An Open-source Bayesian Atmospheric Radiative Transfer (BART) Code. I. Design, Tests, and Application to Exoplanet HD 189733b

• Published in: The planetary science journal Vol. 3; no. 4; pp. 80 - 110
• Main Authors: Harrington, Joseph, Himes, Michael D., Cubillos, Patricio E., Blecic, Jasmina, Rojo, Patricio M., Challener, Ryan C., Lust, Nate B., Bowman, M. Oliver, Blumenthal, Sarah D., Dobbs-Dixon, Ian, Foster, Andrew S. D., Foster, Austin J., Green, M. R., Loredo, Thomas J., McIntyre, Kathleen J., Stemm, Madison M., Wright, David C.
• Format: Journal Article
• Language: English
• Published: The American Astronomical Society 01.04.2022
• Subjects: Astrostatistics techniques; Exoplanet atmospheric composition; Exoplanet systems; Open source software; Planetary atmospheres; Uncertainty bounds
• ISSN: 2632-3338; 2632-3338
• DOI: 10.3847/PSJ/ac3513

We present the open-source Bayesian Atmospheric Radiative Transfer (BART) retrieval package, which produces estimates and uncertainties for an atmosphere’s thermal profile and chemical abundances from observations. Several BART components are also stand-alone packages, including the parallel Multi-Core Markov-chain Monte Carlo (MC3), which implements several Bayesian samplers; a line-by-line radiative-transfer model, transit ; a code that calculates Thermochemical Equilibrium Abundances (TEA), and a test suite for verifying radiative-transfer and retrieval codes, BARTT est . The codes are in Python and C. BART and TEA are under a Reproducible Research (RR) license, which requires reviewed-paper authors to publish a compendium of all inputs, codes, and outputs supporting the paper’s scientific claims. BART and TEA produce the compendium’s content. Otherwise, these codes are under permissive open-source terms, as are MC3 and BARTT est , for any purpose. This paper presents an overview of the code, BARTT est , and an application to eclipse data for exoplanet HD 189733b. Appendices address RR methodology for accelerating science, a reporting checklist for retrieval papers, the spectral resolution required for synthetic tests, and a derivation of the effective sample size required to estimate any Bayesian posterior distribution to a given precision, which determines how many iterations to run. Paper II, by Cubillos et al., presents the underlying radiative-transfer scheme and an application to transit data for exoplanet HAT-P-11b. Paper III, by Blecic et al., discusses the initialization and post-processing routines, with an application to eclipse data for exoplanet WASP-43b. We invite the community to use and improve BART and its components at http://GitHub.com/ExOSPORTS/BART/ .