A Complex Systems Approach to Exoplanet Atmospheric Chemistry: New Prospects for Ruling Out the Possibility of Alien Life As We Know It

Abstract

Abstract The near-term ability to characterize terrestrial exoplanet atmospheres may bring us closer to discovering alien life through atmospheric data. However, remotely detectable candidate biosignature gases are subject to false-positive signals because they can also be produced abiotically, raising a critical need to develop methods to determine whether a gas is produced abiotically or not. To distinguish biological, abiotic, and anomalous sources (unidentified as abiotic or biotic) of biosignature gases, we take a complex systems approach implementing chemical reaction network analysis of planetary atmospheres. We simulated 30,000 terrestrial atmospheres, organized in two data sets: Archean-Earth-like worlds and modern-Earth-like worlds. For Archean-Earth-like worlds, we study cases where CH4 is produced abiotically via serpentinization, biologically via methanogenesis, or from anomalous sources. We also simulate modern-Earth-like atmospheres with and without industrial CFC-12. We show how network properties can effectively distinguish scenarios where CH4 is produced from methanogenesis and serpentinization. Network analysis also distinguishes modern-Earth-like atmospheres with CFC-12 from those without it. Using Bayesian analysis, we demonstrate how atmospheric network statistics can provide stronger confidence for ruling out biological explanations compared to gas abundance statistics alone. Our results confirm how a network theoretic approach allows distinguishing hypotheses about biological, abiotic, and anomalous atmospheric drivers and, importantly, allows ruling out life as we know it as a possible explanation. We conclude with a discussion of how further developing statistical inference methods for spectral data that incorporate network properties could significantly strengthen future biosignature detection efforts.