AstroQ optimizes the allocation and ordering of astronomical observations for the KPF Community Cadence (KPF-CC) program. The autoscheduling framework solves two related scheduling problems: determining which targets should be observed on which nights within a semester and distributing instrument nights optimally across the observing queue. The software reads target request information and configuration files, then computes observation schedules using optimization routines that rely on the Gurobi solver. AstroQ integrates with a Traveling Telescope Problem (TTP) solver to determine the optimal sequence of observations within a night by minimizing slew paths between targets. Example configurations and command-line tools allow users to generate schedules from input request files and analyze resulting observation plans.

ethraid characterizes long-period bound companions using partial-orbit data by analyzing RV trends and curvature to constrain the properties, including mass and separation, of distant giant planets and other long-period companions. It jointly models radial velocity, astrometric, and direct imaging measurements in a Bayesian framework, using Doppler, astrometric, and imaging constraints to derive posterior distributions on companion parameters. A command-line interface runs orbit fits, generates plots, and reports 95% confidence intervals in a single step. The code returns raw and processed posterior samples and up to three plots: a joint two-dimensional posterior in mass–separation space, and marginalized one-dimensional PDFs and CDFs. ethraid includes fitting tools, with modules for astrometry fitting and radial-velocity fitting.

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.

SMINT (Structure Model INTerpolator) obtains posterior distributions on the H/He or H2O mass fraction of a planet; its interface is user-friendly. The parameters of the planet of interest are input with specifications on the priors that should be used. SMINT returns publication-ready plots presenting the joint parameters constraints obtained from interpolating the interior models grid of interest as well as confidence intervals for each parameter.

The EDI (Exoplanet Detection Identifier) Vetter Unplugged software identifies false positive transit signals using Transit Least Squares (TLS) information and has been simplified from the full EDI-Vetter algorithm (ascl:2202.009) for easy implementation with the TLS output.

EDI (Exoplanet Detection Identifier) Vetter identifies false positive transit signal in the K2 data set. It combines the functionalities of Terra (ascl:2202.008) and RoboVetter (ascl:2012.006) and is optimized to test single transiting planet signals. An easily implemented suite of vetting metrics built to run alongside TLS of EDI Vetter, EDI-Vetter Unplugged (ascl:2202.010), is also available.

TERRA (Transiting Exoearth Robust Reduction Algorithm) identifies and removes instrumental noise in Kepler photometry. This transit detection code is optimized to detect small planets around photometrically quiet stars. TERRA calculates photometry in the time domain, combs the calibrated photometry for periodic, box-shaped signals, fits promising signals, and rejects signals inconsistent with exoplanet transits.

RadVel models Keplerian orbits in radial velocity (RV) time series. The code is written in Python with a fast Kepler's equation solver written in C. It provides a framework for fitting RVs using maximum a posteriori optimization and computing robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel can perform Bayesian model comparison and produces publication quality plots and LaTeX tables.