IGRINS RV extracts radial velocities (RVs) from spectra taken with the Immersion GRating INfrared Spectrometer (IGRINS). It uses a modified forward modeling technique that leverages telluric absorption lines as a common-path wavelength calibrator. IGRINS RV achieves an RV precision in the H and K bands of around 25-30 m/s for narrow-line stars.

The IGRINS (Immersion Grating Infrared Spectrometer) PipeLine Package (PLP) processes all IGRINS observing data, such as that from the McDonald 2.7m, LDT/DCT, or Gemini-South telescopes, without (or with a minimum of) human interaction. It was also designed to be adaptable for a real time processing during the observing run. The IGRINS PLP uses a "recipe" to process a certain data group and requires an input file describing which recipe should be used with which data sets.

TESS-SIP creates a Systematics-insensitive Periodogram (SIP) using lightkurve (ascl:1812.013) to detect long period rotation in NASA's TESS mission data. The SIP method detrends telescope systematics (the TESS scattered light) simultaneously with calculating a Lomb-Scargle periodogram, thus allowing estimation of the rotation rate of variables with a period of >30 days when there are multiple sectors.

blasé performs whole-spectrum fitting by cloning 10,000+ spectral lines from a pre-computed synthetic spectral model template and then learning the perturbations to those lines through comparison to real data. Each spectral line has four parameters, yielding possibly 40,000+ parameters. The technique uses autodiff to tune the parameters precisely and quickly. Built in PyTorch with native GPU support, blasé can be extended to, for example, Doppler imaging, Precision RVs, and abundances.

ATOCA (Algorithm to Treat Order Contamination) extracts and decontaminates spectroscopic images with multiple sources or diffraction orders. For all orders and sources, the package takes the wavelength solutions, the trace profiles, the throughputs, and the spectral resolution kernels as input. From these, ATOCA simultaneously models the detector and extracts the spectra.

Optimal BLS explicitly includes Keplerian dynamics in transit searches, which enhances transit detectability while reducing the resources and time usually required for such searches. The (standard) BLS is either fairly insensitive to long-period planets or less sensitive to short-period planets and computationally slower by a significant factor of ~330 (for a 3 yr long dataset). Physical system parameters, such as the host star's size and mass, directly affect transit search. Optimal BLS leverages this understanding to optimize the search for every star individually.

spaceKLIP reduces and analyzes JWST NIRCam and MIRI coronagraphy data. The package runs the official JWST stage 1 and 2 data reduction pipelines with several modifications that improve the quality of high-contrast imaging reductions. spaceKLIP then performs PSF subtraction based on the KLIP algorithm as implemented in pyKLIP (ascl:1506.001), outputs contrast curves, and enables forward model PSF fitting for any detected companions in order to extract their properties (offset and flux).

SpecMatch-Emp extracts the fundamental properties of a star (effective temperature, radius, and metallicity) by comparing a target star's spectrum to a library of spectra from stars with known properties. The spectral library comprises high-resolution, high signal-to-noise observed spectra from Keck/HIRES for 404 touchstone stars with well-determined stellar parameters derived from interferometry, asteroseismology, and spectrophotometry. The code achieves accuracies of 100K, 15%, and 0.09 dex in Teff, Rstar, and [Fe/H] respectively for FGKM dwarfs.

The PACMAN pipeline reduces and analyzes Hubble/Wide Field Camera 3 (WFC3) observations of transiting exoplanets. The pipeline runs end-to-end, beginning with a time series of 2D images and ending with a spectrum for the planet, and includes both spectral extraction and light curve fitting. PACMAN can easily fit multiple observations simultaneously.

PyMieScatt (Python Mie Scattering) calculates relevant parameters including absorption, scattering, extinction, asymmetry, and backscatter. The package also contains single-line functions to calculate optical coefficients (in Mm-1) of ensembles of particles in lognormal (with single or multiple modes) or custom size distributions. The inverse calculations retrieve the complex refractive index from laboratory measurements of scattering and absorption (or backscatter), useful for studying atmospheric organic aerosol of unknown composition.

Crimson Light is a tool to visualize and slice metadata on the available archival observations of samples of astrophysical objects. This visualization enables the user to view available multi-wavelength datasets for a range of objects, optionally filtering the displayed observations on the basis of (angular) resolution, wavelength/frequency coverage, and other properties.

The Parallel Interferometric GPU Imager (Pigi) is a novel implementation of the image domain gridding algorithm that is compatible with both NVIDIA and AMD graphics cards. It provides a high-performance implementation capable of gridding hundreds of mega visibilities per second on modest hardware.

Pigi can correct for baseline-, time-, and direction-dependent effects such as the primary beam or ionosphere as part of the (de)gridding process.

Pigi provides end-to-end deconvolution capabilities with a basic iterative cleaning implementation.

WATSON (Visual Vetting and Analysis of Transits from Space ObservatioNs) enables a comfortable visual vetting of transiting signal candidates from Kepler, K2, and TESS missions. The code looks for transit-like signals that could be generated by other sources or instrument artifacts and runs simplified tests on scenarios including transit shape model fit, odd-even transits checks, and centroids shifts. It also considers optical ghost effects, transit source offsets, and several other scenarios. WATSON then computes metrics and flags problematic signals.

The Tiberius pipeline, written in Python, extracts and reduces time-series spectra and fits exoplanet transit light curves. Written in Python, the code can extract spectra from all four JWST instruments, ground-based long-slit spectrographs, and Keck/NIRSPEC echelle spectra. The light curve fitting routines in Tiberius can be used as standalone code to fit, for example, HST light curves extracted with other methods.

SPCA (Spitzer Phase Curve Analysis) analyzes Spitzer/IRAC observations of exoplanets. It implements 2D polynomial, Pixel Level Decorrelation, BiLinearly-Interpolated Sub-pixel Sensitivity mapping, and Gaussian Process decorrelation methods, allowing the user to change techniques by setting a single variable. The code's modular structure enables integration of custom astrophysical models and decorrelation methods. SPCA can reduce and decorrelate multiple datasets with a single command.

TLCM (Transit and Light Curve Modeler) analyzes the light curves of transiting exoplanets. Written in IDL and runnable under GDL, the code fits the light curves with quadratic limb darkening law; the limb darkening coefficients can be different for the two objects considered. The package carries out the fit of the transit + occultation + out-of-transit variation + radial velocity (RV) model to the observed light curve to find the best agreement between model and observations. TLCM also estimates the uncertainties of the fitted parameters.

The Giants pipeline accesses TESS data, produces noise-corrected light curves, and searches for planets transiting evolved stars. Built with Lightkurve (ascl:1812.013) and written in Python, its emphasis is on finding giant planets around subgiant and RGB stars in TESS Full Frame Images (FFIs). Giants produces a one-page PDF summary for each target.

polyrot computes the structure of rotating polytropic bodies. The code computes the equilibrium structure of rotating planets and stars modeled as "polytropes" with pressure and density, and can also compute models including rotation specified as a function of cylindrical radius. polyrot includes a basic plotting function that can show a cross-section along the rotation axis with the colormap indicating density, and a line plotting the surface radius of the star; these and other quantities are attached as attributes to the model.

MOLPOP-CEP calculates the exact solution of radiative transfer problems in multi-level atomic systems. The radiative transfer equations are analytically integrated to reduce the final problem to the solution of a non-linear algebraic system of equations in the level populations. The code uses Coupled Escape Probability formalism to analytically solve the radiative transfer. Written in Fortran 90, MOLPOP-CEP is limited to plane-parallel slabs that can present arbitrary spatial variations of the physical conditions.

chemcomp models and enables the study of the formation of planets in 1D protoplanetary disks. It includes disk physics for viscous disk evolution, pebble growth and evolution applying the two populations model, evaporation and condensation at evaporation lines, and chemical compositions. Written in Python, chemcomp also includes planet physics for type-I and type-II migration, thermal and dynamical torques, and pebble and gas accretion.

speedyfit fits the photometric spectral energy distribution of stars using a Markov chain Monte Carlo approach to determine the errors on the derived parameters. This command line tool searches the most common online databases for photometric observations of a target and automatically pulls archive photometry from the main surveys. The code fits theoretical atmosphere models to the obtained photometry. Speedyfit handles both single and binary stars and allows for the inclusion of constraints from other sources, such as atmosphere parameters derived from spectroscopy, distances, or reddening.

RadioBEAR (Radio BErkeley Atmospheric Radiative-transfer) calculates the brightness temperature of planetary atmospheres in the meter-to-millimeter wavelength range. The code assumes the atmosphere is in local thermodynamic equilibrium; it can calculate the RT-derived brightness temperatures of a planet on each location on the planet and create 2D model maps of the planet's disk.

SpectralRadex runs RADEX (ascl:1010.075) directly from Python and creates model spectra from RADEX outputs. The package uses F2PY (Fortran to Python interface generator) to compile a version of RADEX written in modern Fortran, most importantly dropping the use of common blocks. As a result, running a RADEX model creates no subprocesses and can be parallelized. SpectralRadex uses the RADEX calculated line opacities and excitation temperatures to calculate the brightness temperature as a function of frequency. This allows observed spectra to be modeled in Python in a non-LTE fashion.

breads (Broad Repository for Exoplanet Analysis, Discovery, and Spectroscopy) provides a toolkit for data analyses in astronomical spectroscopy of exoplanets, in particular frameworks for rigorous forward modeling of observational data to achieve physical inferences with reduced systematic biases. Users choose a data class, a forward model function, and a fitting strategy. Data classes normalize the data format, simplifying reduction across different spectrographs while allowing for specific behaviors of each instrument to also be coded into their own specific class. breads provides specific functionality for modeling data from JWST NIRSpec, Keck OSIRIS, and Keck KPIC, but the underlying mathematical framework is more general.

ECCOplanets simulates the formation of rocky planets in chemical equilibrium (based on a Gibbs free energy minimisation). The package includes tools for analyzing the simulated planet and two databases, one of thermochemical data and the other of stellar abundance patterns. ECCOplanets provides a simplified starting point for getting an approximate idea of the variety of planetary compositions based on the variety of stellar compositions.

NEXO (Nonsingular Estimator for EXoplanet Orbits) fits exoplanet orbits to direct astrometric measurements using nonlinear batch estimation and nonsingular orbital elements. The estimation technique is based on the unscented transform, which approximates probability distributions using finite, deterministic sets of weighted sample points. Furthermore, NEXO uses Gaussian mixtures to account for the strong nonlinearities in the measurement model. As a fitting basis, it uses a set of orbital elements developed specifically for directly observed exoplanets, combining features of the Thiele–Innes constants and the Cohen–Hubbard nonsingular elements.

ExoTR (Exoplanetary Transmission Retrieval) interprets exoplanetary transmission spectra using a Bayesian inverse retrieval algorithm. The code can be used in two ways; the first is by leveraging the physics forward model only to generate synthetic planetary atmospheric transmission spectra (including the addition of errorbars). The second way is by using a retrieval routine based on nested sampling (i.e., MultiNest (ascl:1109.006)) to extract physical and chemical information from the input transmission spectra.

The CIANNA framework creates and trains deep-learning models for astronomical data analysis. Functionalities and optimizations are added based on relevance to astrophysical problem-solving. CIANNA builds and trains a wide variety of neural network architectures for various tasks through a high-level Python interface. It supports both computing on CPU and GPU acceleration through low-level CUDA programming, taking advantage of AI-dedicated hardware substructures. CIANNA distinguishes itself by its low latency, allowing tight integration with other codes.

tshirt (Time Series Helper and Integration Reduction Tool) processes raw data on exoplanet systems for time series science. It reduces raw data to produce flat fields, subtracts bias, and corrects gain. tshirt also performs photometric and optimal spectral extraction of light curves.

Haystacks creates high-fidelity spatial and spectral models of complete planetary systems including star, planets, interplanetary dust, and astrophysical background sources. These models are intended for use in simulations of direct imaging and spectroscopy with high-contrast instruments on exoplanet missions to prepare future exoEarth observations.

pympc performs checks for the presence of minor and major Solar System bodies at specified coordinates. Orbital elements from the Minor Planet Center are used to propagate orbits to determine the position of asteroids, comets, NEOS, planets and major moons at the request epoch. Topocentric corrections are included to allow for observatory-specific positions. The requested position can also be checked for being within the Hill Sphere (in projection) of any Solar System planet.

CAFE (Continuum And Feature Extraction) fits JWST IFU data; the code is a Python version of the original CAFE IDL software for fitting Spitzer/IRS spectra. The code contains two main tools: (1) the CAFE Region Extraction Tool Automaton (CRETA) and (2) the CAFE spectral fitting tool, or fitter. CRETA performs single-position and full-grid extractions from JWST IFU datasets; that is, from pipeline-processed cubes obtained with the NIRSpec IFU and MIRI MRS instruments. The CAFE fitter uses the spectra extracted by CRETA (or spectra provided by the user) and performs a spectral decomposition of the continuum emission (stellar and/or dust), as well as of a variety of common spectral features (in emission and absorption) present in the near- and mid-IR spectra of galaxies, including prominent, broad emission from small grains and molecules such as Polycyclic Aromatic Hydrocarbons (PAHs). The full dust treatment (size and composition) performed by CAFE allows the dust continuum model components to fit not only spectra from typical star-forming galaxies, but also those from more extreme, heavily dust-obscured starburst galaxies, such as luminous infrared galaxies (LIRGs and ULIRGs), active galactic nuclei (AGN), or very luminous quasars.

S3Fit is a python code for the analysis of observational data of galaxies, which can fit spectrum and multi-band photometric Spectral Energy Distribution (SED) simultaneously. It is written to improve the moderate constraints on properties of continuum models in a pure spectral fitting due to the limited wavelength coverage. S3Fit support multiple models with multiple components, and can handle complex systems with a mixed contribution of Active Galactic Nucleus (AGN) and its host galaxy in both of continua and emission lines (e.g., narrow lines and broad outflow lines). The fitting strategy is optimized to enable an efficient solution of the best-fit results for several tens of parameters and model components. S3Fit is also extensible for adding new functions and components by users (e.g., new band filters, new star formation history functions, new emission lines, and also new types of models).

A tabulated version of the slim disk model for fitting tidal disruption events (TDEs) is presented. The synthetic X-ray spectral library is created by ray-tracing stationary, general relativistic slim disks and consistently incorporating gravitational redshift, Doppler, and lensing effects.

easyspec is a tool designed to streamline long-slit spectroscopy, offering an intuitive framework for reducing, extracting, and analyzing astrophysical spectra.

γ-Cascade (also called GCascade) uses a semi-analytic approach to model gamma-ray propagation through cosmological distances accounting for attenuation, the formation of electromagnetic cascades,and cosmological redshifting. V4 implements an assortment of the most widely used EBL models, significantly improves computational precision, and provides new core functionality. Additionally, GCascadeV4 uses a new method to estimate the uncertainty due to the EBL model.

lintsampler performs linear interpolant sampling to create a set of sample points from a density function. The code uses the evaluation of the density at the two endpoints of 1D interval, or the four corners of a 2D rectangle, or generally the 2^k vertices of a dimensional hyperbox (or a series of such hyperboxes, e.g., the cells of a k-dimensional grid) to draw random samples within the hyperbox. lintsampler works by evaluating a given PDF on the nodes of a grid (or grid-like structure, such as a tree); the number of evaluations (and memory occupancy) grows exponentially with the number of dimensions.

POSEIDON models and retrieves 1D, 2D, and 3D exoplanet transmission spectra. Given a set of observed exoplanet spectra from space-based or ground-based telescopes, the code uses Bayesian techniques to infer the atmospheric properties of the planet. POSEIDON also includes disk-integrated thermal emission and reflection spectra modeling and retrievals for both secondary eclipses and directly-imaged substellar objects.

Mister plotter (mr-plotter) creates paper-quality mass-radius diagrams based on a wide range of state-of-the-art models of planetary interiors and atmospheres. It can be used to contextualize planets and infer their possible internal structures. It can also be used to search for correlations at a population level with its color-coding option based on any property collected in the NASA Exoplanet Archive, PlanetS, and Exoplanet.eu catalogs. mr-plotter can also produce article-ready two-column plots.

The visualization tool MARDIGRAS (Mass-Radius DIaGRAm with Sliders) enables simple and intuitive manipulation of mass-radius relationships (also known as iso-composition curves) using interactive sliders. It infers composition based on mass and radius (and other parameters). As a result, it requires use of actual measurements of mass and radius; values that are upper/lower limits, derived from empirical mass-radius relations, or are somewhat controversial should not be used. MARDIGRAS screen captures can be used for general scientific communication but are not of suitable quality for article publication.

The euclidlib python package is an unofficial tool designed to read products from the Euclid Consortium Science Ground Segment. Euclidlib offers user-friendly reading and writing routines, and effectively enables to work overall with Large-Scale Structure cosmological products.

squishyplanet produces realistic lightcurves and phase curves of non-spherical exoplanets. The code generates models of triaxial planets; fitting for the triaxial shape can provide additional constraints on the planet’s interior properties and evolution. squishyplanet also handles complex limb darkening profiles while also accounting for the planet’s non-circular, potentially time-varying, projected shape.

CLOWN (CLOud Watcher at Night) detects and monitors clouds in real time. The software can be used with any type of all-sky camera even without knowing its parameters; parameters are stored instead in a configuration file. CLOWN correctly traces cloud positions in the sky and provides accurate pointing information to the observation planning of the optical telescope to avoid cloudy areas.

cogsworth merges rapid population synthesis and galactic dynamics together; the code can evolve a population of stars using population synthesis while self-consistently integrating their orbits with a chosen galactic potential. This enables exploration of the full evolutionary history (both stellar and orbital) of a population of stars and the ability to make predictions for present day kinematics and other distributions. cogsworth also provides tools for transforming the intrinsic populations into observables and for classifying the nature of each system.

ForestFlow emulates the linear biases and small-scale deviation parameters of the 3D flux power spectrum of the Lyman-alpha forest. The parameters are modeled as a function of cosmology – the small-scale amplitude and slope of the linear power spectrum – and the physics of the intergalactic medium.

BlendingToolKit (BTK) generates images of blended objects and evaluate performance metrics on various detection, deblending and measurement algorithms. The toolkit is a convenient way to produce multi-band postage stamp images of blend scenes and evaluate the performance of deblending algorithms, as well as train samples for machine learning algorithms.

Combustion Toolbox (CT) models thermodynamic properties of the gaseous species with the ideal gas equation of state (EoS). Written in MATLAB, this thermochemical code is modular and has three main modules: CT-EQUIL, CT-SD, and CT-ROCKET. CT-EQUIL computes the composition at the equilibrium of multi-component gas mixtures that undergo canonical thermochemical transformations from an initial state (reactants). CT-SD solves steady-state shock and detonation waves in either normal or oblique incidence, and CT-ROCKET computes the theoretical performance of rocket engines under highly idealized conditions. Modules can be accessed through user-friendly GUI or from MATLAB’s command line in plain code mode.

FitTeD solves time-dependent general relativistic disc equations to fit multi-band light curves and spectra. It includes relativistic optics effects such as Doppler and gravitational energy shifting, and gravitational lensing, and can include non-disc light curve and spectral components to, for example, model the early time rise and decay of tidal disruption event light curves in optical-to-UV bands. FitTeD also provides Monte Carlo Markov Chain fitting procedures that return posterior distributions of black hole and disc parameters.

gwforge generates mock gravitational wave detector data using user-defined population and arbitrary detector sensitivity. The code can, for example, simulate a wide range of binary source populations by specifying parameters such as the local merger rate, distribution functions, and additional keyword arguments, and simulate coloured Gaussian or zero noise using a provided or default power spectrum to represent the detector noise. gwforge can also inject gravitational wave signal(s) into the generated detector data using the previously generated population and a chosen waveform model.

Particle_spray models the position and velocity distributions of newly-escaped stream particles that emerge from globular clusters (GCs). Rather than computing the detailed internal cluster dynamics, which is computationally expensive, the code directly draws tracer particles from these distributions. This algorithm is fast and accurate, and is implemented in a series of notebooks for several galactic dynamics codes, including AGAMA (ascl:1805.008) and galpy (ascl:1411.008).