Inferring binary black holes stellar progenitors with gravitational wave sources
Simone Mastrogiovanni, Astrid Lamberts, Rahul Srinivasan, Tristan, Bruel, Nelson Christensen

TL;DR
This paper reviews how synthetic binary catalogs can be used to infer stellar progenitor properties of binary black holes from gravitational wave data, emphasizing methods, implementation, and case studies for the O4 observing run.
Contribution
It introduces a method to match phenomenological merger rate reconstructions with synthetic catalogs and demonstrates its application to infer progenitor characteristics from gravitational wave observations.
Findings
Relative efficiency in compact object production affects progenitor inference.
Simulation of LIGO/Virgo O4 data enables case studies on progenitor parameters.
Synthetic catalogs facilitate linking progenitor properties to binary black hole observations.
Abstract
With its last observing run, the LIGO, Virgo, and KAGRA collaboration has detected almost one hundred gravitational waves from compact binary coalescences. A common approach to studying the population properties of the observed binaries is to use phenomenological models to describe the spin, mass, and redshift distributions. More recently, with the aim of providing a clearer link to astrophysical processes forming the observed compact binaries coalescences, several authors have proposed to employ synthetic catalogs for population studies. In this paper, we review how to employ and interpret synthetic binary catalogs for gravitational-wave progenitors studies. We describe how to build multi-channel merger rates and describe their associated probabilities focusing on stellar progenitor properties. We introduce a method to quantify the match between the phenomenological reconstruction of…
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