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This and companion papers by Harrington et al. 2021, submitted and Cubilloset al. 2021, submitted describe an open-source retrieval framework, BayesianAtmospheric Radiative Transfer (BART), available to the community under thereproducible-research license via https://github.com/exosports/BART . BART is aradiative-transfer code (transit, https://github.com/exosports/transit , Rojo2009, 2009ASPC..420..321R), initialized by the Thermochemical EquilibriumAbundances (TEA, https://github.com/dzesmin/TEA , Blecic et al. 2016,arXiv:1505.06392) code, and driven through the parameter phase space by adifferential-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 itsmodules that can be used separately for other scientific purposes; outline theretrieval analysis flow; present the initialization routines, describing indetail the atmospheric profile generator and the temperature and speciesparameterizations; 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 ofWASP-43b secondary eclipse data obtained from space- and ground-basedobservations. We compare our results with the results from the literature, andinvestigate how the inclusion of additional opacity sources influence thebest-fit model.

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