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Technosignatures: Frameworks for Their Assessment

Manasvi Lingam, Jacob Haqq‐Misra, Jason T. Wright, Macy Huston, Adam Frank, Ravi Kopparapu

2023The Astrophysical Journal13 citationsDOIOpen Access PDF

Abstract

Abstract In view of the promising advancements in technosignature science, the question of what constitutes a robust technosignature is rendered crucial. In this paper, we first delineate a Bayesian framework for ascertaining the reliability of potential technosignatures by availing ourselves of recent cognate research in biosignatures. We demonstrate that ideal technosignatures must not only have low risk of stemming from false positives but also evince sufficiently high prior probability of existence. Given the inherent difficulties with estimating the latter, we highlight a few alternative metrics drawn from diagnostic testing such as the Youden index that bypass the requirement of explicitly calculating the prior. We apply the models (Bayesian or otherwise) to a select few technosignature candidates and show that artificial electromagnetic signals, chlorofluorocarbons, and artifacts perform well on this front. While these results may be along expected lines, we suggest that identifying and developing suitable approaches to further evaluate technosignature candidates is of considerable importance.

Topics & Concepts

Bayesian probabilityFalse positive paradoxYouden's J statisticReliability (semiconductor)Machine learningFalse positives and false negativesPrior probabilityArtificial intelligencePhysicsComputer scienceRisk analysis (engineering)Receiver operating characteristicMedicineQuantum mechanicsPower (physics)Marine animal studies overviewIchthyology and Marine BiologyGeochemistry and Geologic Mapping
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