3.9 Article

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

Journal

PLANETARY SCIENCE JOURNAL
Volume 3, Issue 4, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.3847/PSJ/ac3513

Keywords

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Funding

  1. NASA Planetary Atmospheres grant [NNX12AI69G]
  2. NASA Astrophysics Data Analysis Program [NNX13AF38G]
  3. NASA Exoplanets Research Program [NNX17AB62G]
  4. NASA [80NSSC20K0682]
  5. NASA Earth and Space Science Fellowship [NNX12AL83H]
  6. NASA Exoplanets Research Program grant [NNX17AC03G]
  7. Fulbright Program for Foreign Students
  8. CONICYT project Basal [AFB-170002]

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This paper presents an open-source Bayesian Atmospheric Radiative Transfer (BART) retrieval package, which can estimate and determine the thermal profile and chemical abundances of an atmosphere from observations. The package consists of several components, including a parallel Bayesian sampler, a radiative-transfer model, a code for calculating abundances, and a test suite. The authors invite the community to use and improve these tools and provide an application example using BART for exoplanet data.
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, BARTTest. 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 BARTTest, for any purpose. This paper presents an overview of the code, BARTTest, 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 .

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