Trilogy automatically scales and combines FITS images to produce color or grayscale images using Python scripts. The user assigns images to each color channel (RGB) or a single image to grayscale luminosity. Trilogy determines the intensity scaling automatically and independently in each channel to display faint features without saturating bright features. Each channel's scaling is determined based on a sample of the image (or summed images) and two input parameters. One parameter sets the output luminosity of "the noise," currently determined as 1-sigma above the sigma-clipped mean. The other parameter sets what fraction of the data (if any) in the sample region should be allowed to saturate. Default values for these parameters (0.15% and 0.001%, respectively) work well, but the user is able to adjust them. The scaling is accomplished using the logarithmic function y = a log(kx + 1) clipped between 0 and 1, where a and k are constants determined based on the data and desired scaling parameters as described above.

TRINITY statistically connects dark matter halos, galaxies and supermassive black holes (SMBHs) from z=0-10. Constrained by multiple galaxy (0 < z < 10) and SMBH datasets (0 < z < 6.5), the empirical model finds the posterior probability distributions of the halo-galaxy-SMBH connection and SMBH properties, all of which are allowed to evolve with redshift. TRINITY can predict many observational data, such as galaxy stellar mass functions and quasar luminosity functions, and underlying galaxy and SMBH properties, including SMBH Eddington average Eddington ratios. These predictions are made by different code files. There are basically two types of prediction codes: the first type generates observable data given input redshift or redshift invertals; the second type generates galaxy or SMBH properties as a function of host halo mass and redshift.

TRIP is an interactive computer algebra system that is devoted to perturbation series computations, and specially adapted to celestial mechanics. Its development started in 1988, as an upgrade of the special purpose FORTRAN routines elaborated by J. Laskar for the demonstration of the chaotic behavior of the Solar System. TRIP is a mature and efficient tool for handling multivariate generalized power series, and embeds two kernels, a symbolic and a numerical kernel. This numerical kernel communicates with Gnuplot or Grace to plot the graphics and allows one to plot the numerical evaluation of symbolic objects.

triple-stability uses a simple form of an artificial neural network, a multi-layer perceptron, to check whether a given configuration of a triple-star system is dynamically stable. The code is written in Python and the MLP classifier can be imported to other custom Python3 scripts.

Written in IDL, TRIPP performs CCD time series reduction and analysis. It provides an on-line check of the incoming frames, performs relative aperture photometry and provides a set of time series tools, such as calculation of periodograms including false alarm probability determination, epoc folding, sinus fitting, and light curve simulations.

TRIPPy (TRailed Image Photometry in Python) uses a pill-shaped aperture, a rectangle described by three parameters (trail length, angle, and radius) to improve photometry of moving sources over that done with circular apertures. It can generate accurate model and trailed point-spread functions from stationary background sources in sidereally tracked images. Appropriate aperture correction provides accurate, unbiased flux measurement. TRIPPy requires numpy, scipy, matplotlib, Astropy (ascl:1304.002), and stsci.numdisplay; emcee (ascl:1303.002) and SExtractor (ascl:1010.064) are optional.

TRISTAN-MP is a fully relativistic Particle-In-Cell (PIC) code for plasma physics computations and self-consistently solves the full set of Maxwell’s equations, along with the relativistic equations of motion for the charged particles. Fields are discretized on a finite 3D or 2D mesh, the computational grid; the code then uses time-centered and space-centered finite difference schemes to advance the equations in time via the Lorentz force equation, and to calculate spatial derivatives, so that the algorithm is second order accurate in space and time. The charges and currents derived from the particles' velocities and positions are then used as source terms to re-calculate the electromagnetic fields. TRISTAN-MP is based on the original TRISTAN code (ascl:2008.025) by O. Buneman (1993).

TRISTAN (TRIdimensional STANford) is a fully electromagnetic code with full relativistic particle dynamics. The code simulates large-scale space plasma phenomena such as the formation of systems of galaxies. TRISTAN particles which hit the boundaries are arrested there and redistributed more uniformly by having the boundaries slightly conducting, thus allowing electrons to recombine with ions and provides a realistic way of eliminating escaping particles from the code. Fresh particle fluxes can then be introduced independently across the boundaries. Written in 1993, this code has largely been superceded by TRISTAN-MP (ascl:1908.008).

TROVE (Theoretical ROVibrational Energies) performs variational calculations of rovibrational energies for general polyatomic molecules of arbitrary structure in isolated electronic states. The software numerically constructs the kinetic energy operator, which is represented as an expansion in terms of internal coordinates. The code is self-contained, requiring no analytical pre-derivation of the kinetic energy operator. TROVE is also general and can be used with any internal coordinates.

TRUVOT decontaminates Swift UVOT grism spectra for transient objects. The technique makes use of template images in a process similar to image subtraction.

TSP is an astronomical data reduction package that handles time series data and polarimetric data from a variety of different instruments, and is distributed as part of the Starlink software collection (ascl:1110.012).

The time series reconstruction method of massive astronomical catalogs reconstructs all celestial objects' time series data for astronomical catalogs with great accuracy. In addition, the program, which requires a Spark cluster, solves the boundary source leakage problem on the premise of ensuring accuracy, and the user can set different parameters for different data sets to filter the error records in the catalogs.

TTVFast efficiently calculates transit times for n-planet systems and the corresponding radial velocities. The code uses a symplectic integrator with a Keplerian interpolator for the calculation of transit times (Nesvorny et al. 2013); it is available in both C and Fortran.

TTVFaster implements analytic formulae for transit time variations (TTVs) that are accurate to first order in the planet–star mass ratios and in the orbital eccentricities; the implementations are available in several languages, including IDL, Julia, Python and C. These formulae compare well with more computationally expensive N-body integrations in the low-eccentricity, low mass-ratio regime when applied to simulated and to actual multi-transiting Kepler planet systems.

TULIPS (Tool for Understanding the Lives, Interiors, and Physics of Stars) creates diagrams of the structure and evolution of stars. It creates plots and movies based on output from the MESA stellar evolution code (ascl:1010.083). TULIPS represents stars as circles of varying size and color. The code can also visualize the size and perceived color of stars, their interior mixing and nuclear burning processes, their chemical composition, and can compare different MESA models.

turboGL is a fast Mathematica code based on a stochastic approach to cumulative weak lensing. It can easily compute the lensing PDF relative to arbitrary halo mass distributions, selection biases, number of observations, halo profiles and evolutions, making it a useful tool to study how lensing depends on cosmological parameters and impact on observations.

TurboSETI analyzes filterbank data (frequency vs. time) for narrow band drifting signals; its main purpose is to search for signals of extraterrestrial origin. TurboSETI can search the data for hundreds of drift rates (in Hz/sec) and handles either .fil or .h5 file formats. It has several dependencies, including Blimpy (ascl:1906.002) and Astropy (ascl:1304.002).

Latest version of TS (Turbospectrum), with NLTE capabilities.
Computation of stellar spectra (flux and intensities) in 1D or average stellar atmosphere models.
In order to compute NLTE stellar spectra, additional data is needed, downloadable outside GitHub.
See documentation in DOC folder

Python wrappers are available at https://github.com/EkaterinaSe/TurboSpectrum-Wrapper/ and https://github.com/JGerbs13/TSFitPy
They allow interpolation between models and fitting of spectra to derive stellar parameters.

Turbospectrum is a 1D LTE spectrum synthesis code which covers 600 molecules, is fast with many lines, and uses the treatment of line broadening described by Barklem & O’Mara (1998).

TurbuStat implements a variety of turbulence-based statistics described in the astronomical literature and defines distance metrics for each statistic to quantitatively compare spectral-line data cubes, as well as column density, integrated intensity, or other moment maps. The software can simulate observations of fractional Brownian Motion fields, including 2-D images and optically thin H I data cubes. TurbuStat also offers multicore fast-Fourier-transform support and provides a segmented linear model for fitting lines with a break point.

TVD solves the magnetohydrodynamic (MHD) equations by updating the fluid variables along each direction using the flux-conservative, second-order, total variation diminishing (TVD), upwind scheme of Jin & Xin. The magnetic field is updated separately in two-dimensional advection-constraint steps. The electromotive force (EMF) is computed in the advection step using the TVD scheme, and this same EMF is used immediately in the constraint step in order to preserve ∇˙B=0 without the need to store intermediate fluxes. The code is extended to three dimensions using operator splitting, and Runge-Kutta is used to get second-order accuracy in time. TVD offers high-resolution per grid cell, second-order accuracy in space and time, and enforcement of the ∇˙B=0 constraint to machine precision. Written in Fortran, It has no memory overhead and is fast. It is also available in a fully scalable message-passing parallel MPI implementation.

tvguide determines whether stars and galaxies are observable by TESS. It uses an object's right ascension and declination and estimates the pointing of TESS's cameras using predicted spacecraft ephemerides to determine whether and for how long the object is observable with TESS. tvguide returns a file with two columns, the first the minimum number of sectors the target is observable for and the second the maximum.

Twinkle is a Python-based tool that calculates the stellar spectral energy distribution (SED) using empirical photometric data and stellar model grids.

Twinkle was originally created to help calculate the excess infrared (IR) flux from a star. The presence of an IR excess indicates dust orbiting the star. This dust likely results from the grinding and collisions of asteroids, influenced by a larger planetary object—pointing to the potential for finding planets. You can check out the published papers from my thesis using this code in Patel, Metchev, and Heinze, 2014 and Patel et al., 2017.

Interested in learning more about debris disks? Check out my blog post.

This code base helps you quickly calculate the temperature and location of the dust to first order by fitting the assumed blackbody or modified blackbody function to the broadband excess emission.

TWO-POP-PY runs a two-population dust evolution model that follows the upper end of the dust size distribution and the evolution of the dust surface density profile and treats dust surface density, maximum particle size, small and large grain velocity, and fragmentation. It derives profiles that describe the dust-to-gas ratios and the dust surface density profiles well in protoplanetary disks, in addition to the radial flux by solid material rain out.

TWODSPEC offers programs for the reduction and analysis of long-slit and optical fiber array spectra, implemented as extensions to the FIGARO package (ascl:1203.013). The software are currently distributed as part of the Starlink software collection (ascl:1110.012). These programs are designed to do as much as possible for the user, to assist quick reduction and analysis of data; for example, LONGSLIT can fit multiple Gaussians to line profiles in batch and decides how many components to fit.

TwoDSSM solves the equations of self-gravitating hydrodynamics in the shearing sheet, with cooling. TwoDSSM is configured to use a simple, exponential cooling model, although it contains code for a more complicated (and perhaps more realistic) cooling model based on a one-zone vertical model. The complicated cooling model can be switched on using a flag.

TYCHO is a general, one dimensional (spherically symmetric) stellar evolution code written in structured Fortran 77; it is designed for hydrostatic and hydrodynamic stages including mass loss, accretion, pulsations and explosions. Mixing and convection algorithms are based on 3D time-dependent simulations. It offers extensive on-line graphics using Tim Pearson's PGPLOT (ascl:1103.002) with X-windows and runs effectively on Linux and Mac OS X laptop and desktop computers.
NOTE: This code is no longer being supported.

USNO/AE98 contains ephemerides for fifteen of the largest asteroids that The Astronomical Almanac has used since its 2000 edition. These ephemerides are based on the Jet Propulsion Laboratory (JPL) planetary ephemeris DE405 and, thus, aligned to the International Celestial Reference System (ICRS). The data cover the period from 1799 November 16 (JD 2378450.5) through 2100 February 1 (JD 2488100.5). The internal uncertainty in the mean longitude at epoch, 1997 December 18, ranges from 0.05 arcseconds for 7 Iris through 0.22 arcseconds for 65 Cybele, and the uncertainty in the mean motion varies from 0.02 arcseconds per century for 4 Vesta to 0.14 arcseconds per century for 511 Davida.

The Astronomical Almanac has published ephemerides for 1 Ceres, 2 Pallas, 3 Juno, and 4 Vesta since its 1953 edition. Historically, these four asteroids have been observed more than any of the others. Ceres, Pallas, and Vesta deserve such attention because as they are the three most massive asteroids, the source of significant perturbations of the planets, the largest in linear size, and among the brightest main belt asteroids. Studying asteroids may provide clues to the origin and primordial composition of the solar system, data for modeling the chaotic dynamics of small solar system bodies, and assessments of potential collisions. Therefore, USNO/AE98 includes more than the traditional four asteroids.

The following criteria were used to select main belt asteroids for USNO/AE98:

Diameter greater than 300 km, presumably among the most massive asteroids
Excellent observing history and discovered before 1850
Largest in their taxonomic class
The massive asteroids included may be studied for their perturbing effects on the planets while those with detailed observing histories may be used to evaluate the accuracy limits of asteroid ephemerides. The fifteen asteroids that met at least one of these criteria are

1 Ceres (new mass determination)
2 Pallas (new mass determination)
3 Juno
4 Vesta (new mass determination)
6 Hebe
7 Iris
8 Flora
9 Metis
10 Hygiea
15 Eunomia
16 Psyche
52 Europa
65 Cybele
511 Davida
704 Interamnia
The refereed paper by Hilton (1999, Astron. J. 117, 1077) describes the USNO/AE98 asteroid ephemerides in detail. The associated USNO/AA Tech Note 1998-12 includes residual plots for all fifteen asteroids and a comparison between these ephemerides and those used in The Astronomical Almanac through 1999.

Software to compact, read, and interpolate the USNO/AE98 asteroid ephemerides is also available. It is written in C and designed to work with the C edition of the Naval Observatory Vector Astrometry Software (NOVAS). The programs could be used with tabular ephemerides of other asteroids as well. The associated README file provides the details of this system.

UBER (Universal Boltzmann Equation Solver) solves the general form of Fokker-Planck equation and Boltzmann equation, diffusive or non-diffusive, that appear in modeling planetary radiation belts. Users can freely specify the coordinate system, boundary geometry and boundary conditions, and the equation terms and coefficients. The solver works for problems in one to three spatial dimensions. The solver is based upon the mathematical theory of stochastic differential equations. By its nature, the solver scheme is intrinsically Monte Carlo, and the solutions thus contain stochastic uncertainty, though the user may dictate an arbitrarily small relative tolerance of the stochastic uncertainty at the cost of longer Monte Carlo iterations.

Uncertain_blackholemass predicts virial black hole masses using a neural network model and quantifies their uncertainties. The scripts retrieve data and run feature extraction and uncertainty quantification for regression. They can be used separately or deployed to existing machine learning methods to generate prediction intervals for the black hole mass predictions.

UCL_PDR is a time dependent photon-dissociation regions model that calculates self consistently the thermal balance. It can be used with gas phase only species as well as with surface species. It is very modular, has the possibility of accounting for density and pressure gradients and can be coupled with UCL_CHEM as well as with SMMOL. It has been used to model small scale (e.g. knots in proto-planetary nebulae) to large scale regions (high redshift galaxies).

UCLCHEM is a time and depth dependent gas-grain chemical model that can be used to estimate the fractional abundances (with respect to hydrogen) of gas and surface species in every environment where molecules are present. The model includes both gas and surface reactions. The code starts from the most diffuse state where all the gas is in atomic form and evolve sthe gas to its final density. Depending on the temperature, atoms and molecules from the gas freeze on to the grains and they hydrogenate where possible. The advantage of this approach is that the ice composition is not assumed but it is derived by a time-dependent computation of the chemical evolution of the gas-dust interaction process. The code is very modular, has been used to model a variety of regions and can be coupled with the UCL_PDR and SMMOL codes.

UDAT is a pattern recognition tool for mass analysis of various types of data, including image and audio. Based on its WND-CHARM (ascl:1312.002) prototype, UDAT computed a large set of numerical content descriptors from each file it analyzes, and selects the most informative features using statistical analysis. The tool can perform automatic classification of galaxy images by training with annotated galaxy images. It also has unsupervised learning capabilities, such as query-by-example of galaxies based on morphology. That is, given an input galaxy image of interest, the tool can search through a large database of images to retrieve the galaxies that are the most similar to the query image. The downside of the tool is its computational complexity, which in most cases will require a small or medium cluster.

UFalcon rapidly post-processes N-body code output into signal maps for many different cosmological probes. The package is able to produce maps of weak-lensing convergence, linear-bias galaxy over-density, cosmic microwave background (CMB) lensing convergence and the integrated Sachs-Wolfe temperature perturbation given a set of N-body lightcones. It offers high flexibility for lightcone construction, such as user-specific survey-redshift ranges, redshift distributions and single-source redshifts. UFalcon also computes the galaxy intrinsic alignment signal, which can be treated as an additive component to the cosmological signal.

Ujti calculates geodesics, gravitational lenses and gravitational redshift in principle, for any metric. Special attention has been given to compact objects, so the current implementation considers only metrics in spherical coordinates.

UltraDark.jl simulates cosmological scalar fields. Written in Julia, it is inspired by PyUltraLight (ascl:1810.009) and designed to be simple to use and extend. It solves a non-interacting scalar field Gross-Pitaevskii equation coupled to Poisson's equation for gravitational potential. The scalar field describes scalar dark matter in models including ultralight dark matter, fuzzy dark matter, axion-like particles and the like. It also describes an inflaton field in the reheating epoch of the early universe.

This three-component package provides a Pythonic implementation of the Nested Sampling integration algorithm for Bayesian model comparison and parameter estimation. It offers multiple implementations for constrained drawing functions and a test suite to evaluate the correctness, accuracy and efficiency of various implementations. The three components are:

- a modular framework for nested sampling algorithms (nested_sampling) and their development;
- a test framework to evaluate the performance and accuracy of algorithms (testsuite); and
- UltraNest, a fast C implementation of a mixed RadFriends/MCMC nested sampling algorithm.

Ulula is an ultra-lightweight 2D hydro code for teaching purposes. The code is written in pure python and is designed to be as short and easy to understand as possible, while not compromising on performance. The latter is achieved with a simple Godunov solver and by using numpy for all array operations.

ULySS (University of Lyon Spectroscopic Analysis Software) is an open-source software package written in the GDL/IDL language to analyze astronomical data. ULySS fits a spectrum with a linear combination of non-linear components convolved with a line-of-sight velocity distribution (LOSVD) and multiplied by a polynomial continuum. ULySS is used to study stellar populations of galaxies and star clusters and atmospheric parameters of stars.

Umbrella detects, validates, and identifies asteroids. The core of this software suite, Umbrella2, includes algorithms and interfaces for all steps of the processing pipeline, including a novel detection algorithm for faint trails. A detection pipeline accessible as a desktop program (ViaNearby) builds on the library to provide near real-time data reduction of asteroid surveys on the Wide Field Camera of the Isaac Newton Telescope. Umbrella can read and write MPC optical reports, supports SkyBoT and VizieR querying, and can be extended by user image processing functions to take advantage of the algorithms framework as a multi-threaded CPU scheduler for easy algorithm parallelization.

Astrochemistry database of chemical species.

The Unicorn pipeline produces data products from the 3D-HST grism survey of four CANDELS fields. It extracts interlaced 2D and 1D spectra for all objects in the Skelton et al. (2014) photometric catalogs. It then fits the 2D spectra and multi-band photometry to determine redshifts and emission line strengths. Unicorn is built on threedhst (ascl:2411.018) and has been superseded by grizli (ascl:1905.001).

UniDAM obtains a homogenized set of stellar parameters from spectrophotometric data of different surveys. Parallax and extinction data can be incorporated into the isochrone fitting method used in UniDAM to reduce distance and age estimate uncertainties for TGAS stars for distances up to 1 kpc and decrease distance Gaia end-of-mission parallax uncertainties by about a factor of 20 and age uncertainties by a factor of two for stars up to 10 kpc away from the Sun.

The data analysis UniMAP (Unicorn Multi-window Anomaly Detection Pipeline) leverages the Temporal Outlier Factor (TOF) method to find anomalies in LVC data. The pipeline requires a target detector and a start and stop GPS time describing a time interval to analyze, and has three outputs: 1.) an array of GPS times corresponding to TOF detections; 2.) a long q-transform of the entire data interval with visualizations of the TOF detections in the time series; and 3.) q-transforms of the data windows that triggered TOF detections.

UniPOPS, a suite of programs and utilities developed at the National Radio Astronomy Observatory (NRAO), reduced data from the observatory's single-dish telescopes: the Tucson 12-m, the Green Bank 140-ft, and archived data from the Green Bank 300-ft. The primary reduction programs, 'line' (for spectral-line reduction) and 'condar' (for continuum reduction), used the People-Oriented Parsing Service (POPS) as the command line interpreter. UniPOPS unified previous analysis packages and provided new capabilities; development of UniPOPS continued within the NRAO until 2004 when the 12-m was turned over to the Arizona Radio Observatory (ARO). The submitted code is version 3.5 from 2004, the last supported by the NRAO.

The UniverseMachine applies simple empirical models of galaxy formation to dark matter halo merger trees. For each model, it generates an entire mock universe, which it then observes in the same way as the real Universe to calculate a likelihood function. It includes an advanced MCMC algorithm to explore the allowed parameter space of empirical models that are consistent with observations.

Univiewer is a visualisation program for HEALPix maps. It is written in C++ and uses OpenGL and the wxWidgets library for cross-platform portability. Using it you can:

- Rotate and zoom maps on the sphere in 3D
- Create high-resolution views of square patches of the map
- Change maximum and minimum values of the colourmap interactively
- Calculate the power spectrum of the full-sky map or a patch
- Display any column of a HEALPix map FITS file on the sphere

Since Univiewer uses OpenGL for 3D graphics, its performance is dependent your video card. It has been tested successfully on computers with as little as 8Mb video memory, but it is recommended to have at least 32Mb to get good performance.

In the 3D view, a HEALPix map is projected onto a ECP pixelation to create a texture which is wrapped around the sphere. In calculating the power spectrum, the spherical harmonic transforms are computed using the same ECP pixelation. This inevitably leads to some discrepancies at small scales due to repixelation effects, but they are reasonably small.

unpopular is an implementation of the Causal Pixel Model (CPM) de-trending method to obtain TESS Full-Frame Image (FFI) light curves. The code, written in Python, models the systematics in the light curves of individual pixels as a linear combination of light curves from many other distant pixels and removes shared flux variations. unpopular is able to preserve sector-length astrophysical signals, allowing for the extraction of multi-sector light curves from the FFI data.

unTimely Catalog Explorer searches for and visualizes detections in the unTimely Catalog, a full-sky, time-domain catalog of detections based on WISE and NEOWISE image data acquired between 2010 and 2020. The tool searches the catalog by coordinates to create finder charts for each epoch with overplotted catalog positions and light curves using the unTimely photometry, to overplot these light curves with AllWISE multi-epoch and NEOWISE-R single exposure (L1b) photometry, and to create image blinks with overlaid catalog positions in GIF format.

The unwise_psf Python module renders point spread function (PSF) models appropriate for use in modeling of unWISE coadd images. unwise_psf translates highly detailed single-exposure WISE PSF models in detector coordinates to the corresponding pixelized PSF models in coadd space, accounting for subtleties including the WISE scan direction and its considerable variation near the ecliptic poles. Applications of the unwise_psf module include performing forced photometry on unWISE coadds, constructing WISE-selected source catalogs based on unWISE coadds and masking unWISE coadd regions contaminated by bright stars.

unWISE-verse is an integrated Python pipeline for downloading sets of unWISE time-resolved coadd cutouts from the WiseView image service and uploading subjects to Zooniverse.org for use in astronomical citizen science research. This software was initially designed for the Backyard Worlds: Cool Neighbors research project and is optimized for target sets containing low luminosity brown dwarf candidates. However, unWISE-verse can be applied to other future astronomical research projects that seek to make use of unWISE infrared sky maps, such as studies of infrared variable/transient sources.

UPMASK, written in R, performs membership assignment in stellar clusters. It uses photometry and spatial positions, but can take into account other types of data. UPMASK takes into account arbitrary error models; the code is unsupervised, data-driven, physical-model-free and relies on as few assumptions as possible. The approach followed for membership assessment is based on an iterative process, principal component analysis, a clustering algorithm and a kernel density estimation.

UPSILoN (AUtomated Classification of Periodic Variable Stars using MachIne LearNing) classifies periodic variable stars such as Delta Scuti stars, RR Lyraes, Cepheids, Type II Cepheids, eclipsing binaries, and long-period variables (i.e. superclasses), and their subclasses (e.g. RR Lyrae ab, c, d, and e types) using well-sampled light curves from any astronomical time-series surveys in optical bands regardless of their survey-specific characteristics such as color, magnitude, and sampling rate. UPSILoN consists of two parts, one which extracts variability features from a light curve, and another which classifies a light curve, and returns extracted features, a predicted class, and a class probability. In principle, UPSILoN can classify any light curves having arbitrary number of data points, but using light curves with more than ~80 data points provides the best classification quality.

URCHIN is a Smoothed Particle Hydrodynamics (SPH) reverse ray tracer (i.e. from particles to sources). It calculates the amount of shielding from a uniform background that each particle experiences. Preservation of the adaptive density field resolution present in many gas dynamics codes and uniform sampling of gas resolution elements with rays are two of the benefits of URCHIN; it also offers preservation of Galilean invariance, high spectral resolution, and preservation of the standard uniform UV background in optically thin gas.

URecon reconstructs the initial conditions of N-body simulations from late time (e.g., z=0) density fields. This simple UNET architecture is implemented in TensorFlow and requires Pylians3 (ascl:2403.012) for measuring power spectrum of density fields. The package includes weights trained on Quijote fiducial cosmology simulations.

The time dependent Monte-Carlo code URILIGHT, written in Fortran 90, assumes homologous expansion. Energy deposition resulting from the decay of radioactive isotopes is calculated by a Monte-Carlo solution of the γ-ray transport, for which interaction with matter is included through Compton scattering and photoelectric absorption. The temperature is iteratively solved for in each cell by requiring that the total emissivity equals the total absorbed energy.

The util_2comp software utilities generate predictions of far-infrared Galactic dust emission and reddening based on a two-component dust emission model fit to Planck HFI, DIRBE and IRAS data from 100 GHz to 3000 GHz. These predictions and the associated dust temperature map have angular resolution of 6.1 arcminutes and are available over the entire sky. Implementations in IDL and Python are included.

The Universal Transit Modeller (UTM) is a light-curve simulator for all kinds of transiting or eclipsing configurations between arbitrary numbers of several types of objects, which may be stars, planets, planetary moons, and planetary rings. A separate fitting program, UFIT (Universal Fitter) is part of the UTM distribution and may be used to derive best fits to light-curves for any set of continuously variable parameters. UTM/UFIT is written in IDL code and its source is released in the public domain under the GNU General Public License.

uvcombine combines single-dish and interferometric data. It can combine high-resolution images that are missing large angular scales (Fourier-domain short-spacings) with low-resolution images containing the short/zero spacing. uvcombine includes the "feathering" technique for interferometry data, implementing a similar approach to CASA’s (ascl:1107.013) feather task but with additional options. Also included are consistency tests for the flux calibration and single-dish scale by comparing the data in the uv-overlap range.

Uvmcmcfit fits parametric models to interferometric data. It is ideally suited to extract the maximum amount of information from marginally resolved observations with interferometers like the Atacama Large Millimeter Array (ALMA), Submillimeter Array (SMA), and Plateau de Bure Interferometer (PdBI). uvmcmcfit uses emcee (ascl:1303.002) to do Markov Chain Monte Carlo (MCMC) and can measure the goodness of fit from visibilities rather than deconvolved images, an advantage when there is strong gravitational lensing and in other situations. uvmcmcfit includes a pure-Python adaptation of Miriad’s (ascl:1106.007) uvmodel task to generate simulated visibilities given observed visibilities and a model image and a simple ray-tracing routine that allows it to account for both strongly lensed systems (where multiple images of the lensed galaxy are detected) and weakly lensed systems (where only a single image of the lensed galaxy is detected).

UVMULTIFIT, written in Python, is a versatile library for fitting models directly to visibility data. These models can depend on frequency and fitting parameters in an arbitrary algebraic way. The results from the fit to the visibilities of sources with sizes smaller than the diffraction limit of the interferometer are superior to the output obtained from a mere analysis of the deconvolved images. Though UVMULTIFIT is based on the CASA package, it can be easily adapted to other analysis packages that have a Python API.

The two Swift UVOT grisms provide uv (170.0-500.0 nm) and visible (285.0-660.0 nm) spectra with a resolution of R~100 and 75. To reduce the grism data, UVOTPY extracts a spectrum given source sky position, and outputs a flux calibrated spectrum. UVOTPY is a replacement for the UVOTIMGRISM FTOOL (ascl:9912.002) in the HEADAS Swift package. Its extraction uses a curved aperture for the uv spectra, accounts the coincidence losses in the detector, provides more accurate anchor positions for the wavelength scale, and is valid for the whole detector.

uvplot makes nice plots of deprojected interferometric visibilities (often called uvplots). It implements plotting functionality, handles MS tables with spectral windows with different number of channels, and can import visibilities from ASCII to MS Table. It also allows export of specific channels. uvplot can be installed inside the NRAO CASA package (ascl:1107.013).

The Versatile Advection Code (VAC) is a freely available general hydrodynamic and magnetohydrodynamic simulation software that works in 1, 2 or 3 dimensions on Cartesian and logically Cartesian grids. VAC runs on any Unix/Linux system with a Fortran 90 (or 77) compiler and Perl interpreter. VAC can run on parallel machines using either the Message Passing Interface (MPI) library or a High Performance Fortran (HPF) compiler.

VADER is a flexible, general code that simulates the time evolution of thin axisymmetric accretion disks in time-steady potentials. VADER handles arbitrary viscosities, equations of state, boundary conditions, and source and sink terms for both mass and energy.

VaeX (Visualization and eXploration) interactively visualizes and explores big tabular datasets. It can calculate statistics such as mean, sum, count, and standard deviation on an N-dimensional grid up to a billion (10⁹) objects/rows per second. Visualization is done using histograms, density plots, and 3d volume rendering, allowing interactive exploration of big data. VaeX uses memory mapping, zero memory copy policy and lazy computations for best performance, and integrates well with the Jupyter/IPython notebook/lab ecosystem.

Validation provides codes to compare several observations to simulated data with stellar mass and star formation rate, simulated data stellar mass function with observed stellar mass function from PRIMUS or SDSS-GALEX in several redshift bins from 0.01-1.0, and simulated data B band luminosity function with observed stellar mass function, and to create plots for various attributes, including stellar mass functions, and stellar mass to halo mass. These codes can model predictions (in some cases alongside observational data) to test other mock catalogs.

VAPHOT is an aperture photometry package for precise time−series photometry of uncrowded fields, geared towards the extraction of target lightcurves of eclipsing or transiting systems. Its photometric main routine works within the IRAF (ascl:9911.002) environment and is built upon the standard aperture photometry task 'phot' from IRAF, using optimized aperture sizes. The associated analysis program 'VANALIZ' works in the IDL environment. It performs differential photometry with graphical and numerical output. VANALIZ produces plots indicative of photometric stability and permits the interactive evaluation and weighting of comparison stars. Also possible is the automatic or manual suppression of data-points and the output of statistical analyses. Several methods for the calculation of the reference brightness are offered. Specific routines for the analysis of transit 'on'-'off' photometry, comparing the target brightness inside against outside a transit are also available.

VAPID (Voigt Absorption Profile [Interstellar] Dabbler) models interstellar absorption lines. It predicts profiles and optimizes model parameters by least-squares fitting to observed spectra. VAPID allows cloud parameters to be optimized with respect to several different data set simultaneously; those data sets may include observations of different transitions of a given species, and may have different S/N ratios and resolutions.

VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers. VAPOR provides an interactive 3D visualization environment that runs on most UNIX and Windows systems equipped with modern 3D graphics cards. VAPOR provides:

- A visual data discovery environment tailored towards the specialized needs of the astro and geosciences CFD community
- A desktop solution capable of handling terascale size data sets
- Advanced interactive 3D visualization tightly coupled with quantitative data analysis
- Support for multi-variate, time-varying data
- Close coupling with RSI's powerful interpretive data language, IDL
- Support for 3D visualization of WRF-ARW datasets

VapoRock calculates the equilibrium partial pressures of metal-bearing gas species of specific elements above the magma ocean surface to determine the metal-bearing composition of the atmosphere as a function of temperature and the bulk composition of the magma ocean. It utilizes ENKI's ThermoEngine (ascl:2208.006) and combines estimates for element activities in silicate melts with thermodynamic data for metal and metal oxide vapor species.

Varstar Detect uses several numerical and statistical methods to filter and interpret the data obtained from TESS. It performs an amplitude test to determine whether a star is variable and if so, provides the characteristics of each star through phenomenological analysis of the lightcurve.

The VARTOOLS program is a command line utility that provides tools for analyzing time series astronomical data. It implements a number of routines for calculating variability/periodicity statistics of light curves, as well as tools for modifying and filtering light curves.

VaST (Variability Search Toolkit) finds variable objects on a series of astronomical images in FITS format. The software performs object detection and aperture photometry using SExtractor (ascl:1010.064) on each image, cross-matches lists of detected stars, performs magnitude calibration with respect to the first (reference) image and constructs a lightcurve for each object. The sigma-magnitude, Stetson's L variability index, Robust Median Statistic (RoMS) and other plots may be used to visually identify variable star candidates. The two distinguishing features of VaST are its ability to perform accurate aperture photometry of images obtained with non-linear detectors and to handle complex image distortions. VaST can be used in cases of unstable PSF (e.g., bad guiding or with digitized wide-field photographic images), and has been successfully applied to images obtained with telescopes ranging from 0.08 to 2.5m in diameter equipped with a variety of detectors including CCD, CMOS, MIC and photographic plates.

VBBinaryLensing forward models gravitational microlensing events using the advanced contour integration method; it supports single and binary lenses. The lens map is inverted on a collection of points on the source boundary to obtain a corresponding collection of points on the boundaries of the images from which the area of the images can be recovered by use of Green’s theorem. The code takes advantage of a number of techniques to make contour integration much more efficient, including using a parabolic correction to increase the accuracy of the summation, introducing an error estimate on each arc of the boundary to enable defining an optimal sampling, and allowing the inclusion of limb darkening. The code is written as a C++ library and wrapped as a Python package, and can be called from either C++ or Python.

VCAL-SPHERE, for VIP-based Calibration of VLT/SPHERE data, is a versatile pipeline for high-contrast imaging of exoplanets and circumstellar disks. The pipeline covers all steps of data reduction, including raw calibration, pre-processing and post-processing (i.e., modeling and subtraction of the stellar halo), for the IFS, IRDIS-DBI and IRDIS-CI modes (and combinations thereof) of the VLT instrument SPHERE. The three main steps of the reduction correspond to different modules, where the first follows the recommended EsoRex (ascl:1504.003) workflow and associated recipes with occasional inclusion of VIP (ascl:1603.003) routines (e.g., for PCA-based sky subtraction), while the other two stages fully rely on the VIP toolbox. Although the default parameters of the pipeline should yield a good reduction in most cases, these can be tuned using JSON parameter files for each stage of the pipeline for optimal reduction of specific datasets.

void-dwarf-analysis analyzes Keck Cosmic Web Imager datacubes to produce maps of kinematic properties (velocity and velocity dispersion), emission line fluxes, and gas-phase metallicities of void dwarf galaxies.

Velbin convolves the radial velocity offsets due to binary orbital motions with a Gaussian to model an observed velocity distribution. This can be used to measure the mean velocity and velocity dispersion from an observed radial velocity distribution, corrected for binary orbital motions. Velbin fits single- or multi-epoch data with any arbitrary binary orbital parameter distribution (as long as it can be sampled properly), however it always assumes that the intrinsic velocity distribution (i.e. corrected for binary orbital motions) is a Gaussian. Velbin samples (and edits) a binary orbital parameter distribution, fits an observed radial velocity distribution, and creates a mock radial velocity distribution that can be used to provide the fitted radial velocities in the single_epoch or multi_epoch methods.

High-quality velocity maps of galaxies frequently exhibit signatures of non-circular streaming motions. velfit yields results that are more easily interpreted than the commonly used procedure. It can estimate the magnitudes of forced non-circular motions over a broad range of bar strengths from a strongly barred galaxy, through cases of mild bar-like distortions to placing bounds on the shapes of halos in galaxies having extended rotation curves.

This code is no longer maintained and has been superseded by DiskFit (ascl:1209.011).

velocileptors computes the real- and redshift-space power spectra and correlation functions of biased tracers using 1-loop perturbation theory (with effective field theory counter terms and up to cubic biasing) as well as the real-space pairwise velocity moments. It provides simple computation of the power spectrum wedges or multipoles, and uses a reduced set of parameters for computing the most common case of the redshift-space power spectrum. In addition, velocileptors offers two "direct expansion" modules available in LPT and EPT.

VELOCIraptor-STF, formerly STructure Finder (ascl:1306.009), is a 6-Dimensional Friends-of-Friends (6D-FoF) phase space halo finder and constructs halo catalogs. The code uses using MPI and OpenMP APIs and can be compiled as a library for on-the-fly halo finding within an N-body/hydrodynamnical code. There is an associated halo merger tree code TreeFrog (ascl:1911.021).

venice reads a mask file (DS9 or fits type) and a catalogue of objects (ascii or fits type) to create a pixelized mask, find objects inside/outside a mask, or generate a random catalogue of objects inside/outside a mask. The program reads the mask file and checks if a point, giving its coordinates, is inside or outside the mask, i.e. inside or outside at least one polygon of the mask.

Verne calculates the Earth-stopping effect for super-heavy Dark Matter (DM). The code allows you to calculate the speed distribution (and DM signal rate) at an arbitrary detector location on the Earth. The calculation takes into account the full anisotropic DM velocity distribution and the full velocity dependence of the DM-nucleus cross section. Results can be obtained for any DM mass and cross section, though the results are most reliable for very heavy DM particles.

Validation of Exoplanet Signals using a Probabilistic Algorithm (VESPA) calculates false positive probabilities and statistically validates transiting exoplanets. Written in Python, it uses isochrones [ascl:1503.010] and the package simpledist.

vetting contains simple, stand-alone Python tools for vetting transiting signals in NASA's Kepler, K2, and TESS data. The code performs a centroid test to look for significant changes in the centroid of a star during a transit or eclipse. vetting requires an installation of Python 3.8 or higher.

Veusz produces a wide variety of publication-ready 2D and 3D plots. Plots are created by building up plotting widgets with a consistent object-based interface, and the package provides many options for customizing plots. Veusz can import data from text, CSV, HDF5 and FITS files; datasets can also be entered within the program and new datasets created via the manipulation of existing datasets using mathematical expressions and more. The program can also be extended, by adding plugins supporting importing new data formats, different types of data manipulation or for automating tasks, and it supports vector and bitmap output, including PDF, Postscript, SVG and EMF.

Vevacious takes a generic expression for a one-loop effective potential energy function and finds all the tree-level extrema, which are then used as the starting points for gradient-based minimization of the one-loop effective potential. The tunneling time from a given input vacuum to the deepest minimum, if different from the input vacuum, can be calculated. The parameter points are given as files in the SLHA format (though is not restricted to supersymmetric models), and new model files can be easily generated automatically by the Mathematica package SARAH (ascl:1904.020).

VH-1 is a multidimensional ideal compressible hydrodynamics code written in FORTRAN for use on any computing platform, from desktop workstations to supercomputers. It uses a Lagrangian remap version of the Piecewise Parabolic Method developed by Paul Woodward and Phil Colella in their 1984 paper. VH-1 comes in a variety of versions, from a simple one-dimensional serial variant to a multi-dimensional version scalable to thousands of processors.

VHD is a numerical study of viscous fluid accretion onto a black hole. The flow is axisymmetric and uses a pseudo-Newtonian potential to model relativistic effects near the event horizon. VHD is based on ZEUS-2D (Stone & Norman 1992) with the addition of an explicit scheme for the viscosity.

The Victoria–Regina stellar models are comprised of seventy-two grids of stellar evolutionary tracks accompanied by complementary zero-age horizontal branches and are presented in “equivalent evolutionary phase” (.eep) files. This Fortran 77 software interpolates isochrones, isochrone population functions, luminosity functions, and color functions of stellar evolutionary tracks.

The Void IDentification and Examination toolkit (VIDE) identifies voids using a modified version of the parameter-free void finder ZOBOV (ascl:1304.005); a Voronoi tessellation of the tracer particles is used to estimate the density field followed by a watershed algorithm to group Voronoi cells into zones and subsequently voids. Output is a summary of void properties in plain ASCII; a Python API is provided for analysis tasks, including loading and manipulating void catalogs and particle members, filtering, plotting, computing clustering statistics, stacking, comparing catalogs, and fitting density profiles.

Viewpoints is an interactive tool for exploratory visual analysis of large high-dimensional (multivariate) data. It uses linked scatterplots to find relations in a few seconds that can take much longer with other plotting tools. Its features include linked scatter plots with brushing, dynamic histograms, normalization, and outlier detection/removal.

VIM (Virtual Observatory Integration and Mining) is a data retrieval and exploration application that assumes an astronomer has a list of 'sources' (positions in the sky), and wants to explore archival catalogs, images, and spectra of the sources, in order to identify, select, and mine the list. VIM does this either through web forms, building a custom 'data matrix,' or locally through downloadable Python code. Any VO-registered catalog service can be used by VIM, as well as co-registered image cutouts from VO-image services, and spectra from VO-spectrum services. The user could, for example, show together: proper motions from GSC2, name and spectral type from NED, magnitudes and colors from 2MASS, and cutouts and spectra from SDSS. VIM can compute columns across surveys and sort on these (eg. 2MASS J magnitude minus SDSS g). For larger sets of sources, VIM utilizes the asynchronous Nesssi services from NVO, that can run thousands of cone and image services overnight.

VINE is a particle based astrophysical simulation code. It uses a tree structure to efficiently solve the gravitational N-body problem and Smoothed Particle Hydrodynamics (SPH) to simulate gas dynamical effects. The code has been successfully used for a number of studies on galaxy interactions, galactic dynamics, star formation and planet formation and given the implemented physics, other applications are possible as well.

VIP (Vortex Image Processing pipeline) provides pre- and post-processing algorithms for high-contrast direct imaging of exoplanets. Written in Python, VIP provides a very flexible framework for data exploration and image processing and supports high-contrast imaging observational techniques, including angular, reference-star and multi-spectral differential imaging. Several post-processing algorithms for PSF subtraction based on principal component analysis are available as well as the LLSG (Local Low-rank plus Sparse plus Gaussian-noise decomposition) algorithm for angular differential imaging. VIP also implements the negative fake companion technique coupled with MCMC sampling for rigorous estimation of the flux and position of potential companions.

viper (Velocity and IP EstimatoR) measures differential radial velocities from stellar spectra taken through iodine or other gas cells. It convolves the product of a stellar template and a gas cell spectrum with an instrumental profile. Via least square fitting, it optimizes the parameters of the instrumental profile, the wavelength solution, flux normalization, and the stellar Doppler shift. viper offers various functions to describe the instrumental profile such as Gaussian, super-Gaussian, skewed Gaussian or mixtures of Gaussians. The code is developed for echelle spectra; it can handle data from CES, CRIRES+, KECK, OES, TCES, and UVES, and additional instruments can easily be added. A graphical interface facilitates the work with numerous flexible options.

VirGO is the next generation Visual Browser for the ESO Science Archive Facility developed by the Virtual Observatory (VO) Systems Department. It is a plug-in for the popular open source software Stellarium adding capabilities for browsing professional astronomical data. VirGO gives astronomers the possibility to easily discover and select data from millions of observations in a new visual and intuitive way. Its main feature is to perform real-time access and graphical display of a large number of observations by showing instrumental footprints and image previews, and to allow their selection and filtering for subsequent download from the ESO SAF web interface. It also allows the loading of external FITS files or VOTables, the superimposition of Digitized Sky Survey (DSS) background images, and the visualization of the sky in a `real life' mode as seen from the main ESO sites. All data interfaces are based on Virtual Observatory standards which allow access to images and spectra from external data centers, and interaction with the ESO SAF web interface or any other VO applications supporting the PLASTIC messaging system.

Virtual Telescope predicts the signal-to-noise and other parameters of imaging and/or spectroscopic observations as a function of telescope size, detector noise, and other factors for the Next-Generation Space Telescope.

ViSBARD interactively visualizes and analyzes space physics data. It provides an interactive integrated 3-D and 2-D environment to determine correlations between measurements across many spacecraft. It supports a variety of spacecraft data products and MHD models and is easily extensible to others. ViSBARD provides a way of visualizing multiple vector and scalar quantities as measured by many spacecraft at once. The data are displayed three-dimesionally along the orbits which may be displayed either as connected lines or as points. The data display allows the rapid determination of vector configurations, correlations between many measurements at multiple points, and global relationships. With the addition of magnetohydrodynamic (MHD) model data, this environment can also be used to validate simulation results with observed data, use simulated data to provide a global context for sparse observed data, and apply feature detection techniques to the simulated data.

viscm is a Python tool for visualizing and designing colormaps using colorspacious and matplotlib.