An Open-source Bayesian Atmospheric Radiative Transfer (BART) Code: II. The Transit Radiative-transfer Module and Retrieval of HAT-P-11b

TL;DR

This paper introduces the Transit radiative-transfer module of the open-source BART code, enabling detailed atmospheric characterization of exoplanets like HAT-P-11b through spectral modeling and retrieval.

Contribution

It presents the development and validation of an efficient line-by-line radiative transfer code integrated into BART for exoplanet atmosphere analysis.

Findings

Transit models agree within a few percent with existing models.

Applied BART to HAT-P-11b data, constraining water abundance.

Results indicate an atmosphere enriched in heavy elements.

Abstract

This and companion papers by Harrington et al. and Blecic et al. present the Bayesian Atmospheric Radiative Transfer (BART) code, an open-source, open-development package to characterize extrasolar-planet atmospheres. BART combines a thermochemical equilibrium abundances (TEA), a radiative-transfer (Transit), and a Bayesian statistical (MC3) module to constrain atmospheric temperatures and molecular abundances for given spectroscopic observations. Here, we describe the Transit radiative-transfer package, an efficient line-by-line radiative-transfer C code for one-dimensional atmospheres, developed by P. Rojo and further modified by the UCF exoplanet group. This code produces transmission and hemisphere-integrated emission spectra. Transit handles line-by-line opacities from HITRAN, Partridge \& Schwenke ({\water}), Schwenke (TiO), and Plez (VO); and collision-induced absorption from Borysow, HITRAN, and ExoMol. Transit emission-spectra models agree with models from C. Morley (priv. comm.) within a few percent. We applied BART to the {\Spitzer} and {\Hubble} transit observations of the Neptune-sized planet HAT-P-11b. Our results generally agree with those from previous studies, constraining the {\water} abundance and finding an atmosphere enhanced in heavy elements. Different conclusions start to emerge when we make different assumptions from other studies. The BART source code and documentation are available at https://github.com/exosports/BART.