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Compressed Parametric and Non-Parametric Approximations to the Gravitational Wave Likelihood
By Vera Delfavero, Richard O'Shaughnessy, Daniel Wysocki, Anjali Yelikar
(Friday, May 27, 2022)

Abstract

Gravitational wave observations of quasicircular compact binary mergers imply complicated posterior measurements of their parameters. Though Gaussian approximations to the pertinent likelihoods have decades of history in the field, the relative generality and practical utility of these approximations hasn't been appreciated, given focus on careful, comprehensive generic Bayesian parameter inference. Building on our previous work in three dimensions, we demonstrate by example that bounded multivariate normal likelihood approximations are accurate, provide useful insight into individual sources and populations, and enable powerful fast calculations which would otherwise be inaccessible for population and low-latency parameter inference. We provide Normal Approximate Likelihood (NAL) fits for each event published in the Gravitational-Wave Transient Catalogs at this https URL, with public code releases in the near future.