νHawkHunter explores the prospects of detecting neutrinos produced by the evaporation of primordial black holes in ground-based experiments. It makes use of neutrino fluxes from Hawking radiation computed with BlackHawk (ascl:2012.020). νHawkHunter is also be used for Diffuse Supernova Neutrino Background or similar studies by replacing the signal fluxes by the proper ones.

β-SGP deconvolves an astronomical image with a known Point Spread Function, providing a means for restoration of telescopic images due to issues ranging from atmospheric turbulence to instrumental aberrations. The code supports improved astrometry, deblending of overlapping sources, faint source detection, and identification of point sources near bright extended objects, and other tasks. β-SGP generalizes the Scaled Gradient Projection (SGP) image deconvolution algorithm using β-divergence as a loss function to restore distorted stellar shapes.

Zwindstroom computes background quantities and scale-dependent growth factors for cosmological models with free-streaming species, such as massive neutrinos. Following the earlier REPS code (ascl:1612.022), the code uses a Newtonian fluid approximation with external neutrino sound speed to close the Boltzmann hierarchy. Zwindstroom supports multi-fluid models with distinct transfer functions and sound speeds. A flexible python interface facilitates interaction with CLASS (ascl:1106.020) through classy. There is also a Zwindstroom plugin for the cosmological initial conditions generator monofonIC (ascl:2008.024) that allows for higher-order LPT ICs for massive neutrino simulations in a single step.

ZWAD (ZTF anomaly detection pipeline) examines data and performs tailored feature extraction. The code then uses machine learning methods to searches for outliers, and identifies anomalies to be examined for validation by experts. Used with the SNAD ZTF data releases object viewer (ascl:2106.034), the infrastructure helps experts to form global views of specific scientifically interesting candidates.

The SNAD ZTF DR4 object viewer enables quick expert investigation of objects within the public Zwicky Transient Facility (ZTF) data releases. The viewer allows visualization of raw and folded light curves and metadata, as well as cross-match information with the General Catalog of Variable Stars, the International Variable Stars Index, the ATLAS Catalog of Variable Stars, the ZTF Catalog of Periodic Variable Stars, the Transient Name Server, the Open Astronomy Catalogs, the OGLE III Catalog of Variable Stars, the Simbad Astronomical Data Base, Gaia DR2 distances (Bailer-Jones+, 2018), and Vizier. The viewer is also available for ZTF DR2 and ZTF DR3.

Photometric redshifts are estimated on the basis of template scenarios with the help of the code ZPEG, an extension of the galaxy evolution model PEGASE.2 and available on the PEGASE web site. The spectral energy distribution (SED) templates are computed for nine spectral types including starburst, irregular, spiral and elliptical. Dust, extinction and metal effects are coherently taken into account, depending on evolution scenarios. The sensitivity of results to adding near-infrared colors and IGM absorption is analyzed. A comparison with results of other models without evolution measures the evolution factor which systematically increases the estimated photometric redshift values by $Delta z$ > 0.2 for z > 1.5. Moreover we systematically check that the evolution scenarios match observational standard templates of nearby galaxies, implying an age constraint of the stellar population at z=0 for each type. The respect of this constraint makes it possible to significantly improve the accuracy of photometric redshifts by decreasing the well-known degeneracy problem. The method is applied to the HDF-N sample. From fits on SED templates by a $chi^2$-minimization procedure, not only is the photometric redshift derived but also the corresponding spectral type and the formation redshift $z_for$ when stars first formed. Early epochs of galaxy formation z > 5 are found from this new method and results are compared to faint galaxy count interpretations.

Zoobot classifies galaxy morphology with Bayesian CNN. Deep learning models were trained on volunteer classifications; these models were able to both learn from uncertain volunteer responses and predict full posteriors (rather than point estimates) for what volunteers would have said. The code reproduces and improves Galaxy Zoo DECaLS automated classifications, and can be finetuned for new tasks.

ZOGY performs optimal image subtraction; the code is designed specifically for the MeerLICHT and BlackGEM pipelines, but should also be useful to apply to images of other telescopes. The module accepts a new and a reference FITS image, runs SExtractor (ascl:1010.064) on them, and finds their WCS solution using Astrometry.net (ascl:1208.001). ZOGY then uses PSFex (ascl:1301.001) to infer the position-dependent PSFs of the images and SWarp (ascl:1010.068) to map the reference image to the new image and performs optimal image subtraction. This produces the subtracted image, the significance image, the corrected significance image, and the PSF photometry image and associated error image. The inferred PSFs are also used to extract optimal photometry of all sources detected by SExtractor.

ZodiPy simulates the zodiacal emission in intensity that an arbitrary solar system observer is predicted to see given an interplanetary dust model, either in the form of timestreams or full-sky HEALPix maps. Written in Python, the code makes zodiacal emission simulations more accessible by providing a simple interface to existing models.

ZODIPIC synthesizes images of exozodiacal clouds. As a default, ZODIPIC creates an image of the solar zodiacal cloud as seen from 10 pc, but it contains many parameters that are tweakable from the command line, making it a handy general-purpose model for optically-thin debris disks that yields both accurate images and photometric information simultaneously. Written in IDL, ZODIPIC includes dust with real optical constants, user-specified dust maps and can compute images as seen through a linear polarizer.

ZInCo manipulates existing initial conditions (ICs) compatible with GADGET-2/3 (ascl:0003.001) ICs, allowing different flavors of zoom-in simulations rather then producing new ICs from scratch. The code can manipulate initial conditions with multiple types of particles, unlike the vast majority of zoom-in ICs codes available, preserving their properties and random field. This allows ZInCo to take advantage of other codes that produce ICs featuring a broad range of different cosmologies; it can be used also on existing ICs even in the unlikely case nothing is known about their properties. The code is written in C++ and parallelized using MPI.

Zeus21 (Zippy Early-Universe Solver for 21-cm) captures the nonlocal and nonlinear physics of cosmic dawn to create an effective model for the 21-cm power spectrum and global signal. The code takes advantage of the approximate log-normality of the star-formation rate density (SFRD) during cosmic dawn to compute the 21-cm power spectrum analytically. It agrees with more expensive semi-numerical simulations to roughly 10% precision, but has comparably negligible computational cost (~ s) and memory requirements. Zeus21 pairs well with data from HERA, but can be used for any 21-cm inference or prediction. Its capabilities include finding the 21-cm power spectrum (at a broad range of k and z), the global signal, IGM temperatures (Tk, Ts, Tcolor), neutral fraction xHI, Lyman-alpha fluxes, and the evolution of the SFRD; all across cosmic dawn z=5-35. It can also predict UVLFs for HST and JWST. Zeus21 can use three different astrophysical models, one of which emulates 21cmFAST (ascl:1102.023), and can vary the cosmology through CLASS (ascl:1106.020).

Zeus is a pure-Python implementation of the Ensemble Slice Sampling method. Ensemble Slice Sampling improves upon Slice Sampling by bypassing some of that method's difficulties; it also exploits an ensemble of parallel walkers, thus making it immune to linear correlations. Zeus offers fast and robust Bayesian inference and efficient Markov Chain Monte Carlo without hand-tuning. The code provides excellent performance in terms of autocorrelation time and convergence rate, can scale to multiple CPUs without any extra effort, and includes convergence diagnostics.

ZEUS-MP is a multiphysics, massively parallel, message-passing implementation of the ZEUS code. ZEUS-MP offers an MHD algorithm that is better suited for multidimensional flows than the ZEUS-2D module by virtue of modifications to the method of characteristics scheme first suggested by Hawley & Stone. This MHD module is shown to compare quite favorably to the TVD scheme described by Ryu et al. ZEUS-MP is the first publicly available ZEUS code to allow the advection of multiple chemical (or nuclear) species. Radiation hydrodynamic simulations are enabled via an implicit flux-limited radiation diffusion (FLD) module. The hydrodynamic, MHD, and FLD modules can be used, singly or in concert, in one, two, or three space dimensions. In addition, so-called 1.5D and 2.5D grids, in which the "half-D'' denotes a symmetry axis along which a constant but nonzero value of velocity or magnetic field is evolved, are supported. Self-gravity can be included either through the assumption of a GM/r potential or through a solution of Poisson's equation using one of three linear solver packages (conjugate gradient, multigrid, and FFT) provided for that purpose. Point-mass potentials are also supported.

Because ZEUS-MP is designed for large simulations on parallel computing platforms, considerable attention is paid to the parallel performance characteristics of each module in the code. Strong-scaling tests involving pure hydrodynamics (with and without self-gravity), MHD, and RHD are performed in which large problems (2563 zones) are distributed among as many as 1024 processors of an IBM SP3. Parallel efficiency is a strong function of the amount of communication required between processors in a given algorithm, but all modules are shown to scale well on up to 1024 processors for the chosen fixed problem size.

ZEUS-2D is a hydrodynamics code based on ZEUS which adds a covariant differencing formalism and algorithms for compressible hydrodynamics, MHD, and radiation hydrodynamics (using flux-limited diffusion) in Cartesian, cylindrical, or spherical polar coordinates.

The ZENO software package integrates N-body and SPH simulation codes with a large array of programs to generate initial conditions and analyze numerical simulations. Written in C, the ZENO system is portable between Mac, Linux, and Unix platforms. It is in active use at the Institute for Astronomy (IfA), at NRAO, and possibly elsewhere.

Zeno programs can perform a wide range of simulation and analysis tasks. While many of these programs were first created for specific projects, they embody algorithms of general applicability and embrace a modular design strategy, so existing code is easily applied to new tasks. Major elements of the system include structured data file utilities facilitate basic operations on binary data, including import/export of ZENO data to other systems; snapshot generation routines to create particle distributions with various properties; systems with user-specified density profiles can be realized in collisionless or gaseous form; multiple spherical and disk components may be set up in mutual equilibrium; and snapshot manipulation routines permit the user to sift, sort, and combine particle arrays, translate and rotate particle configurations, and assign new values to data fields associated with each particle.

Simulation codes include both pure N-body and combined N-body/SPH programs. Pure N-body codes are available in both uniprocessor and parallel versions. SPH codes offer a wide range of options for gas physics, including isothermal, adiabatic, and radiating models. Snapshot analysis programs calculate temporal averages, evaluate particle statistics, measure shapes and density profiles, compute kinematic properties, and identify and track objects in particle distributions. Visualization programs generate interactive displays and produce still images and videos of particle distributions; the user may specify arbitrary color schemes and viewing transformations.

Zeltron is an explicit 3D relativistic electromagnetic Particle-In-Cell code suited for modeling particle acceleration in astrophysical plasmas. The code is efficiently parallelized with the Message Passing Interface, and can be run on a laptop computer or on multiple cores on current supercomputers. Zeltron takes into account the effect of the radiation reaction force on the motion of the particles; it assigns variable weights to the macro-particles to model particle density gradients, and does not strictly conserve the total energy. The code uses linear interpolation to deposit the charges and currents generated by each particle at the nodes of the computational grid, and computes the charge and current densities for Maxwell's equations. Zeltron contains a large set of analysis tools, including plasma density, particle spectrum, optically thin synchrotron and inverse Compton spectra, angular distributions, and stress-energy tensor.

ZeldovichRecon computes the halo correlation function using the Zeldovich approximation. It includes 3 variants: 1.) zelrecon.cpp, which computes the various contributions to the correlation function; 2.) zelrecon_ctypes.cpp, which is designed to be called from Python using the ctypes library; and 3.) a version which implements the "ZEFT" formalism of "A Lagrangian effective field theory" [arxiv:1506.05264] including the alpha term described in that paper.

zeldovich-PLT generates Zel'dovich approximation (ZA) initial conditions (i.e. first-order Lagrangian perturbation theory) for cosmological N-body simulations, optionally applying particle linear theory (PLT) corrections.

The Zelda command-line tool extracts correlation functions in velocity space from a galaxy catalog. Zelda is modular, extendable, and can be generalized to produce power spectra and to work in position space. Written in C, it was heavily inspired by the cosmological Boltzmann code CLASS (ascl:1106.020). Zelda is a parallel code using the OpenMP standard.

The current version of the Zurich Extragalactic Bayesian Redshift Analyzer (ZEBRA) combines and extends several of the classical approaches to produce accurate photometric redshifts down to faint magnitudes. In particular, ZEBRA uses the template-fitting approach to produce Maximum Likelihood and Bayesian redshift estimates based on: (1.) An automatic iterative technique to correct the original set of galaxy templates to best represent the SEDs of real galaxies at different redshifts; (2.) A training set of spectroscopic redshifts for a small fraction of the photometric sample; and (3.) An iterative technique for Bayesian redshift estimates, which extracts the full two-dimensional redshift and template probability function for each galaxy.

The cross-correlation function (CCF) is commonly employed in the study of AGN, where it is used to probe the structure of the broad line region by line reverberation, to study the continuum emission mechanism by correlating multi-waveband light curves and to seek correlations between the variability and other AGN properties. The z -transformed discrete correlation function (ZDCF) is a method for estimating the CCF of sparse, unevenly sampled light curves. Unlike the commonly used interpolation method, it does not assume that the light curves are smooth and it does provide errors on its estimates.

zCluster measures galaxy cluster photometric redshifts using data from broadband photometry in large public surveys, given a priori knowledge of the cluster position. The code retrieves and uses redshift probability distributions in order to create a projected two-dimensional density map of a targeted galaxy cluster, which is later convolved with a Gaussian kernel to smooth the map. zCluster also produces photometric redshift estimates and galaxy density maps for any point in the sky using the included zField tool.

ZChecker finds, measures, and visualizes known comets in the Zwicky Transient Facility time-domain survey. Images of targets are identified using on-line ephemeris generation and survey metadata. The photometry of the targets are measured and the images are processed with temporal filtering to highlight morphological variations in time.

ZBARYCORR determines the barycentric redshift (z_B) for a given star. It calculates the positions and velocities of solar system objects, applies the rotation, precession, nutation, and polar motion of the Earth, applies the stellar motion using the Markwardt library (ascl:1807.016), Shapiro delay, and light-travel term, and finally calculates the quantity z_B—the barycentric correction independent of the measured redshift. A Python wrapper, BARYCORR (ascl:1807.018), is available.

ZASPE (Zonal Atmospheric Stellar Parameters Estimator) computes the atmospheric stellar parameters (Teff, log(g), [Fe/H] and vsin(i)) from echelle spectra via least squares minimization with a pre-computed library of synthetic spectra. The minimization is performed only in the most sensitive spectral zones to changes in the atmospheric parameters. The uncertainities and covariances computed by ZASPE assume that the principal source of error is the systematic missmatch between the observed spectrum and the sythetic one that produces the best fit. ZASPE requires a grid of synthetic spectra and can use any pre-computed library minor modifications.

ZAP (Zurich Atmosphere Purge) provides sky subtraction for integral field spectroscopy; its approach is based on principal component analysis (PCA) developed for the Multi Unit Spectrographic Explorer (MUSE) integral field spectrograph. ZAP employs filtering and data segmentation to enhance the inherent capabilities of PCA for sky subtraction. ZAP reduces sky emission residuals while robustly preserving the flux and line shapes of astronomical sources; this method works in a variety of observational situations from sparse fields with a low density of sources to filled fields in which the target source fills the field of view. With the inclusion of both of these situations the method is generally applicable to many different science cases and should also be useful for other instrumentation.

ytree reads and works with merger tree data from multiple formats. An extension of yt (ascl:1011.022), which can analyze snapshots from cosmological simulations, ytree can be thought of as the yt of merger trees. ytree's online documentation lists supported formats; support for additional formats can be added, as in principle, any type of tree-like data where an object has one or more ancestors and a single descendant can be supported.

yt is an open source, community-developed volumetric analysis and visualization toolkit. Originally designed for handling Enzo's (ascl:1010.072) structure adaptive mesh refinement (AMR) data, yt has been extended to work with numerous simulation methods and simulation codes including Orion, RAMSES (ascl:1011.007), and FLASH (ascl:1010.082). Analysis and visualization with yt are oriented around physically relevant quantities rather than quantities native to data representation on-disk or in-memory. yt can be used for projections, multivariate volume rendering, multi-dimensional histograms, halo finding, light cone generation and topologically-connected isocontour identification.

yt benefits from the contributions of a broad range of community members, and a full list of credits for the code can be found on the yt website or in the source repository.

ysoisochrone is a Python3 package that handles the isochrones for young stellar objects (YSOs), and utilize isochrones to derive the stellar mass and ages. Our primary method is a Bayesian inference approach, and the Python code builds on the IDL version developed in Pascucci et al. (2016). The code estimates the stellar masses, ages, and associated uncertainties by comparing their stellar effective temperature, bolometric luminosity, and their uncertainties with different stellar evolutionary models, including those specifically developed for YSOs. User-developed evolutionary tracks can also be utilized when provided in the specific format described in the code documentation.

Youpi is a portable, easy to use web application providing high level functionalities to perform data reduction on scientific FITS images. Built on top of various open source reduction tools released to the community by TERAPIX (http://terapix.iap.fr), Youpi can help organize data, manage processing jobs on a computer cluster in real time (using Condor) and facilitate teamwork by allowing fine-grain sharing of results and data. Youpi is modular and comes with plugins which perform, from within a browser, various processing tasks such as evaluating the quality of incoming images (using the QualityFITS software package), computing astrometric and photometric solutions (using SCAMP), resampling and co-adding FITS images (using SWarp) and extracting sources and building source catalogues from astronomical images (using SExtractor). Youpi is useful for small to medium-sized data reduction projects; it is free and is published under the GNU General Public License.

YONDER uses singular value decomposition to perform low-rank data denoising and reconstruction. It takes a tabular data matrix and an error matrix as input and returns a denoised version of the original dataset as output. The approach enables a more accurate data analysis in the presence of uncertainties. Consequently, this package can be used as a simple toolbox to perform astronomical data cleaning.

YODA, implemented in C++, performs object detection, photometry and star-galaxy classification on astronomical images. Developed specifically to cope with the multi-band imaging data common in modern extragalactic imaging surveys, it is modular and therefore easily adaptable to specific needs. YODA works under conditions of inhomogeneous background noise across the detection frame, and performs accurate aperture photometry in image sets not sharing a common coordinate system or pixel scale as is often the case in present-day extragalactic survey work.

YNOGKM (Yun-Nan observatories geodesic in a Kerr-Newman spacetime for massive particles) performs fast calculation of time-like geodesics in the Kerr-Newman (K-N) spacetime; it is a direct extension of YNOGK (Yun-Nan observatories geodesic Kerr) calculating null geodesics in a Kerr spacetime. The four Boyer-Lindquis coordinates and proper time are expressed as functions of a parameter p semi-analytically by using the Weierstrass' and Jacobi's elliptic functions and integrals. The elliptic integrals are computed by Carlson's elliptic integral method, which guarantees the fast speed of the code. The source Fortran file ynogkm.f90 contains three modules: constants, rootfind, ellfunction, and blcoordinates.

YNOGK, written in Fortran, calculates the null geodesics in the Kerr spacetime. It uses Weierstrass' and Jacobi's elliptic functions to express all coordinates and affine parameters as analytical and numerical functions of a parameter $p$, which is an integral value along the geodesic. The information about the turning points do not need to be specified in advance by the user, allowing applications such as imaging, the calculation of line profiles or the observer-emitter problem to become root finding problems. Elliptic integrations are computed by Carlson's elliptic integral method, which allows fast computation.

YMW16 models the distribution of free electrons in the Galaxy, the Magellanic Clouds and the inter-galactic medium and can be used to estimate distances for real or simulated pulsars and fast radio bursts (FRBs) based on their position and dispersion measure. The Galactic model is based on 189 pulsars that have independently determined distances as well as dispersion measures, whereas simpler models are used for the electron density in the MC and the IGM.

Yaxx is a Perl script that facilitates batch data processing using Perl open source software and commonly available software such as CIAO/Sherpa, S-lang, SAS, and FTOOLS. For Chandra and XMM analysis it includes automated spectral extraction, fitting, and report generation. Yaxx can be run without climbing an extensive learning curve; even so, yaxx is highly configurable and can be customized to support complex analysis. yaxx uses template files and takes full advantage of the unique Sherpa / S-lang environment to make much of the processing user configurable. Although originally developed with an emphasis on X-ray data analysis, yaxx evolved to be a general-purpose pipeline scripting package.

The xwavecal library automatically wavelength calibrates echelle spectrographs for high precision radial velocity work. The routines are designed to operate on data with extracted 1D spectra. The library provides a convienience function which returns a list of wavelengths from just a list of spectral feature coordinates (pixel and order) and a reference line list. The returned wavelengths are the wavelengths of the measured spectral features under the best fit wavelength model. xwavecal also provides line identification and spectral reduction utilities. The library is modular; each step of the wavelength calibration is a stage which can be disabled by removing the associated line in the config.ini file. Wavelength calibrating data which already have spectra means only using the wavelength calibration stages. Using the full experimental pipeline means enabling the other data reduction stages, such as overscan subtraction.

XSTAR is a command-driven, interactive, computer program for calculating the physical conditions and emission spectra of photoionized gases. It may be applied in a wide variety of astrophysical contexts. Stripped to essentials, its job may be described simply: A spherical gas shell surrounding a central source of ionizing radiation absorbs some of this radiation and reradiates it in other portions of the spectrum; XSTAR computes the effects on the gas of absorbing this energy, and the spectrum of reradiated light. The user supplies the shape and strength of the incident continuum, the elemental abundances in the gas, its density or pressure, and its thickness; the code can be directed to return any of a large number of derived quantities, including (but not limited to) the ionization balance and temperature, opacity tables, and emitted line and continuum fluxes.

It has been over a decade since the first paper was published containing results determined using the general X-ray spectral-fitting program XSPEC. Since then XSPEC has become the most widely used program for this purpose, being the de facto standard for the ROSAT and the de jure standard for the ASCA and XTE satellites. Probably the most important features of XSPEC are the large number of theoretical models available and the facilities for adding new models.

XSPEC_EMCEE is an XSPEC-friendly interface for emcee (ascl:1303.002). It carries out MCMC analyses of X-ray spectra in the X-ray spectral fitting program XSPEC (ascl:9910.005). It can run multiple xspec processes simultaneously, speeding up the analysis, and can switch to parameterizing norm
parameters in log space.

xSonify maps scientific data to acoustic sequences. Listening to data can help discover patterns in huge amounts of data. Written in Java, xSonify allows visually impaired people to examine numerical data for patterns. The data can be imported from local files or from remote databases via the Internet. Single results of measurements from spacecraft instruments can be selected by their corresponding variables in a specific time frame. The results are transformed into MIDI sequences which can be played with a selection of different instruments from a soundbank. Another software module enables xSonify to convert the sonified data into other sound formats to make it easier to archive and exchange the Sonification results with other scientists.

Xsmurf is a software package written in C/Tcl/Tk that implements the continuous wavelet transform modulus maxima method, an image processing tool for measuring fractal and multifractal properties in experimental and simulation data.
Multifractal analysis is described in the following page: http://www.scholarpedia.org/article/Wavelet-based_multifractal_analysis

Xsmurf has been used in multiple applications in astrophysics, e.g. :
- analysis of solar magnetograms for characterizing complexity of evolving regions
- fractal/multifractal nature and anisotropic structure of Galactic atomic hydrogen (H I)
- analysis of simulation data (velocity field, ...) of turbulent flow

XSHPipelineManager provides a framework for reducing spectroscopic observations taken by the X-shooter spectrograph at the Very Large Telescope. This Python code wraps recipes developed by the European Southern Observatory and runs the full X-shooter data reduction pipeline. The code offers full flexibility in terms of what data reduction recipes to include and which calibration files to use. During the data reduction chain restart-files are saved, making it possible to restart at any step in the chain.

Xpol computes angular power spectra based on cross-correlation between maps and covariance matrices. The code is written in C and is fully MPI parallelized in CPU and memory using spherical transform by s2hat (ascl:1110.013). It has been used to derive CMB and dust power spectra for Archeops and CMB, dust, CIB, SZ, SZ-CIB for Planck, among others.

XPHOT is an IDL implementation of a non-parametric method for estimating the apparent and intrinsic broad-band fluxes and absorbing X-ray column densities of weak X-ray sources. XPHOT is intended for faint sources with greater than ∼5-7 counts but fewer than 100-300 counts where parametric spectral fitting methods will be superior. This method is similar to the long-standing use of color-magnitude diagrams in optical and infrared astronomy, with X-ray median energy replacing color index and X-ray source counts replacing magnitude. Though XPHOT was calibrated for thermal spectra characteristic of stars in young stellar clusters, recalibration should be possible for some other classes of faint X-ray sources such as extragalactic active galactic nuclei.

XPCell simulates convective plasma cells. The program is implemented in two versions, one using GNUPLOT and the second OpenGL. XPCell offers a GUI to introduce the parameter required by the program.

XookSuut models circular and noncircular flows on resolved velocity maps. The code performs nonparametric fits to derive kinematic models without assuming analytical functions on the different velocity components of the models. It recovers the circular and radial motions in galaxies in dynamical equilibrium and can derive the noncircular motions induced by oval distortions, such as that produced by stellar bars. XookSuut explores the full space of parameters on a N-dimensional space to derive their mean values; this combined method efficiently recovers the constant parameters and the different kinematic components.

XNS solves for the axisymmetric equilibrium configuration of neutron stars in general relativity. It can model differentially rotating and magnetic fields that are either purely toroidal, purely poloidal or in the mixed twisted torus configuration. Einsten's equations are solved using the XCFC approximation for the metric in spherical coordinates.

Xmatch is a cross-platform, multi-GPU tool which allows for extremely fast cross-matching between two Astronomic catalogs. It is capable of asyncronously managing multiple GPUs, ideal for workstation and cluster environments.

XID+ is a prior-based source extraction tool which carries out photometry in the Herschel SPIRE (Spectral and Photometric Imaging Receiver) maps at the positions of known sources. It uses a probabilistic Bayesian framework that provides a natural framework in which to include prior information, and uses the Bayesian inference tool Stan to obtain the full posterior probability distribution on flux estimates.

Xgremlin is a hardware and operating system independent version of the data analysis program Gremlin used for Fourier transform spectrometry. Xgremlin runs on PCs and workstations that use the X11 window system, including cygwin in Windows. It is used to Fourier transform interferograms, plot spectra, perform phase corrections, perform intensity and wavenumber calibration, and find and fit spectral lines. It can also be used to construct synthetic spectra, subtract continua, compare several different spectra, and eliminate ringing around lines.

xGDS (Exploration Ground Data Systems) synthesizes real world data (from sensors, robots, ROVs, mobile devices, etc) and human observations into rich, digital maps and displays for analysis, decision making, and collaboration. xGDS processes and maps data (including video) in real-time during operations and uses it to support live role-based geolocated note taking. Notes can be used to search for and display important data. The software enables real-time analysis of data, permitting one to make inferences and plan new data collection operations while still in the field.

XGA (X-ray: Generate and Analyse) analyzes X-ray sources observed by the XMM-Newton Space telescope. It is based around declaring different types of source and sample objects which correspond to real X-ray sources, finding all available data, and then insulating the user from the tedious generation and basic analysis of X-ray data products. XGA generates photometric products and spectra for individual sources, or whole samples, with just a few lines of code. Though not a pipeline, pipelines for complex analysis can be built on top of it. XGA provides an easy to use (and parallelized) Python interface with XMM's Science Analysis System (ascl:1404.004), as well as with XSPEC (ascl:9910.005). All XMM products and fit results are read into an XGA source storage structure, thus avoiding the need to leave a Python environment at any point during the analysis. This module also supports more complex analyses for specific object types such as the easy generation of scaling relations, the measurement of gas masses for galaxy clusters, and the PSF correction of images.

XFGL visualizes gravitational lenses. It has an XFORM GUI and is completely interactive with the mouse. It uses OpenGL for the simulations.

XEphem is a scientific-grade interactive astronomical ephemeris package for UNIX-like systems. Written in C, X11 and Motif, it is easily ported to systems. XEphem computes heliocentric, geocentric and topocentric information for all objects and has built-in support for all planets, the moons of Mars, Jupiter, Saturn, Uranus and Earth, central meridian longitude of Mars and Jupiter, Saturn's rings, and Jupiter's Great Red Spot. It allows user-defined objects including stars, deepsky objects, asteroids, comets and Earth satellites, provides special efficient handling of large catalogs including Tycho, Hipparcos, GSC, displays data in configurable tabular formats in conjunction with several interactive graphical views, and displays a night-at-a-glance 24 hour graphic showing when any selected objects are up. It also displays 3-D stereo Solar System views that are particularly well suited for visualizing comet trajectories, quickly finds all close pairs of objects in the sky, and sorts and prints all catalogs with very flexible criteria for creating custom observing lists.

The CL-based package XDSPRES is a complete reducing facility for cross-dispersed spectra taken with the Ohio State Infrared Imager/Spectrometer, as installed at the SOAR telescope. This instrument provides spectra in the range between 1.2um and 2.35um in a single exposure, with resolving power of R ~ 1200. XDSPRES consists of two tasks, namely xdflat and doosiris. The former is a completely automated code for preparing normalized flat field images from raw flat field exposures. Doosiris provides a complete reduction pipeline that requires a minimum of user interaction. The user guide explains the general steps towards a fully reduced spectrum.

XDQSO, written in IDL, calculates photometric quasar probabilities to mimick SDSS-III’s BOSS quasar target selection or photometric redshifts for quasars, whether in three redshift ranges (z < 2.2; 2.2 leq z leq 3.5; z > 3.5) or arbitrary redshift ranges.

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

XDF-GAN generates mock galaxy surveys with a Spatial Generative Adversarial Network (SGAN)-like architecture. Mock galaxy surveys are generated from data that is preprocessed as little as possible (preprocessing is only a 99.99th percentile clipping). The outputs can also be tessellated together to create a very large survey, limited in size only by the RAM of the generation machine.

XCLASS (eXtended CASA Line Analysis Software Suite) extends CASA (ascl:1107.013) with new functions for modeling interferometric and single dish data. It provides a tool for calculating synthetic spectra by solving the radiative transfer equation for an isothermal object in one dimension, taking into account the finite source size and dust attenuation. It also includes an interface for MAGIX (ascl:1303.009) to find the parameter set that most closely reproduces the data.

XAssist provides automation of X-ray astrophysics, specifically data reprocessing, source detection, and preliminary spatial, temporal and spectral analysis for each source with sufficient counts, with an emphasis on galaxies. It has been used for data from Chandra, ROSAT, XMM-Newton, and other various projects.

X-PSI simulates rotationally-modified (pulsed) surface X-ray emission from neutron stars, taking into account relativistic effects on the emitted radiation. This can then be used to perform Bayesian statistical inference on real or simulated astronomical data sets. Model parameters of interest may include neutron star mass and radius (useful to constrain the properties of ultradense nuclear matter) or the system geometry and properties of the hot emitting surface-regions. To achieve this, X-PSI couples code for likelihood functionality (simulation) with existing open-source software for posterior sampling (inference).

WzBinned extracts binned and uncorrelated estimates of dark energy equation of state w(z) using Type Ia supernovae Hubble diagram and other cosmological probes and priors. It can handle an arbitrary number of input distance modulus data (entered as an input file SNdata.dat) and various existing cosmological information.

wwz provides a python3 implementation of the Foster weighted wavelet z-transform, a wavelet-based method for periodicity analysis of unevenly sampled data.

WVTICs generates glass-like initial conditions for Smoothed Particle Hydrodynamics. Relaxation of the particle distribution is done using an algorithm based on Weighted Voronoi Tesselations; additional particle reshuffling can be enabled to improve over- and undersampled maxima/minima. The WBTICs package includes a full suite of analytical test problems.

WVT Binning is a spatially adaptive 2-dimensional binning algorithm designed to bin sparse X-ray data. It can handle background subtracted, exposure corrected data to produce intensity images, hardness ratio maps, or temperature maps. The algorithm is an extension of Cappellari & Copin's (2003) Voronoi binning code and uses Weighted Voronoi Tesselations (WVT) to produce a very compact binning structure with a constant S/N per bin. The bin size adjusts to the required resolution in single-pixel steps, which minimizes the scatter around the target S/N. The code is very versatile and can in principle be applied to any type of data. The user manual contains instructions on how to apply the WVT binning code to X-ray data and how to extend the algorithm to other problems.

wvrgcal is a command line front end to LibAIR, the atmospheric inference library for phase correction of ALMA data using water vapour radiometers, and is the user-facing application for calculating atmospheric phase correction from WVR data. wvrgcal outputs a CASA gain calibration table which can then be applied to the observed data in the usual way.

Note: wvrgcal has been incorporated into the NRAO CASA suite.

wsynphot provides a broad set of filters, including observation facility, instrument, and wavelength range, and functions for imaging stars to produce a filter curve showing the transmission of light for each wavelength value. It can create a filter curve object, plot the curve, and allows the user to do calculations on the filter curve object.

wssa_utils contains utilities for accessing the full-sky, high-resolution maps of the WSSA 12 micron data release. Implementations in both Python and IDL are included. The code allows users to sample values at (longitude, latitude) coordinates of interest with ease, transparently mapping coordinates to WSSA tiles and performing interpolation. The wssa_utils software also serves to define a unique WSSA 12 micron flux at every location on the sky.

Pairwise forces between particles in cosmological N-body simulations are generally softened to avoid hard collisions. Physically, this softening corresponds to treating the particles as diffuse clouds rather than point masses. For particles of unequal mass (and hence unequal softening length), computing the softened force involves a nontrivial double integral over the volumes of the two particles. We show that Plummer force softening is consistent with this interpretation of softening while spline softening is not. We provide closed-form expressions and numerical implementation for pairwise gravitational force laws for pairs of particles of general softening scales $epsilon_1$ and $epsilon_2$ assuming the commonly used cloud profiles: NGP, CIC, TSC, and PQS. Similarly, we generalize Plummer force law into pairs of particles of general softenings. We relate our expressions to the gaussian, Plummer and spline force softenings known from literature. Our expressions allow possible inclusions of pointlike particles such as stars or supermassive black holes.

WSClean (w-stacking clean) is a fast generic widefield imager. It uses the w-stacking algorithm and can make use of the w-snapshot algorithm. It supports full-sky imaging and proper beam correction for homogeneous dipole arrays such as the MWA. WSClean allows Hogbom and Cotton-Schwab cleaning, and can clean polarizations joinedly. All operations are performed on the CPU; it is not specialized for GPUs.

Wqed (pronounced "Wicked") is a set of tools developed by the Delaware Asteroseismic Research Center (DARC) to simplify the process of reducing time-series CCD data on variable stars. It does not provide tools to measure the brightness of stars in individual frames, focusing instead on what comes next:

- selecting and removing data lost to cloud,
- removing the effects of light cloud and seeing variations,
- keeping track of what star a given data set refers to, and when that data was taken, and
- performing barycentric corrections to data.

wpca, written in Python, offers several implementations of Weighted Principal Component Analysis and uses an interface similar to scikit-learn's sklearn.decomposition.PCA. Implementations include a direct decomposition of a weighted covariance matrix to compute principal vectors, and then a weighted least squares optimization to compute principal components, and an iterative expectation-maximization approach to solve simultaneously for the principal vectors and principal components of weighted data. It also includes a standard non-weighted PCA implemented using the singular value decomposition, primarily to be useful for testing.

Wōtan provides free and open source algorithms to remove trends from time-series data automatically as an aid to search efficiently for transits in stellar light curves from surveys. The toolkit helps determine empirically the best tool for a given job, serving as a one-stop solution for various smoothing tasks.

World Observatory visualizes S/N-versus-cost tradeoffs for large optical and near-infrared telescopes. Both mid-latitude and Arctic/Antarctic sites can be considered; the intent is a simple simulation to grow intuition for where major capital costs lie relative to key observatory design choices, and against expected scientific performance at various sites. User-defined unit costs for (a possibly "effective") roadway, enclosure, aperture, focal length, and adaptive optics can be scaled up for polar sites, and down for better seeing and lower sky brightness in K-band. Observatory models and results are immediately displayed side-by-side. Either point-source-detection S/N or recovery of bulge-to-total ratios in a simulated galaxy survey are divided by the total project cost, thus providing a universal metric.

WOMBAT (sWift Objects for Mhd BAsed on Tvd) is an astrophysical fluid code that is an implementation of a non-relativistic MHD TVD scheme; an extension for relativistic MHD has been added. The code operates on 1, 2, and 3D Eulerian meshes (cartesian and cylindrical coordinates) with magnetic field divergence restriction controlled by a constrained transport (CT) scheme. The user can tune code performance to a given processor based on chip cache sizes. Proper settings yield significant speed-ups due to efficient cache reuse.

WOLF processes FITS files and generates photometry files, annotated JPGs, opacity maps, background, transient detection and luminance changes detection. This software was used to process data for the Night Sky Live project.

wobble analyzes time-series spectra. It was designed with stabilized extreme precision radial velocity (EPRV) spectrographs in mind, but is highly flexible and extensible to a variety of applications. It takes a data-driven approach to deriving radial velocities and requires no a priori knowledge of the stellar spectrum or telluric features.

WND-CHARM quantitatively analyzes morphologies of galaxy mergers and associate galaxies by their morphology. It computes a large set (up to ~2700) of image features for each image based on the WND-CHARM algorithm. It can then split the images into training and test sets and classify them. The software extracts the image content descriptor from raw images, image transforms, and compound image transforms. The most informative features are then selected, and the feature vector of each image is used for classification and similarity measurement using Fisher discriminant scores and a variation of Weighted Nearest Neighbor analysis. WND-CHARM's results comparable favorably to the performance of task-specific algorithms developed for tested datasets. The simple user interface allows researchers who are not knowledgeable in computer vision methods and have no background in computer programming to apply image analysis to their data.

WM-basic is an easy-to-use interface to a program package which models the atmospheres of Hot Stars (and also SN and GN). The release comprises all programs required to calculate model atmospheres which especially yield ionizing fluxes and synthetic spectra. WM-basic is a native 32-bit application, conforming to the Multiple Documents Interface (MDI) standards for Windows XP/2000/NT/9x. All components of the program package have been compiled with Digital Visual Fortran V6.6(Pro) and Microsoft Visual C++.

WISP (Wenger Interferometry Software Package) is a radio interferometry calibration, reduction, imaging, and analysis package. WISP is a collection of Python code implemented through CASA (ascl:1107.013). Its generic and modular framework is designed to handle any continuum or spectral line radio interferometry data.

WiseView renders image blinks of Wide-field Infrared Survey Explorer (WISE) coadds spanning a multi-year time baseline in a browser. The software allows for easy visual identification of motion and variability for sources far beyond the single-frame detection limit, a key threshold not surmounted by many studies. WiseView transparently gathers small image cutouts drawn from many terabytes of unWISE coadds, facilitating access to this large and unique dataset. Users need only input the coordinates of interest and can interactively tune parameters including the image stretch, colormap and blink rate. WiseView was developed in the context of the Backyard Worlds: Planet 9 citizen science project, and has enabled hundreds of brown dwarf candidate discoveries by citizen scientists and professional astronomers.

WISE2MBH uses infrared cataloged data from the Wide-field Infrared Survey Explorer (WISE) to estimate the mass of supermassive black holes (SMBH). It implements a Monte Carlo approach for error propagation, considering mean photometric errors from WISE magnitudes, errors in fits of scaling relations used and scatter of those relations, if available.

WinNet, a single zone nuclear reaction network, calculates many different nucleosynthesis processes, including r-process, nup-process, and explosive nucleosynthesis, and many more). It reads in a user-defined file with runtime parameters, then chooses the evolution mode, which is dependent on temperature. The temperature, density, and neutrino quantities are updated, after which the reaction network equations are solved numerically. If convergence is not achieved, the step size is halved and the iteration is repeated. Once convergence is reached, the output is generated and the time is evolved; the final output such as the final abundances and mass fractions are written.

WINGSPAN is a program written to analyze spectral data from the Burst and Transient Source Experiment (BATSE) on NASA's Compton Gamma-Ray Observatory. Data files in the FITS (BFITS) format are suitable for input into the program. WINGSPAN can be used to view and manipulate event time histories or count spectra, and also has the capability to perform spectral deconvolution via a standard forward folding model fitting technique (Levenberg-Marquardt algorithm). Although WINGSPAN provides many functions for data manipulation, the program was designed to allow users to easily plug in their own external IDL routines. These external routines have access to all data read from the FITS files, as well as selection intervals created in the main part of WINGSPAN (background intervals and model, etc).

WimPyDD calculates accurate predictions for the expected rates in WIMP direct–detection experiments within the framework of Galilean–invariant non–relativistic effective theory. The object–oriented customizable Python code handles different scenarios including inelastic scattering, WIMP of arbitrary spin, and a generic velocity distribution of WIMP in the Galactic halo.

WIMpy_NREFT (also known as WIMpy) calculates Dark Matter-Nucleus scattering rates in the framework of non-relativistic effective field theory (NREFT). It currently supports operators O1 to O11, as well as millicharged and magnetic dipole Dark Matter. It can be used to generate spectra for Xenon, Argon, Carbon, Germanium, Iodine and Fluorine targets. WIMpy_NREFT also includes functionality to calculate directional recoil spectra, as well as signals from coherent neutrino-nucleus scattering (including fluxes from the Sun, atmosphere and diffuse supernovae).

WignerFamilies generates families of Wigner 3j and 6j symbols by recurrence relation. These exact methods are orders of magnitude more efficient than strategies such as prime factorization for problems which require every non-trivial symbol in a family, and are very useful for large quantum numbers. WignerFamilies is thread-safe and very fast, beating the standard Fortran routine DRC3JJ from SLATEC by a factor of 2-4.

Wigglewave uses a finite difference method to solve the linearized governing equations for a torsion Alfvèn wave propagating in a plasma with negligible plasma beta and in a force-free axisymmetric magnetic field with no azimuthal component embedded in a high density divergent tube structure. Wigglewave is fourth order in time and space using a fourth-order central difference scheme for calculating spatial derivatives and a fourth-order Runge-Kutta (RK4) scheme for updating at each timestep. The solutions calculated are the perturbations to the velocity, v and to the magnetic field, b. All variables are calculated over a uniform grid in radius r and height z.

Whisky is a code to evolve the equations of general relativistic hydrodynamics (GRHD) and magnetohydrodynamics (GRMHD) in 3D Cartesian coordinates on a curved dynamical background. It was originally developed by and for members of the EU Network on Sources of Gravitational Radiation and is based on the Cactus Computational Toolkit. Whisky can also implement adaptive mesh refinement (AMR) if compiled together with Carpet.

Whisky has grown from earlier codes such as GR3D and GRAstro_Hydro, but has been rewritten to take advantage of some of the latest research performed here in the EU. The motivation behind Whisky is to compute gravitational radiation waveforms for systems that involve matter. Examples would include the merger of a binary system containing a neutron star, which are expected to be reasonably common in the universe and expected to produce substantial amounts of radiation. Other possible sources are given in the projects list.

WhereWolf tracks (sub)haloes even if they have been lost by a halo finder in cosmological simulations and supplements halo catalogs such as VELOCIraptor (ascl:1911.020) with these recovered (sub)haloes. The code can improve measurements of the subhalo/halo mass function and present estimates of the distribution of radii at which subhaloes merge.

whereistheplanet predicts the locations of directly imaged companions (mainly exoplanets and brown dwarfs) based on past orbital fits to the data. This tool helps coordinate follow-up observations to characterize their properties, as precise pointing of the instrument is often needed. It uses orbitize! (ascl:1910.009) as a backend. whereistheplanet is available as a Python API, a command line tool, and a web form at whereistheplanet.com.

WFC3UV_GC is an improved geometric-distortion solution for the Hubble Space Telescope UVIS channel of Wide Field Camera 3 for ten broad-band filters. The solution is made up of three parts:

1.) a 3rd-order polynomial to deal with the general optical distortion;
2.) a table of residuals that accounts for both chip-related anomalies and fine-structure introduced by the filter; and,
3.) a linear transformation to put the two chips into a convenient master frame.

WF4Py implements frequency-domain gravitational wave waveform models in pure Python, thus enabling parallelization over multiple events at a time. Waveforms in WF4Py are built as classes; the functions take dictionaries containing the parameters of the events to analyze as input and provide Fourier domain waveform models. All the waveforms are accurately checked with their implementation in LALSuite (ascl:2012.021) and are a core element of GWFAST (ascl:2212.001).

WeirdestGalaxies finds the weirdest galaxies in the Sloan Digital Sky Survey (SDSS) by using a basic outlier detection algorithm. It uses an unsupervised Random Forest (RF) algorithm to assign a similarity measure (or distance) between every pair of galaxy spectra in the SDSS. It then uses the distance matrix to find the galaxies that have the largest distance, on average, from the rest of the galaxies in the sample, and defined them as outliers.

WeightWatcher is a program that combines weight-maps, flag-maps and polygon data in order to produce control maps which can directly be used in astronomical image-processing packages like Drizzle, SWarp or SExtractor.

This code, which requires HEALPix 2.x (ascl:1107.018), allows you to generate power spectrum estimators from WMAP 5-year maps and generate hybrid cross- and auto- power spectrum and covariance from general foreground-cleaned maps. In addition, it allows you to simulate combined maps or combinations of maps for individual detectors and do MPI spherical transforms of arrays of maps, calculate coupling matrices etc. The code includes all of LensPix (ascl:1102.025), the MPI framework used for doing spherical transforms (based on HealPix).

Weighted EMPCA performs principal component analysis (PCA) on noisy datasets with missing values. Estimates of the measurement error are used to weight the input data such that the resulting eigenvectors, when compared to classic PCA, are more sensitive to the true underlying signal variations rather than being pulled by heteroskedastic measurement noise. Missing data are simply limiting cases of weight = 0. The underlying algorithm is a noise weighted expectation maximization (EM) PCA, which has additional benefits of implementation speed and flexibility for smoothing eigenvectors to reduce the noise contribution.

WebbPSF provides a PSF simulation tool in a flexible and easy-to-use software package implemented in Python. Functionality includes support for spectroscopic modes of JWST NIRISS, MIRI, and NIRSpec, including modeling of slit losses and diffractive line spread functions.