SIMBI simulates heterogeneous relativistic gas dynamics up to 3d for special relativistic hydrodynamics and up to 2D Newtonian hydrodynamics. It supports user-defined mesh expansion and contraction, density, momentum, and energy density terms outside of grid; the code also supports source terms in the Euler equations and source terms at the boundaries. Boundary conditions, which include periodic, reflecting, outflow, and inflow boundaries, are given as an array of strings. If an inflow boundary condition is set but no inflow boundary source terms are given, SIMBI switches to outflow boundary conditions to prevent crashes. The code can track a single passive scalar, insert an immersed boundary, and is impermeable by default. SIMBI USES the Cython framework to blend together C++, CUDA, HIP, and Python.

SimCADO simulates observations with any NIR/Vis imaging system. Though the package was originally designed to simulate images for the European Extremely Large Telescope (ELT) and MICADO, with the proper input, it is capable of simulating observations from many different telescope and instrument configurations.

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.

Simframe facilitates setting up and running scientific simulations. The package organizes simulation data into fields derived from NumPy arrays, allowing users to define variables, parameters, and differential equations within a unified simulation frame. It includes numerical integration schemes—both explicit and implicit—to evolve model variables and supports adaptive step sizes and custom integration methods. simframe also provides tools for structuring simulation components, updating variables during integration, and writing or reading output data files. Example applications include solving coupled differential equations and modeling dynamical systems such as N-body problems or compartmental models.

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 (<i>e.g.</i>, 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 (<i>e.g.</i>, 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.

<strong>S</strong><small>often</small><strong>ingLe</strong><small>ngth</small>: 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. : <div style="text-align: center;">|r'-r|² ← |r'-r|² + λ².</div> 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: <div style="text-align: center;">ρ(z)= ρ₀[1 + a₁(z/h)²+...+a_q (z/h)^2q+...+a_N (z/h)^{2 N}].</div>

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.

Siril reduces reduction and improves the signal/noise ratio of an image from multiple captures. It can can align automatically or manually, and stack and enhance pictures from various file formats, even image sequence files (films and SER files). Its Graphical User Interface (GUI) allows manual processing of images in addition to scripts or typing commands. Siril provides astrometry and photometry options and performs geometric transformations in addition to many other tools.

SIROCCO (Simulating Ionization and Radiation in Outflows Created by Compact Objects) simulates ionisation and radiative transfer in outflows created by compact objects using a Monte Carlo framework using the Sobolev approximation. Formerly known as Python and renamed in October 2024, the code models azimuthally-symmetric winds and computes photon-packet propagation through user-specified wind geometries. SIROCCO reads input parameter files and atomic-data tables and produces synthetic spectra and diagnostic tables of ionisation structure.

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.

Skaro populates a Milky‑Way–like galaxy with synthetic planetary systems by combining high‑resolution hydrodynamical galaxy formation outputs from the HESTIA simulations with planet population synthesis from the New Generation Planet Population Synthesis (NGPPS) framework. The code assigns planets to stars based on host‑star mass and metallicity, identifies distinct Galactic morphological components (<i>e.g.</i>, bulge, thin disk, thick disk, halo), and computes distributions and occurrence rates of planets across these components. It provides routines for data handling, analysis of stellar and planetary populations, and visualization (<i>e.g.</i>, radial profiles and spatial maps) to study how exoplanet demographics vary with Galactic environment.

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 <span style="font-style: italic">tipsy</span> 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 <a href="https://www.eso.org/observing/etc/bin/gen/form?INS.MODE=swspectr+INS.NAME=SKYCALC">ESO’s SkyCalc tool</a> 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 <a href="http://www.efigi.org/">EFIGI</a> 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.

Skynet SOAP is a field-wide aperture photometry pipeline for astronomical observations from the Skynet Robotic Telescope Network. The software performs automated source extraction, background subtraction, aperture photometry, catalog cross-matching, and photometric calibration for all sources in an image. It supports SEP-based source extraction and photometry, forced photometry at user-specified sky positions, limiting-magnitude estimation, configurable aperture selection, calibration against catalogs including SkyMapper, APASS, and Pan-STARRS, and export to multiple tabular formats. Originally designed for follow-up observations of gamma-ray bursts, the pipeline enables science-ready photometric analysis of transient and time-domain observations made with Skynet.

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.

skysurvey simulates astronomical targets and their observation by sky surveys. It provides Target classes to generate realistic transient populations (such as supernovae), Survey objects to represent pointing patterns and observing conditions, and DataSet objects that combine these to produce simulated light curves and associated metadata. The code uses sncosmo (ascl:1611.017) for bandpass and lightcurve generation. skysurvey supports multi-band observations, survey statistics, and analytical and visualization tools for assessing transient detectability and survey performance.

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 <a href="http://www.ascl.net/1110.012">Starlink</a> (ascl:1110.012).

Sledgehamr (ScaLar fiEld Dynamics Getting solvEd witH Adaptive Mesh Refinement) simulates the dynamics of coupled scalar fields on a 3-dimensional mesh. Adaptive mesh refinement (AMR) can boost performance if spatially localized regions of the scalar field require high resolution. sledgehamr is compatible with both GPU and CPU clusters, and, because it is AMReX-based (ascl:2409.012), offers a flexible and customizable framework. This framework enables various applications, such as the generation of gravitational wave spectra.

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 <a href="https://www.slicer.org/">3D Slicer</a>, 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.

slideParam provides an interactive visualisation tool to display a parameter with respect to 2D positions. The interactive tool uses one projection in the 2D space (for instance right ascension and declination) to study some parameters related to those positions. The tool allows the interactive visualisation of the data for different values for the selected parameter and their ranges.

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 (Spectral energy distributions Markov chain Analysis with Radiative Transfer models) implements a Bayesian Markov chain Monte Carlo (MCMC) method to fit the ultraviolet to millimeter spectral energy distributions (SEDs) of galaxies exclusively with radiative transfer models. The models constitute four types of pre-computed libraries, which describe the starburst, active galactic nucleus (AGN) torus, host galaxy and polar dust components.

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 (Spectral Modeling Analysis and RV Tool) forward models spectral data. The method works best in those spectral orders with both strong telluric absorption features for accurate wavelength calibration and sufficient structure in the stellar spectrum to distinguish it from the telluric absorption. The code uses Markov Chain Monte Carlo (MCMC) methods to determine stellar parameters such as effective temperature, surface gravity, and rotational velocity, and calibration factors, including continuum and wavelength corrections, instrumental line-spread function (LSF), and strength of telluric absorption. SMART has been used with Keck/NIRSPEC, SDSS/APOGEE, Gemini/IGRINS high-resolution near-infrared spectrometers, among others, and with medium-resolution spectrometers, including Keck/OSIRIS and Keck/NIRES.

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 <i>X</i> n grid in O(<i>n</i>² log <i>n</i>) and efficiently derives the necessary conditional covariance matrices.

The Python code smhr (Spectroscopy Made Harder) wraps the MOOG spectral synthesis code (ascl:1202.009) to analyze high-resolution stellar spectra. It offers numerous analysis tools, including normalization of apertures, inverse variance-weighted stitching of overlapping apertures and/or sequential exposures. The code also provides Doppler measurement and correction, automatic measurement of EWs, and multiple methods for inferring stellar parameters; further, it measures elemental abundances from EWs or spectral synthesis and performs a rigorous uncertainty analysis. smhr can be run automatically (in batch mode) or interactively through a graphical user interface. Analyses can be saved to a single file for, for example, distribution to other spectroscopists or release with a publication.

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: <ul><li>orbit integration in various 2d and 3d potentials (including N-body and basis-set representations of an arbitrary potential);</li><li>methods for analysis of orbital class, fundamental frequencies, regular or chaotic nature of an orbit, computation of Lyapunov exponents;</li><li>Poincaré sections (in 2d) and frequency maps (in 3d) for analyzing orbital structure of potential;</li><li>construction of self-consistent Schwarzschild models; and</li><li>convenient visualization and integrated GUI environment, and a console scriptable version.</li></ul>SMILE is portable to different platforms including MS Windows, Linux and Mac.

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).

SMINT (Structure Model INTerpolator) obtains posterior distributions on the H/He or H2O mass fraction of a planet; its interface is user-friendly. The parameters of the planet of interest are input with specifications on the priors that should be used. SMINT returns publication-ready plots presenting the joint parameters constraints obtained from interpolating the interior models grid of interest as well as confidence intervals for each parameter.

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 <a href="http://www.ascl.net/1110.012">Starlink</a> (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 <a href="http://www.ascl.net/1310.001">ORAC-DR</a> (ascl:1310.001) data reduction pipeline for JCMT.

sMV (serial MultiView) scripts provide a semi-automatic and easy-to-use workflow for serial MultiView phase plane estimation. The phase plane is iteratively rotated based on the time series of calibrator residual phases; because time-domain information is included in the iterations, phase ambiguities are accurately and automatically identified. sMV enables efficient, high-accuracy differential astrometry and artifact-reduced imaging for astrophysical studies.

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.

SNITCH (bayeSian iNference given emIssion and absorpTion features of quenChing Histories) performs Bayesian inference of star formation histories using measured emission and absorption spectral features. The code ingests equivalent widths and spectral indices (<i>e.g.</i>, EW[Hα], Dₙ4000, Hβ, Hδₐ, Mg Fe′) and, via a pre-computed look-up table generated with FSPS models, returns posterior estimates of parameters such as metallicity, quenching time and quenching rate. It uses emcee (ascl:1303.002) to explore parameter space, produces diagnostic plots of MCMC walkers and corner plots, and is configurable to suit custom spectral parameter sets and lookup-table ranges. Designed for application to integrated‐light or IFU galaxy spectra, SNITCH enables flexible adaptation for a variety of star‐formation-history studies.

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' <a href="https://github.com/jpierel14/SNSED_Repository">SN SED Repository</a>) 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.

SOAP (Spherical Overdensity and Aperture Processor) computes halo and galaxy properties from SWIFT (ascl:1805.020) simulations after being post-processed with a subhalo finder. The package takes a subhalo catalog as input and calculates a wide array of properties for each object. It offers parallel processing capabilities for efficient handling of large datasets, and allows for consistent property calculation across multiple halo finders. SOAP supports various halo definitions, including spherical overdensities and fixed physical apertures, providing flexibility for diverse observational comparisons. The package is compatible with both dark matter-only and full hydrodynamic simulations, producing HDF5 catalogues that are integrated with the swiftsimio package for seamless unit handling.

socca (Source Characterization using a Composable Analysis) models astronomical image data using forward modeling and Bayesian inference. The package is designed around modular, composable building blocks that allow users to flexibly define complex source models with hierarchical and physically motivated priors, instrument responses, and noise models within a unified framework. socca leverages JAX to enable automatic differentiation, just-in-time compilation, and efficient vectorized computations, making it well suited for computationally intensive inference tasks. Posterior exploration is supported through state-of-the-art sampling algorithms, enabling scalable parameter estimation.

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.