get_emlines predicts logarithmic nebular emission-line luminosities in galaxies from their star formation rates and gas-phase metallicities. The code assigns an ionization parameter based on a power-law relation with metallicity and performs bilinear interpolation over ionization parameter and metallicity using a grid of photoionization models, with electron density held fixed. It uses the input star formation rate to calculate H-alpha luminosity, which is then used to scale the predicted fluxes of other emission lines to galaxy-wide luminosities. The code calculates optical, ultraviolet, and far-infrared emission lines, including H-alpha, H-beta, Ly-alpha, [O II], [O III], [N II], and [C II]. Users can modify the slope and normalization of the ionization parameter–metallicity relation and calculate line luminosities for individual galaxies or arrays of galaxies.

pyEDITH (Exposure Direct Imaging Timer for HWO) calculates wavelength-dependent exposure times and signal-to-noise ratios (S/N) for simulated coronagraphic observations of exoplanets with NASA's proposed Habitable Worlds Observatory (HWO). The Python package incorporates astrophysical and instrumental noise models, telescope and instrument specifications, and user-defined target parameters to simulate direct imaging observations. It supports imaging and integral field spectroscopy (IFS) modes and can calculate exposure times for specified S/N values or determine S/N for given exposure times. pyEDITH enables comparisons of different HWO instrument configurations and their effects on exoplanet detection and characterization. It provides command-line and Python interfaces for configuring and running calculations.

AVICA (Automated VLBI pipeline in CASA) calibrates archival Very Long Baseline Array (VLBA) observations using the Common Astronomy Software Applications (CASA) package (ascl:1107.013). Built on the rPICARD (ascl:1905.015) calibration framework, it checks FITS-IDI data for known problems, applies corrections where possible, imports the data into CASA, and applies available station flag files. AVICA automatically selects calibrators and reference antennas by evaluating fringe signal-to-noise ratios across scans and baselines, then executes the calibration workflow. It uses ALFRD (ascl:2610.009) to coordinate pipeline execution, track progress, record results, and support resuming interrupted or failed processing. The pipeline supports archival VLBA observations across multiple frequency bands and uses MPI parallelization for processing large datasets.

ALFRD (Automated Logical Framework for executing Dynamic scripts) manages the execution and monitoring of command-line processing pipelines across multiple targets. It uses YAML configuration files to define pipeline steps and CSV-based execution plans to track progress and select tasks for processing. The Python package records execution status, failures, logs, runtimes, and processing history, and supports resuming incomplete workflows. ALFRD provides a local web interface for monitoring and managing pipeline execution. Developed for radio astronomy data processing with AVICA (ascl:2610.010), it can also be used with other command-line pipelines.

weaklens_pipeline computes galaxy–galaxy weak lensing signals, including the excess surface mass density (ΔΣ) and average tangential shear around lens galaxies, given a catalog of lens and source galaxies. The pipeline preprocesses galaxy catalogs and identifies lens–source pairs within specified radial bins using a tree-based search. It supports source selection using photometric redshift estimates or full redshift probability distributions, with configurable selection criteria and corrections. Implemented in C++ with Python bindings and wrappers, weaklens_pipeline uses a memory-efficient approach to identifying lens–source pairs that avoids requiring all source redshift probability distributions to be held in memory simultaneously.

stiffGWpy computes the expansion history of the extended ΛCDM model with the stochastic gravitational-wave background (SGWB) from inflation and an additional stiff component. The presence of a possible early stiff era may cause amplification of the primordial SGWB relative to that in the base ΛCDM model. For given cosmological parameters, the coupled dynamical system of the Friedmann equation and the tensor wave equation is solved iteratively, which accounts for the backreaction from the stiff-amplified SGWB on the background expansion history.

astro-mmdc provides a Python interface to the Markarian Multiwavelength Data Center (MMDC) for retrieving, analyzing, and modeling multiwavelength observations of blazars and other astronomical sources. It accesses time-resolved spectral energy distributions (SEDs) and light curves assembled from archival catalogs and observations from instruments including Swift UVOT/XRT, NuSTAR, and Fermi-LAT. The package supports positional searches, data filtering, unit conversion, CSV export, and visualization of SEDs. It enables on-demand Swift UVOT photometry and XRT spectral analysis through the MADAM pipeline. astro-mmdc also provides access to synchrotron self-Compton (SSC), external inverse Compton (EIC), and lepto-hadronic emission modeling and fitting. Results are returned as Python objects, and data retrieval, analysis, and modeling tasks can be submitted asynchronously.

GPUPhot performs GPU-accelerated photometry and astrometry on astronomical CCD and scientific CMOS images. The Python framework uses CuPy for background estimation, source detection, point spread function (PSF) modeling, and aperture photometry, with CPU- or GPU-based catalog crossmatching and photometric and astrometric calibration. It integrates with astrometry.net (ascl:1208.001) for World Coordinate System (WCS) calibration and uses Celery to distribute image processing tasks across CPUs, GPUs, and multiple machines. GPUPhot monitors GPU memory usage and provides a spatial-binning fallback to accommodate GPUs with different memory capacities. It supports instrument-specific configurations, stores photometric and astrometric results in a PostgreSQL database, and is designed for automated image reduction at survey cadence in robotic telescope facilities.

py-sphviewer2 visualizes Smoothed Particle Hydrodynamics (SPH) simulations by projecting particle-based fields into two-dimensional images. A complete reimplementation of its predecessor py-sphviewer (ascl:1712.003), py-sphviewer2 uses a hierarchy of nested grids to perform projections with computational complexity independent of the final image resolution. The library combines a multithreaded C++ backend with a Python interface and supports mass-conserving projections, periodic boundary conditions, zooming, cropping, and three-dimensional rotations. py-sphviewer2 includes a parallel k-nearest neighbor algorithm for calculating particle smoothing lengths from coordinates. Projected multiscale grid hierarchies can be saved in HDF5 format for subsequent visualization without repeating the particle projection.

OpenGadget3 simulates the formation and evolution of cosmic structures, modeling the gravitational and hydrodynamical processes that govern matter in cosmological simulations. An enhanced version of the Gadget-2/3 code family, it combines a Barnes–Hut oct-tree and Particle-Mesh method for gravitational calculations with a choice of Smoothed Particle Hydrodynamics or Meshless Finite Mass solvers for gas dynamics. The code includes physical modules for gas cooling, star formation and feedback, chemical enrichment, black hole evolution, magnetohydrodynamics, and dark matter physics. OpenGadget3 supports hybrid MPI/OpenMP parallelization with GPU offloading through OpenACC and OpenMP, along with mixed-precision calculations. It provides parameter management, configuration checks, and reporting of simulation settings and active physics modules to support reproducibility.