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

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, multi-star systems, transit-timing variations, phase curves, stellar variability, star spots, stellar flares, and various systematic noise models including Gaussian Processes. It features both parameter estimation and Bayesian model selection, allowing to easily run either a Markov Chain Monte Carlo (MCMC) or Nested Sampling fit. For novice users, a graphical user interface allows to specify all input and perform analyses; for python users, all modules can be readily imported in any existing scripts. 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 on several examples and provide updates to the literature where possible for Pi Mensae, TOI-216, WASP-18, KOI-1003 and GJ 1243.

36 pages, 15 figures, 9 tables, submitted to AAS journals

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Cited by in corpus (4)

• NGTS-19b : A high mass transiting brown dwarf in a 17-day eccentric orbit
• NGTS 15b, 16b, 17b and 18b: four hot Jupiters from the Next Generation Transit Survey
• PACMAN: A pipeline to reduce and analyze Hubble Wide Field Camera 3 IR Grism data
• A sub-Neptune transiting the young field star HD 18599 at 40 pc