SimLine computes the profiles of molecular rotational transitions and atomic fine structure lines in spherically symmetric clouds with arbitrary density, temperature and velocity structure. The code is designed towards a maximum flexibility and very high accuracy based on a completely adaptive discretization of all quantities. The code can treat arbitrary species in spherically symmetric configurations with arbitrary velocity structures and optical depths between about -5 and 5000. Moreover, SimLine includes the treatment of turbulence and clumping effects in a local statistical approximation combined with a radial dependence of the correlation parameters. The code consists of two parts: the self-consistent solution of the balance equations for all level populations and energy densities at all radial points and the computation of the emergent line profiles observed from a telescope with finite beam width and arbitrary offset.

SImMER (Stellar Image Maturation via Efficient Reduction) reduces astronomical imaging data. It performs standard dark-subtraction and flat-fielding operations on data from, for example, the ShARCS camera on the Shane 3-m telescope at Lick Observatory and the PHARO camera on the Hale 5.1-m telescope at Palomar Observatory; its object-oriented design allows the software to be extended to other instruments. SImMER can also perform sky-subtraction, image registration, FWHM measurement, and contrast curve calculation, and can generate tables and plots. For widely separated stars which are of somewhat equal brightness, a “wide binary” mode allows the user to selects which star is the primary around which each image should be centered.

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.

simple_reg_dem reconstructs differential emission measures (DEMs) in the solar corona. It overcomes issues, such as complexity, idiosyncratic output, convergence difficulty, and lack of speed, that exists in other methods. Initially written for extreme ultraviolet (EUV) data, the algorithm is notable for its simplicity, and is robust and extensible to any other wavelengths (e.g., X-rays) where the DEM treatment is valid. It is available in the SolarSoft (ascl:1208.013) package.

Made-to-measure (M2M) is a standard technique for modeling the dynamics of astrophysical systems in which the system is modeled with a set of N particles with weights that are slowly optimized to fit a set of constraints while integrating these particles forward in the gravitational potential. Simple-m2m extends this standard technique to allow parameters of the system other than the particle weights to be fit as well, including nuisance parameters that describe the observer's relation to the dynamical system (e.g., the inclination) or parameters describing an external potential.

SIMPLE (Simple Intensity Map Producer for Line Emission) generates intensity maps that include observational effects such as noise, anisotropic smoothing, sky subtraction, and masking. Written in Python, it is based on a lognormal simulation of galaxies and random assignment of luminosities to these galaxies and generates mock intensity maps that can be used to study survey systematics and calculate covariance matrices of power spectra. The code is modular, allowing its components to be used independently.

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.

simqso generates mock quasar spectra and photometry. Simulated quasar spectra are built from a series of components. Common quasar models are built-in, such as a broken power-law continuum model and Gaussian emission line templates; however, the code allows user-defined features to be included. Mock spectra are generated at arbitrary resolution and can be used to produce broadband photometry representative of a number of surveys.

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.

simulateSearch simulates high time-resolution data in radio astronomy. The code is built around producing multiple binary data files that contain information on the radiometer noise and sources that are being simulated. These binary data files subsequently get combined and output PSRFITS
search mode files produced. The PSRFITS files can be processed using standard pulsar software packages such as PRESTO (ascl:1107.017).

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.

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.

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.

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:

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.

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.

SIRENA (Software Ifca for Reconstruction of EveNts for Athena X-IFU) reconstructs the energy of incoming X-ray photons after their detection in the X-IFU TES detector. It is integrated in the SIXTE (ascl:1903.002) end-to-end simulations environment where it currently runs over SIXTE simulated data. This is done by means of a tool called tesreconstruction, which is mainly a wrapper to pass a data file to the SIRENA tasks.

SISPO (Space Imaging Simulator for Proximity Operations) simulates trajectories, light parameters, and camera intrinsic parameters for small solar system body fly-by and terrestrial planet surface missions. The software provides realistic surface rendering and realistic dust- and gas-environment optical models for comets and active asteroids and also simulates common image aberrations such as simple geometric distortions and tangential astigmatism. SISPO uses Blender and its Cycles rendering engine, which provides physically based rendering capabilities and procedural micropolygon displacement texture generation.

SISTER (Starshade Imaging Simulations Toolkit for Exoplanet Reconnaissance) predicts how an exoplanet system would look in an instrument that utilizes an Starshade to block the light from the host star. The tool allows for controlling a set of parameters of the whole instrument for: (1) the Starshade design, (2) the exoplanetary system, (3) the telescope and (4) the camera. SISTER includes plotting software, and can also store simulations on disk for plotting with other software.

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.

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.

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.

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.

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.

SkyCalc-iPy (SkyCalc for interactive Python) accesses atmospheric emission and transmission data generated by ESO’s SkyCalc tool interactively with Python. This package is based on the command line tool by ESO for accessing spectra on the ESO SkyCalc server.

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:

• Tclutil - Generic Tcl and C++ utilities
• Astrotcl - Astronomical Tcl and C++ utilities
• RTD - Real-time Display classes and widgets
• Catlib - Catalog library and widgets
• Skycat - Skycat application and library package

All of the required packages are always included in the tarfile.

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.

The Skye framework develops and prototypes new EOS physics; it is not tied to a specific set of physics choices and can be extended for new effects by writing new terms in the free energy. It takes into account the effects of positrons, relativity, electron degeneracy, and non-linear mixing effects and more, and determines the point of Coulomb crystallization in a self-consistent manner. It is available in the MESA (ascl:1010.083) EOS module and as a standalone package.

Skye detects a statistically significant excess clustering of transit times, indicating that there are likely systematics at specific times that cause many false positive detections, for the Kepler DR25 planet candidate catalog. The technique could be used for any survey looking to statistically cull false alarms.

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.

Skylens++ implements a Layer-based raytracing framework particularly well-suited for realistic simulations of weak and strong gravitational lensing. Source galaxies can be drawn from analytic models or deep space-based imaging. Lens planes can be populated with arbitrary deflectors, typically either from N-body simulations or analytic lens models. Both sources and lenses can be placed at freely configurable positions into the light cone, in effect allowing for multiple source and lens planes.

SkyLine generates mock line-intensity maps (both in 3D and 2D) in a lightcone from a halo catalog, accounting for the evolution of clustering and astrophysical properties, and observational effects such as spectral and angular resolutions, line-interlopers, and galactic foregrounds. Using a given astrophysical model for the luminosity of each line, the code paints the signal for each emitter and generates the map, adding coherently all contributions of interest. In addition, SkyLine can generate maps with the distribution of Luminous Red Galaxies and Emitting Line Galaxies.

SkyMaker simulates astronomical images. It accepts object lists in ASCII generated by the Stuff program (ascl:1010.067) to produce realistic astronomical fields. SkyMaker is part of the EFIGI development project.

Skymapper maps astronomical survey data from the celestial sphere onto 2D using a collection of matplotlib instructions. It facilitates interactive work as well as the creation of publication-quality plots with a python-based workflow many astronomers are accustomed to. The primary motivation is a truthful representation of samples and fields from the curved sky in planar figures, which becomes relevant when sizable portions of the sky are observed.

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.

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.

Skyoffset makes wide-field mosaics of FITS images. Principal features of Skyoffset are the ability to produce a mosaic with a continuous background level by solving for sky offsets that minimize the intensity differences between overlapping images, and its handling of hierarchies, making it ideal for optimizing backgrounds in large mosaics made with array cameras (such as CFHT’s MegaCam and WIRCam). Skyoffset uses MongoDB in conjunction with Mo’Astro (ascl:2104.012) to store metadata about each mosaic and SWarp (ascl:1010.068) to handle image combination and propagate uncertainty maps. Skyoffset can be integrated into Python pipelines and offers a convenient API and metadata storage in MongoDB. It was developed originally for the Andromeda Optical and Infrared Disk Survey (ANDROIDS).

SkyPy simulates the astrophysical sky. It provides functions that sample realizations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models, while task scheduling and data dependencies are handled internally. The package's modular design, containing a library of physical and empirical models across a range of observables and a command line script to run end-to-end simulations, allows users to interface with external software.

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.

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.

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).

Many fields in science and engineering measure data that inherently live on non-Euclidean geometries, such as the sphere. Techniques developed in the Euclidean setting must be extended to other geometries. Due to recent interest in geometric deep learning, analogues of Euclidean techniques must also handle general manifolds or graphs. Often, data are only observed over partial regions of manifolds, and thus standard whole-manifold techniques may not yield accurate predictions. In this thesis, a new wavelet basis is designed for datasets like these.

Although many definitions of spherical convolutions exist, none fully emulate the Euclidean definition. A novel spherical convolution is developed, designed to tackle the shortcomings of existing methods. The so-called sifting convolution exploits the sifting property of the Dirac delta and follows by the inner product of a function with the translated version of another. This translation operator is analogous to the Euclidean translation in harmonic space and exhibits some useful properties. In particular, the sifting convolution supports directional kernels; has an output that remains on the sphere; and is efficient to compute. The convolution is entirely generic and thus may be used with any set of basis functions. An application of the sifting convolution with a topographic map of the Earth demonstrates that it supports directional kernels to perform anisotropic filtering.

Slepian wavelets are built upon the eigenfunctions of the Slepian concentration problem of the manifold - a set of bandlimited functions which are maximally concentrated within a given region. Wavelets are constructed through a tiling of the Slepian harmonic line by leveraging the existing scale-discretised framework. A straightforward denoising formalism demonstrates a boost in signal-to-noise for both a spherical and general manifold example. Whilst these wavelets were inspired by spherical datasets, like in cosmology, the wavelet construction may be utilised for manifold or graph data.

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.

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.

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.

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.

SLIT (Sparse Lens Inversion Technique) provides a method for inversion of lensed images in the frame of strong gravitational lensing. The code requires the input image along with lens mass profile and a PSF. The user then has to chose a maximum number of iterations after which the algorithm will stop if not converged and a image size ratio to the input image to set the resolution of the reconstructed source. Results are displayed in pyplot windows.

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.

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.

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.

Smart provides pre-processing for LP-VIcode (ascl:1501.007). It computes the accelerations and variational equations given a generic user-defined potential function, eliminating the need to calculate manually the accelerations and variational equations.

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.

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.

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.

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.

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:

• orbit integration in various 2d and 3d potentials (including N-body and basis-set representations of an arbitrary potential);
• methods for analysis of orbital class, fundamental frequencies, regular or chaotic nature of an orbit, computation of Lyapunov exponents;
• Poincaré sections (in 2d) and frequency maps (in 3d) for analyzing orbital structure of potential;
• construction of self-consistent Schwarzschild models; and
• convenient visualization and integrated GUI environment, and a console scriptable version.

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).

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.

Smooth calculates several mean quantities for all particles in an N-Body simulation output file. The program produces a file for each type of output specified on the command line. This output file is in ASCII format with one smoothed quantity for each particle. The program uses a symmetric SPH (Smoothed Particle Hydrodynamics) smoothing kernel to find the mean quantities.

smops interpolates input sub-band model FITS images, such as those produced by WSClean (ascl:1408.023), into more finely channelized sub-band model FITS images, thus generating model images at a higher frequency resolution. It is a Python-based command line tool. For example, given input model FITS images initially created from sub-dividing a given bandwidth into four, smops can subdivide that bandwidth further, resulting in more finely channelized model images, to a specified frequency resolution. This smooths out the stepwise behavior of models across frequency, which can improve the results of self-calibration with such models.

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.

SNANA is a general analysis package for supernova (SN) light curves that contains a simulation, light curve fitter, and cosmology fitter. The software is designed with the primary goal of using SNe Ia as distance indicators for the determination of cosmological parameters, but it can also be used to study efficiencies for analyses of SN rates, estimate contamination from non-Ia SNe, and optimize future surveys. Several SN models are available within the same software architecture, allowing technical features such as K-corrections to be consistently used among multiple models, and thus making it easier to make detailed comparisons between models. New and improved light-curve models can be easily added. The software works with arbitrary surveys and telescopes and has already been used by several collaborations, leading to more robust and easy-to-use code. This software is not intended as a final product release, but rather it is designed to undergo continual improvements from the community as more is learned about SNe.

SNAPDRAGONS (Stellar Numbers And Parameters Determined Routinely And Generated Observing N-body Systems) is a simplified version of the population synthesis code Galaxia (ascl:1101.007), using a different process to generate the stellar catalog. It splits each N-body particle from the galaxy simulation into an appropriate number of stellar particles to create a mock catalog of observable stars from the N-body model. SNAPDRAGON uses the same isochrones and extinction map as Galaxia.

SNCosmo synthesizes supernova spectra and photometry from SN models, and has functions for fitting and sampling SN model parameters given photometric light curve data. It offers fast implementations of several commonly used extinction laws and can be used to construct SN models that include dust. The SNCosmo library includes supernova models such as SALT2, MLCS2k2, Hsiao, Nugent, PSNID, SNANA and Whalen models, as well as a variety of built-in bandpasses and magnitude systems, and provides convenience functions for reading and writing peculiar data formats used in other packages. The library is extensible, allowing new models, bandpasses, and magnitude systems to be defined using an object-oriented interface.

SNEC (SuperNova Explosion Code) is a spherically-symmetric Lagrangian radiation-hydrodynamics code that follows supernova explosions through the envelope of their progenitor star, produces bolometric (and approximate multi-color) light curve predictions, and provides input to spectral synthesis codes for spectral modeling. SNEC's features include 1D (spherical) Lagrangian Newtonian hydrodynamics with artificial viscosity, stellar equation of state with a Saha solver ionization/recombination, equilibrium flux-limited photon diffusion with OPAL opacities and low-temperature opacities, and prediction of bolometric light curves and multi-color lightcurves (in the blackbody approximation).

SNEWPY uses simulated supernovae data to generate a time series of neutrino spectral fluences at Earth or the total time-integrated spectral fluence. The code can also process generated data through SNOwGLoBES (ascl:2109.019) and collate its output into the observable channels of each detector. Data from core-collapse, thermonuclear, and pair-instability supernovae simulations are included in the package.

We present an algorithm to identify the type of an SN spectrum and to determine its redshift and age. This algorithm, based on the correlation techniques of Tonry & Davis, is implemented in the Supernova Identification (SNID) code. It is used by members of ongoing high-redshift SN searches to distinguish between type Ia and type Ib/c SNe, and to identify "peculiar" SNe Ia. We develop a diagnostic to quantify the quality of a correlation between the input and template spectra, which enables a formal evaluation of the associated redshift error. Furthermore, by comparing the correlation redshifts obtained using SNID with those determined from narrow lines in the SN host galaxy spectrum, we show that accurate redshifts (with a typical error less than 0.01) can be determined for SNe Ia without a spectrum of the host galaxy. Last, the age of an input spectrum is determined with a typical 3-day accuracy, shown here by using high-redshift SNe Ia with well-sampled light curves. The success of the correlation technique confirms the similarity of some SNe Ia at low and high redshifts. The SNID code, which is available to the community, can also be used for comparative studies of SN spectra, as well as comparisons between data and models.

snmachine reads in photometric supernova light curves, extracts useful features from them, and subsequently performs supervised machine learning to classify supernovae based on their light curves. This python library is also flexible enough to easily extend to general transient classification.

Snoopy is a spectral 3D code that solves the MHD and Boussinesq equations, such as compressibility, particles, and Braginskii viscosity, and several other physical effects. It's useful for turbulence study involving shear and rotation. Snoopy requires the FFTW library (ascl:1201.015), and can run on parallel machine using MPI OpenMP or both at the same time.

The SNooPy package (also known as SNpy), written in Python, contains tools for the analysis of TypeIa supernovae. It offers interactive plotting of light-curve data and models (and spectra), computation of reddening laws and K-corrections, LM non-linear least-squares fitting of light-curve data, and various types of spline fitting, including Diercx and tension. The package also includes a SNIa lightcurve template generator in the CSP passbands, estimates of Milky-Way Extinction, and a module for dealing with filters and spectra.

Snowball models atmospheric loss in order to constrain an atmosphere's cumulative impact of historic X-ray and extreme ultraviolet radiation-driven mass loss. The escape model interpolates the BaSTI luminosity evolution grid to the observed mass and luminosity of the host star.

SNOwGLoBES (SuperNova Observatories with GLoBES) computes interaction rates and distributions of observed quantities for supernova burst neutrinos in common detector materials. The code provides a very simple and fast code and data package for tests of observability of physics signatures in current and future detectors, and for evaluation of relative sensitivities of different detector configurations. The event estimates are made using available cross-sections and parameterized detector responses. Water, argon, scintillator and lead-based configurations are included. The package makes use of GLoBES (ascl:2109.018). SNOwGLoBES is not intended to replace full detector simulations; however output should be useful for many types of studies, and simulation results can be incorporated.

SNRPy (Super Nova Remnant Python) models supernova remnant (SNR) evolution and is useful for understanding SNR evolution and to model observations of SNR for obtaining good estimates of SNR properties. It includes all phases for the standard path of evolution for spherically symmetric SNRs and includes alternate evolutionary models, including evolution in a cloudy ISM, the fractional energy loss model, and evolution in a hot low-density ISM. The graphical interface takes in various parameters and produces outputs such as shock radius and velocity vs. time, SNR surface brightness profile and spectrum.

SNSEDextend extrapolates core-collapse and Type Ia Spectral Energy Distributions (SEDs) into the UV and IR for use in simulations and photometric classifications. The user provides a library of existing SED templates (such as those in the authors' SN SED Repository) along with new photometric constraints in the UV and/or NIR wavelength ranges. The software then extends the existing template SEDs so their colors match the input data at all phases. SNSEDextend can also extend the SALT2 spectral time-series model for Type Ia SN for a "first-order" extrapolation of the SALT2 model components, suitable for use in survey simulations and photometric classification tools; as the code does not do a rigorous re-training of the SALT2 model, the results should not be relied on for precision applications such as light curve fitting for cosmology.

Supernova Time Delays (SNTD) simulates and measures time delay of multiply-imaged supernovae, and offers an improved characterization of the uncertainty caused by microlensing. Lensing time delays can be determined by fitting the multiple light curves of these objects; measuring these delays provide precise tests of lens models or constraints on the Hubble constant and other cosmological parameters that are independent of the local distance ladder. Fitting the effects of microlensing without an accurate prior often leads to biases in the time delay measurement and over-fitting to the data; this can be mitigated by using a Gaussian Process Regression (GPR) technique to determine the uncertainty due to microlensing. SNTD can produce accurate simulations for wide-field time domain surveys such as LSST and WFIRST.

so_noise_models is the N(ell) noise curve projection code for the Simons Observatory. The code, written in pure Python, consists of several independent sub-modules, representing each version of the noise code. The usage of the models can vary substantially from version to version. The package also includes demo code that that demonstrates usage of the noise models, such as by producing noise curve plots, effective noise power spectra for SO LAT component-separated CMB T, E, B, and Compton-y maps, and lensing noise curves from SO LAT component-separated CMB T, E, B maps.

SOAP (Spot Oscillation And Planet) 2.0 simulates the effects of dark spots and bright plages on the surface of a rotating star, computing their expected radial velocity and photometric signatures. It includes the convective blueshift and its inhibition in active regions.

SOAP-GPU is a revision of SOAP 2 (ascl:1504.021), which simulates spectral time series with the effect of active regions (spot, faculae or both). In addition to the traditional outputs of SOAP 2.0 (the cross-correlation function and extracted parameters: radial velocity, bisector span, full width at half maximum), SOAP-GPU generates the integrated spectra at each phase for given input spectra and spectral resolution. Additional capabilities include fast spectral simulation of stellar activity due to GPU acceleration, simulation of more complicated active region structures with superposition between active regions, and more realistic line bisectors, based on solar observations, that varies as function of mu angle for both quiet and active regions. In addition, SOAP-GPU accepts any input high resolution observed spectra. The PHOENIX synthetic spectral library are already implemented at the code level which allows users to simulate stellar activity for stars other than the Sun. Furthermore, SOAP-GPU simulates realistic spectral time series with either spot number/SDO image as additional inputs. The code is written in C and provides python scripts for input pre-processing and output post-processing.

SOFA (Standards Of Fundamental Astronomy) is a collection of subprograms, in source-code form, that implement official IAU algorithms for fundamental astronomy computations. SOFA offers more than 160 routines for fundamental astronomy, including time scales (including dealing with leap seconds), Earth rotation, sidereal time, precession, nutation, polar motion, astrometry and transforms between various reference systems (e.g. BCRS, ICRS, GCRS, CIRS, TIRS, ITRS). The subprograms are supported by 55 vector/matrix routines, and are available in both Fortran77 and C implementations.

SoFiA 2 is a fully automated spectral-line source finding pipeline originally intended for the detection of galaxies in large HI data cubes. It is a reimplementation of parts of the original SoFiA pipeline (ascl:1412.001) in the C programming language and uses OpenMP for multithreading, making it substantially faster and more memory-efficient than its predecessor. At its core, SoFiA 2 uses the Smooth + Clip algorithm for source finding which operates by spatially and spectrally smoothing the data on multiple scales and applying a user-defined flux threshold relative to the noise level in each iteration. A wide range of useful preconditioning and post-processing filters is available, including noise normalization, flagging of artifacts and reliability filtering. In addition to global data products and source catalogs in different formats, SoFiA 2 can also generate cutout images and spectra for each individual detection.

SoFiA is a flexible source finding pipeline designed to detect and parameterize sources in 3D spectral-line data cubes. SoFiA combines several powerful source finding and parameterization algorithms, including wavelet denoising, spatial and spectral smoothing, source mask optimization, spectral profile fitting, and calculation of the reliability of detections. In addition to source catalogues in different formats, SoFiA can also generate a range of output data cubes and images, including source masks, moment maps, sub-cubes, position-velocity diagrams, and integrated spectra. The pipeline is controlled by simple parameter files and can either be invoked on the command line or interactively through a modern graphical user interface.

A reimplementation of this pipeline using OpenMPI, SoFiA 2 (ascl:2109.005), is available.

SoFiAX is a web-based platform to merge and interact with the results of parallel execution of SoFiA HI source finding software [ascl:1412.001] and other steps of processing ASKAP Wallaby HI survey data.

Solar-MACH (Solar MAgnetic Connection HAUS) derives and visualizes the spatial configuration and solar magnetic connection of different observers (i.e., spacecraft or planets) in the heliosphere at different times. It provides publication-ready figures for analyzing Solar Energetic Particle events (SEPs) or solar transients such as Coronal Mass Ejections (CMEs). Solar-MACH is available as a Python package; a Streamlit-enabled tool that runs in a browser is also available (solar-mach.github.io)

SolarAxionFlux quantifies systematic differences and statistical uncertainties in the calculation of the solar axion flux from axion-photon and axion-electron interactions. Determining the limitations of these calculations can be used to identify potential improvements and help determine axion model parameters more accurately.

SolarKAT mitigates solar interference in MeerKAT data and recovers the visibilities rather than discarding them; this solar imaging pipeline takes 1GC calibrated data in Measurement Set format as input. Written in Python, the pipeline employs solar tracking, subtraction, and peeling techniques to enhance data quality by significantly reducing solar radio interference. This is achieved while preserving the flux measurements in the main field. SolarKAT is versatile and can be applied to general radio astronomy observations and solar radio astronomy; additionally, generated solar images can be used for weather forecasting. SolarKAT is deployed in Stimela (ascl:2305.007). It is based on existing radio astronomy software, including CASA (ascl:1107.013), breizorro (ascl:2305.009), WSclean (ascl:1408.023), Quartical (ascl:2305.006), and Astropy (ascl:1304.002).

SolarSoft is a set of integrated software libraries, data bases, and system utilities which provide a common programming and data analysis environment for Solar Physics. The SolarSoftWare (SSW) system is built from Yohkoh, SOHO, SDAC and Astronomy libraries and draws upon contributions from many members of those projects. It is primarily an IDL based system, although some instrument teams integrate executables written in other languages. The SSW environment provides a consistent look and feel at widely distributed co-investigator institutions to facilitate data exchange and to stimulate coordinated analysis. Commonalities and overlap in solar data and analysis goals are exploited to permit application of fundamental utilities to the data from many different solar instruments. The use of common libraries, utilities, techniques and interfaces minimizes the learning curve for investigators who are analyzing new solar data sets, correlating results from multiple experiments or performing research away from their home institution.

SolAster provides querying, analysis, and calculation methods to independently derive 'sun-as-a-star' RV variations using SDO/HMI data for any time span since SDO has begun observing. Scaling factors are provided in order to calculate RVs comparable to magnitudes measured by ground-based spectrographs (HARPS-N and NEID). In addition, there are routines to calculate magnetic observables to compare with RV variations and determine what is driving Solar activity.

SolTrack computes the position of the Sun, the rise and set times and azimuths, and transit times and altitudes. It includes corrections for aberration and parallax, and has a simple routine to correct for atmospheric refraction, taking into account local atmospheric conditions. SolTrack is derived from the Fortran library libTheSky (ascl:2209.018). The package can be used to track the Sun on a low-specs machine, such as a microcontroller or PLC, and can be used for (highly) concentrated (photovoltaic) solar power or accurate solar-energy modeling.

SONG computes the non-linear evolution of the Universe in order to predict cosmological observables such as the bispectrum of the Cosmic Microwave Background (CMB). More precisely, it is a second-order Boltzmann code, as it solves the Einstein and Boltzmann equations up to second order in the cosmological perturbations.

SOPHIA (Simulations Of Photo Hadronic Interactions in Astrophysics) solves problems connected to photohadronic processes in astrophysical environments and can also be used for radiation and background studies at high energy colliders such as LEP2 and HERA, as well as for simulations of photon induced air showers. SOPHIA implements well established phenomenological models, symmetries of hadronic interactions in a way that describes correctly the available exclusive and inclusive photohadronic cross section data obtained at fixed target and collider experiments.

SOPHISM models astronomical instrumentation from the entrance of the telescope to data acquisition at the detector, along with software blocks dealing with, for example, demodulation, inversion, and compression. The code performs most analyses done with light in astronomy, such as differential photometry, spectroscopy, and polarimetry. The simulator offers flexibility and implementation of new effects and subsystems, making it user-adaptable for a wide variety of instruments. SOPHISM can be used for all stages of instrument definition, design, operation, and lifetime tracking evaluation.

SOPIE (Sequential Off-Pulse Interval Estimation) provides functions to non-parametrically estimate the off-pulse interval of a source function originating from a pulsar. The technique is based on a sequential application of P-values obtained from goodness-of-fit tests for the uniform distribution, such as the Kolmogorov-Smirnov, Cramér-von Mises, Anderson-Darling and Rayleigh goodness-of-fit tests.

SOPT (Sparse OPTimisation) is a C implementation of the Sparsity Averaging Reweighted Analysis (SARA) algorithm. The approach relies on the observation that natural images exhibit strong average sparsity; average sparsity outperforms state-of-the-art priors that promote sparsity in a single orthonormal basis or redundant frame, or that promote gradient sparsity.

SORA optimally analyzes stellar occultation data. The library includes processes starting on the prediction of such events to the resulting size, shape and position of the Solar System object and can be used to build pipelines to analyze stellar occultation data. A stellar occultation is defined by the occulting body (Body), the occulted star (Star), and the time of the occultation. On the other hand, each observational station (Observer) will be associated with their light curve (LightCurve). SORA has tasks that allow the user to determine the immersion and emersion times and project them to the tangent sky plane, using the information within the Observer, Body and Star Objects. That projection will lead to chords that will be used to obtain the object’s apparent size, shape and position at the moment of the occultation. Automatic processes optimize the reduction of typical events. However, users have full control over the parameters and methods and can make changes in every step of the process.

Spin-Orbit Tomography (SOT) is a retrieval technique of a two-dimensional map of an Exo-Earth from time-series data of integrated reflection light. The software provides code for the Bayesian version of the static SOT and dynamic mapping (time-varying mapping) with full Bayesian modeling, and tutorials for L2 and Bayesian SOT are available in jupyter notebooks.

SourceXtractor++ extracts a catalog of sources from astronomical images; it is the successor to SExtractor (ascl:1010.064). SourceXtractor++ has been completely rewritten in C++ and improves over its predecessor in many ways. It provides support for multiple “measurement” images, has an optimized multi-object, multi-frame model-fitting engine, and can define complex priors and dependencies for model parameters. It also offers efficient image data caching and multi-threaded processing, and has a modular design with support for third-party plug-ins.

SOXS creates simulated X-ray observations of astrophysical sources. The package provides a comprehensive set of tools to design source models and convolve them with simulated models of X-ray observatories. In particular, SOXS is the primary simulation tool for simulations of Lynx and Line Emission Mapper observations. SOXS provides facilities for creating spectral models, simple spatial models for sources, astrophysical background and foreground models, as well as a Python implementation of the SIMPUT file format.

SP_Ace (Stellar Parameters And Chemical abundances Estimator) estimates the stellar parameters Teff, log g, [M/H], and elemental abundances. It employs 1D stellar atmosphere models in Local Thermodynamic Equilibrium (LTE). The code is highly automated and suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R = 2000-20 000). A web service for calculating these values with the software is also available.

The Solar Position Algorithm (SPA) calculates the solar zenith and azimuth angles in the period from the year -2000 to 6000, with uncertainties of +/- 0.0003 degrees based on the date, time, and location on Earth. SPA is implemented in C; in addition to being available for download, an online calculator using this code is available at https://www.nrel.gov/midc/solpos/spa.html.

SpaceHub uses unique algorithms for fast precise and accurate computations for few-body problems ranging from interacting black holes to planetary dynamics. This few-body gravity integration toolkit can treat black hole dynamics with extreme mass ratios, extreme eccentricities and very close encounters. SpaceHub offers a regularized Radau integrator with round off error control down to 64 bits floating point machine precision and can handle extremely eccentric orbits and close approaches in long-term integrations.