dark matter particles introduce a different physics inside dark-matter haloes, making the density profile cored, reduce the number of subhaloes, and trigger gravothermal collapse. sidm-nbody is an N-body simulation code with Direct Simulation Monte Carlo scattering for self interaction, and some codes to analyse gravothermal collapse of isolated haloes. The N-body simulation is based on GADGET 1.1.
SICON (Stokes Inversion based on COnvolutional Neural networks) provides a three-dimensional cube of thermodynamical and magnetic properties from the interpretation of two-dimensional maps of Stokes profiles by use of a convolutional neural network. In addition to being much faster than parallelized inversion codes, SICON, when trained on synthetic Stokes profiles from two numerical simulations of different structures of the solar atmosphere, also provided a three-dimensional view of the physical properties of the region of interest in geometrical height, and pressure and Wilson depression properties that are decontaminated from the blurring effect of instrumental point spread functions.
sick infers astrophysical parameters from noisy observed spectra. Phenomena that can alter the data (e.g., redshift, continuum, instrumental broadening, outlier pixels) are modeled and simultaneously inferred with the astrophysical parameters of interest. This package relies on emcee (ascl:1303.002); it is best suited for situations where a grid of model spectra already exists, and one would like to infer model parameters given some data.
sic (Sparse Inpainting Code) generates Gaussian, isotropic CMB realizations, masks them, and recovers the large-scale masked data using sparse inpainting; it is written in Fortran90.
Shwirl visualizes spectral data cubes with meaningful coloring methods. The program has been developed to investigate transfer functions, which combines volumetric elements (or voxels) to set the color, and graphics shaders, functions used to compute several properties of the final image such as color, depth, and/or transparency, as enablers for scientific visualization of astronomical data. The program uses Astropy (ascl:1304.002) to handle FITS files and World Coordinate System, Qt (and PyQt) for the user interface, and VisPy, an object-oriented Python visualization library binding onto OpenGL.
SHTOOLS performs (among others) spherical harmonic transforms and reconstructions, rotations of spherical harmonic coefficients, and multitaper spectral analyses on the sphere. The package accommodates any standard normalization of the spherical harmonic functions ("geodesy" 4π normalized, Schmidt semi-normalized, orthonormalized, and unnormalized), and either real or complex spherical harmonics can be employed. Spherical harmonic transforms are calculated by exact quadrature rules using either (1) the sampling theorem of Driscoll and Healy (1994) where data are equally sampled (or spaced) in latitude and longitude, or (2) Gauss-Legendre quadrature. A least squares inversion routine for irregularly sampled data is included as well. The Condon-Shortley phase factor of (-1)m can be used or excluded with the associated Legendre functions. The spherical harmonic transforms are accurate to approximately degree 2800, corresponding to a spatial resolution of better than 4 arc minutes. Routines are included for performing localized multitaper spectral analyses and standard gravity calculations, such as computation of the geoid, and the determination of the potential associated with finite-amplitude topography. The routines are fast. Spherical harmonic transforms and reconstructions take on the order of 1 second for bandwidths less than 600 and about 3 minutes for bandwidths close to 2800.
Sherpa is the CIAO (ascl:1311.006) modeling and fitting application made available by the Chandra X-ray Center (CXC). It can be used for analysis of images, spectra and time series from many telescopes, including optical telescopes such as Hubble. Sherpa is flexible, modular and extensible. It has an IPython user interface and it is also an importable Python module. Sherpa models, optimization and statistic functions are available via both C++ and Python for software developers wishing to link such functions directly to their own compiled code.
The CIAO 4.3 Sherpa release supports fitting of 1-D X-ray spectra from Chandra and other X-ray missions, as well as 1-D non-X-ray data, including ASCII data arrays, radial profiles, and lightcurves. The options for grating data analysis include fitting the spectrum with multiple response files required for overlapping orders in LETG observations. Modeling of 2-D spatial data is fully supported, including the PSF and exposure maps. User specified models can be added to Sherpa with advanced "user model" functionality.
Current and upcoming wide-field, ground-based, broad-band imaging surveys promise to address a wide range of outstanding problems in galaxy formation and cosmology. Several such uses of ground-based data, especially weak gravitational lensing, require highly precise measurements of galaxy image statistics with careful correction for the effects of the point-spread function (PSF). The SHERA (SHEar Reconvolution Analysis) software simulates ground-based imaging data with realistic galaxy morphologies and observing conditions, starting from space-based data (from COSMOS, the Cosmological Evolution Survey) and accounting for the effects of the space-based PSF. This code simulates ground-based data, optionally with a weak lensing shear applied, in a model-independent way using a general Fourier space formalism. The utility of this pipeline is that it allows for a precise, realistic assessment of systematic errors due to the method of data processing, for example in extracting weak lensing galaxy shape measurements or galaxy radial profiles, given user-supplied observational conditions and real galaxy morphologies. Moreover, the simulations allow for the empirical test of error estimates and determination of parameter degeneracies, via generation of many noise maps. The public release of this software, along with a large sample of cleaned COSMOS galaxy images (corrected for charge transfer inefficiency), should enable upcoming ground-based imaging surveys to achieve their potential in the areas of precision weak lensing analysis, galaxy profile measurement, and other applications involving detailed image analysis.
This code is no longer maintained and has been superseded by GalSim (ascl:1402.009).
SHELLSPEC is designed to calculate lightcurves, spectra and images of interacting binaries and extrasolar planets immersed in a moving circumstellar environment which is optically thin. It solves simple radiative transfer along the line of sight in moving media. The assumptions include LTE and optional known state quantities and velocity fields in 3D. Optional (non)transparent objects such as a spot, disc, stream, jet, shell or stars as well as an empty space may be defined (embedded) in 3D and their composite synthetic spectrum calculated. Roche model can be used as a boundary condition for the radiative tranfer. The program does not solve the inverse problem of finding the stellar and orbital parameters.
The Spherical Harmonic Discrete Ordinate Method (SHDOM) radiative transfer model computes polarized monochromatic or spectral band radiative transfer in a one, two, or three-dimensional medium for either collimated solar and/or thermal emission sources of radiation. The model is written in a variant of Fortran 77 and in Fortran90 and requires a Fortran 90 compiler. Also included are programs for generating the optical property files input to SHDOM from physical properties of water cloud particles and aerosols.
Shark is a flexible semi-analytic galaxy formation model for easy exploration of different physical processes. Shark has been implemented with several models for gas cooling, active galactic nuclei, stellar and photo-ionization feedback, and star formation (SF). The software can determine the stellar mass function and stellar–halo mass relation at z=0–4; cosmic evolution of the star formation rate density, stellar mass, atomic and molecular hydrogen; local gas scaling relations; and structural galaxy properties. It performs particularly well for the mass–size relation for discs/bulges, the gas–stellar mass and stellar mass–metallicity relations. Shark is written in C++11 and has been parallelized with OpenMP.
Shapelets are a complete, orthonormal set of 2D basis functions constructed from Laguerre or Hermite polynomials weighted by a Gaussian. A linear combination of these functions can be used to model any image, in a similar way to Fourier or wavelet synthesis. The shapelet decomposition is particularly efficient for images localized in space, and provide a high level of compression for individual galaxies in astronomical data. The basis has many elegant mathematical properties that make it convenient for image analysis and processing.
Shape is a flexible interactive 3D morpho-kinematical modeling application for astrophysics. It reduces the restrictions on the physical assumptions, data type and amount required for a reconstruction of an object's morphology. It applies interactive graphics and allows astrophysicists to provide a-priori knowledge about the object by interactively defining 3D structural elements. By direct comparison of model prediction with observational data, model parameters can then be automatically optimized to fit the observation.
Complicated cosmic string loops will fragment until they reach simple, non-intersecting ("stable") configurations. Through extensive numerical study we characterize these attractor loop shapes including their length, velocity, kink, and cusp distributions. We find that an initial loop containing $M$ harmonic modes will, on average, split into 3M stable loops. These stable loops are approximately described by the degenerate kinky loop, which is planar and rectangular, independently of the number of modes on the initial loop. This is confirmed by an analytic construction of a stable family of perturbed degenerate kinky loops. The average stable loop is also found to have a 40% chance of containing a cusp. We examine the properties of stable loops of different lengths and find only slight variation. Finally we develop a new analytic scheme to explicitly solve the string constraint equations.
Shadowfax simulates galaxy evolution. Written in object-oriented modular C++, it evolves a mixture of gas, subject to the laws of hydrodynamics and gravity, and any collisionless fluid only subject to gravity, such as cold dark matter or stars. For the hydrodynamical integration, it makes use of a (co-) moving Lagrangian mesh. The code has a 2D and 3D version, contains utility programs to generate initial conditions and visualize simulation snapshots, and its input/output is compatible with a number of other simulation codes, e.g. Gadget2 (ascl:0003.001) and GIZMO (ascl:1410.003).
SgrbWorldModel, written in Fortran 90, presents an attempt at modeling the population distribution of the Short-duration class of Gamma-Ray Bursts (SGRBs) as detected by the NASA's now-defunct Burst And Transient Source Experiment (BATSE) onboard the Compton Gamma Ray Observatory (CGRO). It is assumed that the population distribution of SGRBs is well fit by a multivariate log-normal distribution, whose differential cosmological rate of occurrence follows the Star-Formation-Rate (SFR) convolved with a log-normal binary-merger delay-time distribution. The best-fit parameters of the model are then found by maximizing the likelihood of the observed data by the BATSE detectors via a native built-in Adaptive Metropolis-Hastings Markov-Chain Monte Carlo (AMH-MCMC)Sampler that is part of the code. A model for the detection algorithm of the BATSE detectors is also provided.
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.
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.
SFH is an efficient IDL tool that quickly computes accurate predictions for the baryon budget history in a galactic halo.
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.
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.
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.
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.
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