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Bayesian approach to SETI
Edited by Neta A. Bahcall, Princeton University, Princeton, NJ, and approved August 31, 2018 (received for review May 20, 2018)

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Significance
Ongoing and future initiatives in the search for extraterrestrial intelligence (SETI) will explore the Galaxy on an unprecedented scale to find evidence of communicating civilizations beyond Earth. Here, we construct a Bayesian formulation of SETI to infer the posterior probability of the mean number of radio signals crossing Earth, given a positive or a null outcome of all-sky searches for nonnatural radio emissions. We show that not detecting signals within
Abstract
The search for technosignatures from hypothetical galactic civilizations is going through a new phase of intense activity. For the first time, a significant fraction of the vast search space is expected to be sampled in the foreseeable future, potentially bringing informative data about the abundance of detectable extraterrestrial civilizations or the lack thereof. Starting from the current state of ignorance about the galactic population of nonnatural electromagnetic signals, we formulate a Bayesian statistical model to infer the mean number of radio signals crossing Earth, assuming either nondetection or the detection of signals in future surveys of the Galaxy. Under fairly noninformative priors, we find that not detecting signals within about 1 kly from Earth, while suggesting the lack of galactic emitters or at best the scarcity thereof, is nonetheless still consistent with a probability exceeding 10% that typically over
Footnotes
- ↵1To whom correspondence may be addressed. Email: claudio.grimaldi{at}epfl.ch or geoff.w.marcy{at}gmail.com.
Author contributions: C.G. designed research; C.G. developed the theory; C.G. and G.W.M. performed research; C.G. and G.W.M. analyzed data; and C.G. and G.W.M. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1808578115/-/DCSupplemental.
Published under the PNAS license.
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