Allesfitter: Flexible Star and Exoplanet Inference from Photometry and Radial Velocity

Abstract

Abstract We present allesfitter, a public and open-source Python software for flexible and robust inference of stars and exoplanets given photometric and radial velocity data. Allesfitter offers a rich selection of orbital and transit/eclipse models, accommodating multiple exoplanets, multistar systems, transit-timing variations, phase curves, stellar variability, starspots, stellar flares, and various systematic noise models, including Gaussian processes. It features both parameter estimation and Bayesian model selection, allowing either a Markov Chain Monte Carlo or Nested Sampling fit to be easily run. For novice users, a graphical user interface allows all input and perform analyses to be specified; for Python users, all modules can be readily imported into any existing script. Allesfitter also produces publication-ready tables, LaTeX commands, and figures. The software is publicly available (https://github.com/MNGuenther/allesfitter), pip-installable (pip install allesfitter), and well documented (www.allesfitter.com). Finally, we demonstrate the software’s capabilities in several examples and provide updates to the literature where possible for Pi Mensae, TOI-216, WASP-18, KOI-1003, and GJ 1243.