pinc ("profiles in cosmology") computes profile likelihoods in cosmology; it can also determine the (boundary-corrected) confidence intervals with the graphical construction. The code uses a simulated annealing scheme and interfaces with MontePython (ascl:1805.027). pinc consists of three short scripts; these automatically set the relevant parameters in MontePython, submit the minimization chains, and analyze the results.

CAMEL (Cosmological Analysis with Minuit Exploration of the Likelihood) performs cosmological parameters estimations using best fits, Monte-Carlo Markov Chains, and profile-likelihoods. Widely used in Planck satellite data analysis, by default it employs CLASS (ascl:1106.020) to compute all relevant cosmological quantities, but any other Boltzmann solver can easily be plugged in.

Procoli extracts profile likelihoods in cosmology. It wraps MontePython (ascl:1805.027), the fast sampler written specifically for CLASS (ascl:1106.020). All likelihoods available for use with MontePython are hence immediately available for use. Procoli is based on a simulated-annealing optimizer to find the global maximum likelihoods value as well as the maximum likelihood points along the profile of any use input parameter.

We develop a Physics-Informed Neural Network (PINN) code to solve the modified Teukolsky equation under realistic astrophysical conditions. The code embeds domain-specific physics—spin-weighted curvature perturbations, quasi-normal mode (QNM) boundary conditions, and attenuation dynamics—directly into the training loss function. Applied to data from the GW190521 event, the model accurately infers complex QNM frequencies (ω = 0.2917 − 0.0389i) and learns an attenuation coefficient α = 0.04096, corresponding to a 14.4% decay rate. The code demonstrates strong predictive performance, reducing mean squared error by 50.3% (MSE = 0.2537 vs. 0.5310) compared to Bayesian baselines, and achieving a positive R² score. It further reveals non-trivial r–t coupling and gravitational memory effects, which standard exponential decay models fail to capture. This PINN-based implementation establishes a computationally efficient and accurate tool for environmental modeling in gravitational wave astrophysics and offers a path forward for black hole spectroscopy beyond vacuum assumptions.

The ExoplanetsSysSim.jl package generates populations of planetary systems, simulates observations of those systems with a transit survey, and facilitates comparisons of simulated and observed catalogs of planetary systems. Critically, ExoplanetsSysSim accounts for intrinsic correlations in the sizes and orbital periods of planets within a planetary system.

LSCS (Lightweight Space Coronagraph Simulator) simulates realistic high-contrast space imaging instruments in their linear regime of small wavefront perturbations about the nominal dark hole. The code can be used for testing high-order wavefront sensing and control as well as post-processing algorithms. It models broadband images with sensor noise, wavefront drift, actuators drift, and residual effects from low-order wavefront sensing, and supports a model of the Roman Space Telescope Hybrid Lyot Coronagraph based on its FALCO (ascl:2304.004, ascl:2304.005) model. The LSCS package provides an example of dark hole maintenance using an Extended Kalman Filter and Electric Field Conjugation.

SysSimExClusters provides a comprehensive forward modelling framework for studying planetary systems in conjunction with ExoplanetsSysSim (ascl:2507.001). It includes several statistical models for describing the intrinsic planetary systems, their architectures, and the correlations within multi-planet systems using the Kepler population of exoplanet candidates.

SysSimPyPlots loads, plots, and visualizes the simulated catalogs generated by ExoplanetsSysSim (ascl:2507.001), a comprehensive forward modeling framework for studying planetary systems based on the Kepler mission. In particular, it is designed to work with the SysSim clustered planetary system models (ascl:2507.003) that characterize the underlying occurrence and intra-system correlations of multi-planet systems. Unlike the SysSim codebase, which is written in Julia, SysSimPyPlot is written almost entirely in Python 3.

SysSimPyMMEN infers the minimum-mass extrasolar nebula (MMEN), a power-law profile for the minimum mass in disk solids required to form the existing exoplanets if they formed in their present locations. Designed to work with the SysSim clustered planetary system models (ascl:2507.001) that characterize the underlying occurrence and intra-system correlations of multi-planet systems, SysSimPyMMEN can also be applied to any other planetary system.

The Opacity Wizard performs easy and fast visualizations of opacity and abundance data for exoplanet and brown dwarf atmospheres. It was designed to be used by observers studying these substellar objects as a way to explore which molecules are most important for a given planet and predict where the absorption features of those molecules will be. Opacity Wizard provides an iPython notebook with widgets for choosing a pressure, temperature, metallicity, and molecule list, and then create plots of the mixing ratios and opacities.

Nii-C implements a framework of automatic parallel tempering Markov Chain Monte Carlo. Parameters ensure an efficient parallel tempering process that is set by a control system during the initial stages of a sampling process. The autotuned parameters consist of two parts: the temperature ladders of all parallel tempering Markov Chains, and the proposal distributions for all model parameters across all parallel tempering chains. Written in C, Nii-C supersedes the Python code Nii (ascl:2111.010). Nii-C is parallelized using the message-passing interface protocol to optimize the efficiency of parallel sampling, which facilitates rapid convergence in the sampling of high-dimensional and multimodal distributions, as well as the expeditious code execution time. The code can be used to trace complex distributions due to its high sampling efficiency and quick execution speed.

Tayph analyzes high-resolution spectroscopic time-series observations of close-in exoplanets using a cross-correlation technique. The tool can be applied to transit observations of hot Jupiters made with echelle spectrographs at optical wavelengths. In particular, it can be applied to pipeline-reduced observations by HARPS, HARPS-N, ESPRESSO, CARMENES and to a certain extent UVES, with minimal interaction required. Tayph works on observations made with other instruments, provided the user provides these according to a specific format, and can also be used in conjunction with Molecfit (ascl:1501.013).

Coniferest implements anomaly detection algorithms and interactive active learning tools. The centerpiece of the package is an Isolation Forest algorithm, which operates by constructing random decision trees. Coniferest also offers two modified versions for active learning: AAD Forest and Pineforest. The AAD Forest modifies the Isolation Forest by reweighting its leaves based on responses from human experts, providing a faster alternative to the ad_examples package. Pineforest employs a filtering algorithm that builds and dismantles trees with each new human-machine iteration step. The Coniferest package provides a user-friendly interface for conducting interactive human-machine sessions; the code has been used for anomaly detection with a particular focus on light-curve data from large time-domain surveys.

show_cube displays the results of reducing, aligning, and combining near-infrared integral field spectroscopy with the Gemini Observatory NIFS (Near-infrared Integral Field Spectrometer) instrument. Image slices are extracted from the raw data frames to make the input datacube. The code site also provides a tarfile containing all the raw NIFS FITS-format files for the observations of high-redshift radio galaxies 3C230, 3C294, and 4C+41.17, the last of which are reported, together with line-strengths using the MAPPINGS III (ascl:1306.008) shock models.

COBRA (Cosmology with Optimally factorized Bases for Rapid Approximation) rapidly computes large-scale structure observables, separating scale dependence from cosmological parameters in the linear matter power spectrum while also minimizing the number of necessary basis terms. This enables direct and efficient computation of derived and nonlinear observables. Moreover, the dependence on cosmological parameters is efficiently approximated using radial basis function interpolation. COBRA opens a new window for efficient computations of higher loop and higher order correlators involving multiple powers of the linear matter power spectra. The resulting factorization can also be utilied in clustering, weak lensing and CMB analyses.

arctic_weather analyzes meteorological data recorded from High Arctic weatherstations (called Inuksuit) deployed on coastal mountains north of 80 degrees on Ellesmere Island Canada from 2006 through 2009, along with clear-sky fractions from horizon-viewing sky-monitoring cameras. The code calculates solar and lunar elevations, and so allows correlation of polar nighttime to the development of prevailing thermal inversion conditions in winter, and statistical comparison to other optical/infrared observatory sites.

Sapphire++ (Simulating astrophysical plasmas and particles with highly relativistic energies in C++) numerically solves the Vlasov–Fokker–Planck equation for astrophysical applications. It employs a numerical algorithm based on a spherical harmonic expansion of the distribution function, expressing the Vlasov–Fokker–Planck equation as a system of partial differential equations governing the evolution of the expansion coefficients. The code uses the discontinuous Galerkin method in conjunction with implicit and explicit time stepping methods to compute these coefficients, providing significant flexibility in its choice of spatial and temporal accuracy.

SAUSERO (Software to AUtomatize in a Simple Environment the Reduction of Osiris+) processes raw science frames to address noise, cosmetic defects, and pixel heterogeneity, preparing them for photometric analysis for OSIRIS+ (Gran Telescopio Canarias). Correcting these artifacts is a critical prerequisite for reliable scientific analysis. The software applies observation-specific reduction steps, ensuring optimized treatment for different data types. Developed with a focus on simplicity and efficiency, SAUSERO streamlines the reduction pipeline, enabling researchers to obtain calibrated data ready for photometric studies.

nGIST (new Galaxy Integral-field Spectroscopy Tool) analyzes modern galaxy integral field spectroscopic (IFS) data. Borne out of the need for a robust but flexible analysis pipeline for an influx of MUSE and other galaxy IFS data, the code is the continuation of the archived GIST pipeline (ascl:1907.025). It improves memory and parallelization management and deals better with longer optical wavelength ranges and sky residuals that are particularly problematic at redder wavelengths (>7000 Angstrom). Performance improvements include memory and parallelization optimization, and smaller and more convenient output files. nGIST can create continuum-only cubes and offers better handling of cube variance and better bias estimation for stellar kinematics, and includes a pPXF-based emission line fitter and an updated version of Mapviewer for a quick-look interface to view results.

Spinifex is a pure Python tooling for ionospheric corrections in radio astronomy, e.g., getting total electron content and rotation measures. The code is in part a re-write of RMextract (ascl:1806.024). All existing features of RMextract have been re-implemented, but spinifex is not directly backwards compatible with RMextract.

Spectool processes astronomical spectral data, offering a collection of common spectral analysis algorithms. The toolkit includes functions for spectral resampling, spectral flattening, radial velocity measurements, spectral convolution broadening, among others. Each function in the package is implemented independently, allowing users to select and utilize the desired features as needed. Spectool's functions have simple and intuitive interfaces, ensuring ease of use for various data sets and analysis tasks.

ysoisochrone handles the isochrones for young stellar objects (YSOs) and uses isochrones to derive the stellar mass and ages. The method uses a Bayesian inference approach. 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. ysoisochrone also enables user-developed evolutionary tracks.

QUIDS is a Python package for generating synthetic Stokes Q and U polarization maps using 3D dust density and Galactic Magnetic Field (GMF) shell data. It integrates polarized emission over log-spaced spherical shells, with polarization angles derived from GMF models such as UF23 or JF12. The goal is to explore whether small-scale structures in the GMF and dust distribution can reconstruct or preserve the large-scale polarization patterns observed across the sky. This package is particularly relevant for modeling and probing how local Galactic features contribute to or interfere with global polarization signals.

Modern large scale cosmological hydrodynamic simulations require robust tools capable of analysing their data outputs in a parallel and efficient manner. We introduce SOAP (Spherical Overdensity and Aperture Processor), a Python package designed to compute halo and galaxy properties from SWIFT simulations after being post-processed with a subhalo finder. SOAP takes a subhalo catalogue as input and calculates a wide array of properties for each object. SOAP offers parallel processing capabilities via mpi4py for efficient handling of large datasets, and allows for consistent property calculation across multiple halo finders. SOAP supports various halo definitions, including spherical overdensities and fixed physical apertures, providing flexibility for diverse observational comparisons. The package is compatible with both dark matter-only and full hydrodynamic simulations, producing HDF5 catalogues that are integrated with the swiftsimio package for seamless unit handling.

MathWAP contains Mathematica notebooks that compute the Fourier power spectrum and bispectrum, including contributions (up to second order) from wide-separation (WS) and relatativistic (GR) efects as well as primoridal non-Gaussianity (PNG). Outputs are stored from Mathematica in .json files in mathematica_expr. The read_mathematica notebook can be used to convert from Mathematica to Python formatting for use by CosmoWAP (ascl:2507.020).

CosmoWAP (Cosmology with Wide-separation, relAtivistic and Primordial non-Gaussian contibutions) analyzes the Fourier power spectra and bispectra with wide-separation, relativistic and primordial non-Gaussian effects in large-scale structure cosmology. The analytical expressions themselves are computed analytically in Mathematica using MathWAP (ascl:2507.019) routines, which can be exported as .py files. CosmoWAP then takes these expressions and implements them for a given cosmology and set of survey parameters.

SPAN (SPectral ANalysis) is a cross-platform graphical user interface (GUI) application for extracting, manipulating, and analyzing astronomical spectra. It is optimized for the study of galaxy spectra across the near-ultraviolet (NUV) to near-infrared (NIR) atmospheric windows.
SPAN extracts 1D spectra from FITS images and datacubes, performs spectral processing (e.g., Doppler correction, continuum modelling, denoising), and supports analyses such as line-strength measurements, stellar and gas kinematics, and stellar population studies, using both built-in routines and the widely adopted pPXF algorithm (ascl:1210.002) for full spectral fitting.
It runs on Windows, Linux, macOS, and Android, and features an intuitive, task-oriented interface. The goal of SPAN is to unify essential tools for modern spectral analysis into a single, user-friendly application that offers a flexible and accessible environment while maintaining scientific accuracy.

PCM-HiPT (Planetary Climate Model for High Pressures and Temperatures) simulates the thermal structure of dense, hot terrestrial exoplanet atmospheres. This 1D line-by-line radiative-convective model uses a high-resolution spectral grid and HITRAN-based absorption data to model radiative energy transfer with high accuracy at elevated pressures and temperatures (>1000 K). PCM-HiPT extends the PCM_LBL model (ascl:2504.003) for early Mars conditions, and modifications allow PCM-HiPT to capture complex atmospheric structures, including detached convective zones and stable lower atmosphere layers driven by shortwave absorption.

spherimatch performs efficient cross-matching and self-matching of astronomical catalogs in spherical coordinates. Designed for use in astrophysics, where data is naturally distributed on the celestial sphere, the package enables fast matching with an algorithmic complexity of O (N log N). It supports Friends-of-Friends (FoF) group identification and duplicate removal in spherical coordinates, and integrates easily with common data processing tools such as pandas.

Capivara implements a spectral-based segmentation method for Integral Field Unit (IFU) data cubes. The code uses hierarchical clustering in the spectral domain, grouping similar spectra to improve the signal-to-noise ratio without compromising astrophysical similarity among regions, and leverages advanced matrix operations via torch for GPU acceleration.

P-CORONA models the intensity and polarization of coronal atomic lines in any given three dimensional (3D) model of the solar corona. It takes into account the scattering of anisotropic radiation as well as the symmetry-breaking effects arising from the influence of magnetic fields, through the Hanle and Zeeman effects, and from non-radial solar wind velocities. The code solves the statistical equilibrium equations for the elements of the atomic density matrix corresponding to the multi-level atomic model under consideration, assuming complete frequency redistribution. The calculations are carried out assuming an optically thin plasma, with the emergent Stokes profiles resulting from the integration of the local emission coefficients along the line-of-sight in the chosen 3D coronal model. P-CORONA incorporates HDF5 input/output functionality and includes a graphical user interface.

EXP performs and analyzes N-body simulations using biorthogonal and orthogonal expansions. The package also supports time series analysis of expansion coefficients using multivariate Singular Spectrum Analysis (mSSA) to discover new dynamical correlations, separate signal from noise, and visualize these in two- and three-dimensional renderings. EXP's object-oriented design enforces minimal consistency while retaining flexibility.

HYDRAD (HYDrodynamics and RADiation) computes solutions to field-aligned hydrodynamic equations in coronal loops. The code models a broad variety of phenomena, including multi-species plasma confined to full-length, magnetic flux tubes of arbitrary geometrical and cross-section variation in the field-aligned direction; solar flares driven by non-thermal electrons3 and Alfven waves4, and the non-thermal equilibrium response of the chromosphere; and coronal rain formed by condensations in thermal non-equilibrium where the adaptive grid is required to fully resolve and track multiple steep transition regions. HYDRAD also models ultracold, strongly coupled laboratory plasmas composed of weakly-ionized strontium. The code, written in C++, is modular in its structure; new capabilities can be added in a relatively straightforward way and handled robustly by the numerical scheme. HYDRAD is also intended to be fairly undemanding of computational resources, though its needs do depend strongly on the particular nature of each model run.

SPIBACK (SPIral arms & Bar bACKward integrations) generates Milky Way models through the backward integration method. The code allows users to plot the 2D local velocity space distribution at the Sun's position, as well as median Galactocentric radial velocity maps across the area of the Galactic disk probed with Gaia DR3. This can be done for different bar and spiral arms parameters. The parameters are set by default to be those of the "fiducial model" and can be adjusted as needed.

torchmfbd carries out multi-object multi-frame blind deconvolution (MOMFBD) of point-like or extended objects, and is especially tailored to solar images. The code is built on PyTorch and provides a high-level interface for adding observations, defining phase diversity channels, and adding regularization. It can deal with spatially variant PSFs either by mosaicking the images or by defining a spatially variant PSF. torchmfbd supports smooth solutions and solutions based on the ℓ 1 penalization of the isotropic undecimated wavelet transform of the object, and regularizations are easily extendable. The code also includes an API and a configuration file.

PIRATES (Polarimetric Image Reconstruction AI for Tracing Evolved Structures) uses machine learning to perform image reconstruction. It uses MCFOST (ascl:2207.023) to generate models, then uses those models to build, train, iteratively fit, and evaluate PIRATES performance.

DPMhalo (Descriptive Parametric Model) generates profiles of gaseous halos (pressure, electron density, and metallicity) as functions of radius, halo mass, and redshift. The code assumes spherically symmetric, volume-filling warm/hot gas, and enables mock observations of the circumgalactic medium (CGM), group halos, and clusters across a number of wavebands including X-ray, sub-millimeter/millimeter, radio, and ultraviolet (UV).

STELA Toolkit is a fully documented Python package for interpolating gappy/irregular, noisy light curves using Gaussian Processes, enabling the computation of a wide range of time-domain and frequency-domain data products. STELA supports standard Fourier frequency-resolved products such as power spectra, cross spectra, lag spectra, and coherence, as well as lags via the Cross-Correlation Function (CCF), interpolated with GPs or traditional linear interpolation.

FRion computes and applies corrections for the effects of Faraday rotation by the Earth's ionosphere in radio polarization data. Other ionospheric Faraday rotation codes can compute the predicted Faraday rotation measure as a function of time and direction, and in some cases apply the correction directly to visibilities. FRion has been made to tackle the case where direct correction in visibilities is not possible and correction must occur post-imaging. FRion computes the time-averaged Faraday rotation across the duration of an observation, which should serve as a reasonable approximation for the effect of the ionosphere in radio interferometer images. For the ionosphere Faraday rotation calculations we use the external package RMextract (ascl:1806.024). FRion can further apply the correction to Stokes Q and U cubes to remove the effects of the ionosphere.