Atmospheric Retrieval for Super-Earths: Uniquely Constraining the Atmospheric Composition with Transmission Spectroscopy
Bjoern Benneke, Sara Seager

TL;DR
This paper introduces a Bayesian retrieval method to analyze transmission spectra of super-Earth exoplanets, enabling the determination of atmospheric composition, surface or cloud-top pressure, and mean molecular mass with specific spectral features.
Contribution
The paper presents a novel atmospheric retrieval approach applicable to general exoplanet atmospheres, including clouds and unknown main constituents, using MCMC and a new parameterization.
Findings
Unique constraints on atmospheric mixing ratios are possible with sufficient spectral data.
Surface or cloud-top pressure can be inferred if a cloud deck is present.
Rayleigh scattering signatures are crucial for distinguishing atmospheric compositions.
Abstract
We present a retrieval method based on Bayesian analysis to infer the atmospheric compositions and surface or cloud-top pressures from transmission spectra of exoplanets with general compositions. In this study, we identify what can unambiguously be determined about the atmospheres of exoplanets from their transmission spectra by applying the retrieval method to synthetic observations of the super-Earth GJ 1214b. Our approach to infer constraints on atmospheric parameters is to compute their joint and marginal posterior probability distributions using the MCMC technique in a parallel tempering scheme. A new atmospheric parameterization is introduced that is applicable to general atmospheres in which the main constituent is not known a priori and clouds may be present. Our main finding is that a unique constraint of the mixing ratios of the absorbers and up to two spectrally inactive…
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