Population-informed priors in gravitational-wave astronomy

Christopher J. Moore and Davide Gerosa
Phys. Rev. D 104, 083008 – Published 5 October 2021
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Abstract

We describe a Bayesian formalism for analyzing individual gravitational-wave events in light of the rest of an observed population. This analysis reveals how the idea of a “population-informed prior” arises naturally from a suitable marginalization of an underlying hierarchical Bayesian model which consistently accounts for selection effects. Our formalism naturally leads to the presence of “leave-one-out” distributions which include subsets of events. This differs from other approximations, also known as empirical Bayes’ methods, which effectively double count one or more events. We design a double-reweighting postprocessing strategy that uses only existing data products to reconstruct the resulting population-informed posterior distributions. Although the correction we highlight is an important conceptual point, we find it has a limited impact on the current catalog of gravitational-wave events. Our approach further allows us to study, for the first time in the gravitational-wave literature, correlations between the parameters of individual events and those of the population.

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  • Received 5 August 2021
  • Accepted 8 September 2021

DOI:https://doi.org/10.1103/PhysRevD.104.083008

© 2021 American Physical Society

Physics Subject Headings (PhySH)

Gravitation, Cosmology & Astrophysics

Authors & Affiliations

Christopher J. Moore1,* and Davide Gerosa1,2,3

  • 1Institute for Gravitational Wave Astronomy & School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
  • 2Dipartimento di Fisica “G. Occhialini”, Universitá degli Studi di Milano-Bicocca, Piazza della Scienza 3, 20126 Milano, Italy
  • 3INFN, Sezione di Milano-Bicocca, Piazza della Scienza 3, 20126 Milano, Italy

  • *moorecj@bham.ac.uk

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Issue

Vol. 104, Iss. 8 — 15 October 2021

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