A Comprehensive Review of Exoplanet Biosignatures

Authors

  • Myasar Ismael Amded

Keywords:

exoplanets; biosignatures; atmospheric spectroscopy; redox disequilibrium; vegetation red edge; temporal variability; Bayesian inference; false positives.

Abstract

       We present a comprehensive synthesis of exoplanet biosignatures spanning atmospheric (gaseous), surface, and temporal indicators, with an emphasis on contextual, multi-observable assessment. Building on rapid advances in exoplanet characterization—particularly high-precision spectroscopy enabled by current and planned facilities—we review candidate gases (e.g., O₂, O₃, CH₄, N₂O) and alternative volatiles (e.g., NH₃, PH₃, DMS, COS, CH₃Cl), outlining their principal biological sources, dominant sinks, and leading abiotic false-positive pathways. We formalize three evaluation pillars—detectability, survivability, and specificity—and highlight the diagnostic value of thermodynamic and kinetic redox disequilibria (e.g., O₂–CH₄ co-occurrence) as integrative metrics. Beyond gases, we survey surface biosignatures such as the vegetation red edge and pigment-linked polarization, and temporal biosignatures including seasonal modulation of atmospheric composition and phase-dependent photometric variability tied to surface phenology. We discuss observational strategies that combine transmission/emission/reflection spectroscopy with rotational mapping and polarimetry to improve robustness against confounding processes (e.g., photochemistry, volcanism, hazes, and clouds). Finally, we outline probabilistic (Bayesian) frameworks that synthesize multiwavelength data and planetary–stellar context to quantify the likelihood that observed signals are life-driven. This review consolidates current understanding, identifies key degeneracies, and maps observational pathways that can transform ambiguous detections into convergent evidence for inhabited worlds.

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Published

2025-09-14

How to Cite

Myasar Ismael Amded. (2025). A Comprehensive Review of Exoplanet Biosignatures. Journal of Computational Analysis and Applications (JoCAAA), 34(8), 369–387. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3666

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