Coupling magma-ocean and atmospheres in spectral retrievals of sub-Neptunes

TL;DR

This paper introduces MELTYQ, a novel Bayesian retrieval framework that links sub-Neptune atmospheric spectra to underlying magma ocean properties, enabling insights into their interior composition and redox state.

Contribution

MELTYQ is the first coupled magma-atmosphere spectral retrieval model that integrates equilibrium chemistry with Bayesian analysis for sub-Neptune planets.

Findings

MELTYQ can constrain magma redox state and volatile content with good observational data.

Application to JWST spectra of K2-18 b and TOI-270 d shows the model's capability to reproduce observed spectra.

Current limitations include the need for more flexible retrieval approaches and model assumptions.

Abstract

Recent high-precision atmospheric observations with JWST is enabling detailed characterization of sub-Neptune atmospheres and motivating efforts to understand and constrain their interiors. Theoretical studies suggest that sub-Neptunes possibly host hydrogen-dominated atmospheres that are chemically coupled with an underlying magma ocean. However, a quantitative retrieval framework directly linking atmospheric spectra to magma ocean properties has yet to be established. Here we introduce MELTYQ, a coupled magma-atmosphere retrieval framework that links transmission spectra to the oxidation state and volatile inventory of underlying magma oceans. MELTYQ combines a magma-atmosphere equilibrium model, which includes the solubility of H-/O-/C-/N-bearing species in the melt and redox reactions, with a Bayesian spectral retrieval scheme. Using simulated retrieval tests, we validate the approach and show that magma redox state and volatile content can be constrained under favorable observational conditions. As a proof of concept, we apply MELTYQ to JWST transmission spectra of the benchmark sub-Neptunes K2-18 b and TOI-270 d. We find that coupled magma-atmosphere retrievals are generally capable of reproducing the observed spectra of these planets. However, we identify several key limitations in the current framework. Specifically: more flexible free-retrieval approaches remain statistically preferred; the CO/CO$_2$ absorption feature near 4.5 $\mu$m for TOI-270 d is not fully captured; and a number of underlying model assumptions may not be strictly valid. Nevertheless, embedding coupled magma-atmosphere models directly within Bayesian retrievals enables quantitative assessment of degeneracies and sensitivities, establishing a pathway for directly connecting atmospheric spectra to magma composition in this underexplored exoplanet regime.