Uniform Reinterpretation of Rocky Exoplanet Secondary Eclipse Observations and the Impact of Stellar and Orbital Uncertainties

TL;DR

This paper presents a framework to incorporate stellar and orbital uncertainties into the modeling of rocky exoplanet secondary eclipse data, highlighting their impact on constraining planetary atmospheres.

Contribution

It introduces a novel method to account for astrophysical uncertainties in eclipse modeling, improving the robustness of exoplanet surface and atmospheric analysis.

Findings

Uncertainty in eclipse depth can be as large as observational errors.

Model uncertainty correlates with errors in system parameters.

Mitigating uncertainties is essential for accurate exoplanet composition analysis.

Abstract

Secondary eclipse observations are a powerful way to investigate whether or not a rocky exoplanet hosts an atmosphere, as an atmospheric presence would transport heat to the nightside and render the dayside colder than anticipated. The interpretation of the secondary eclipse observations relies, however, on models based on imperfect knowledge of the host star properties and the system parameters. Any uncertainties in such astrophysical variables will propagate into both atmospheric and bare-rock models, potentially leading to poorly constrained results and erroneous conclusions. In this work, we introduce a framework to efficiently account for the stellar and orbital uncertainties when modeling the emission spectra of rocky exoplanets, and demonstrate its use by reanalyzing the current suite of rocky exoplanets with published eclipse observations. Our analysis reveals notable uncertainty in the predicted eclipse depth even for a simple dark ($A_{\mathrm{B}}=0$) bare rock as a result of the finite precision of the system's parameters and treatment of the host star's flux. In some cases, the model uncertainty is comparable to the observational uncertainty, further complicating our capability to constrain an atmospheric presence from secondary-eclipse observations. From our modeling schematic, we derive a linear correlation between the model uncertainty and the error in $R_{\mathrm{p}}/R_{\mathrm{*}}$, $ a_{\mathrm{p}}/R_{\mathrm{*}}$, and $T_{\mathrm{*}}$, therefore enabling a more robust compositional analysis in future studies. The model uncertainty serves as a fundamental precision limit to surface analyses, and must be mitigated to strongly constrain the composition of exoplanets in future eclipse observations.