Modern Earth-like Chemical Disequilibrium Biosignatures Are Challenging To Constrain Through Spectroscopic Retrievals
arXiv:2505.16231 · doi:10.3847/1538-4357/addbd7
Abstract
Robust exoplanet characterization studies are underway, and the community is looking ahead toward developing observational strategies to search for life beyond our solar system. With the development of life detection approaches like searching for atmospheric chemical species indicative of life, chemical disequilibrium has also been proposed as a potentially key signature for life. Chemical disequilibrium can arise from the production of waste gases due to biological processes and can be quantified using a metric known as the available Gibbs free energy. The main goal of this study was to explore the detectability of chemical disequilibrium for a modern Earth-like analog. Atmospheric retrievals coupled to a thermodynamics model were used to determine posterior distributions for the available Gibbs free energy given simulated observations at various noise levels. In reflected light, chemical disequilibrium signals were difficult to detect and limited by the constraints on the CH4 abundance, which was challenging to constrain for a modern Earth case with simulated observations spanning ultraviolet through near-infrared wavelengths with V-band SNRs of 10, 20, and 40. For a modern Earth analog orbiting a late-type M dwarf, we simulated transit observations with the James Webb Space Telescope Mid-Infrared Instrument (MIRI) and found that tight constraints on the available Gibbs free energy can be achieved, but only at extremely low noise on the order of several ppm. This study serves as further proof of concept for remotely inferring chemical disequilibrium biosignatures and should be included in continuing to build life detection strategies for future exoplanet characterization missions.
25 pages, 17 figures. Accepted to ApJ. Accessible figure data: https://doi.org/10.5281/zenodo.15485517 Python Thermodynamics Model: https://github.com/Bellatrix12/Python_Equilibrium_Code.git
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