An open-source Bayesian atmospheric radiative transfer (BART) code: III. Initialization, atmospheric profile generator, post-processing routines, and application to exoplanet WASP-43b

TL;DR

This paper introduces the initialization, atmospheric profile generator, post-processing routines, and application of the open-source Bayesian Atmospheric Radiative Transfer (BART) framework to analyze exoplanet WASP-43b, enhancing retrieval capabilities for atmospheric characterization.

Contribution

It provides detailed descriptions of BART's modules, including atmospheric profile generation and post-processing, and demonstrates its application to real exoplanet data, advancing open-source tools for atmospheric retrieval.

Findings

WASP-43b atmospheric analysis using BART aligns with previous results.

Inclusion of additional opacity sources affects the best-fit models.

The framework's modules can be used independently for various scientific purposes.

Abstract

This and companion papers by Harrington et al. 2021, submitted and Cubillos et al. 2021, submitted describe an open-source retrieval framework, Bayesian Atmospheric Radiative Transfer (BART), available to the community under the reproducible-research license via https://github.com/exosports/BART . BART is a radiative-transfer code (transit, https://github.com/exosports/transit , Rojo 2009, 2009ASPC..420..321R), initialized by the Thermochemical Equilibrium Abundances (TEA, https://github.com/dzesmin/TEA , Blecic et al. 2016, arXiv:1505.06392) code, and driven through the parameter phase space by a differential-evolution Markov-chain Monte Carlo (MC3, https://github.com/pcubillos/mc3 , Cubillos et al. 2017, arXiv:1610.01336) sampler. In this paper we give a brief description of the framework, and its modules that can be used separately for other scientific purposes; outline the retrieval analysis flow; present the initialization routines, describing in detail the atmospheric profile generator and the temperature and species parameterizations; and specify the post-processing routines and outputs, concentrating on the spectrum band integrator, the best-fit model selection, and the contribution functions. We also present an atmospheric analysis of WASP-43b secondary eclipse data obtained from space- and ground-based observations. We compare our results with the results from the literature, and investigate how the inclusion of additional opacity sources influence the best-fit model.