Impact of Bayesian prior on the characterization of binary black hole coalescences

TL;DR

This paper demonstrates how different prior assumptions in Bayesian analysis significantly influence the inferred parameters of binary black hole mergers from gravitational-wave data, affecting physical interpretations.

Contribution

It systematically analyzes the impact of alternative, astrophysically motivated priors on the inference of black hole parameters from LIGO data, highlighting the importance of prior choice.

Findings

Prior variations cause ~10% changes in spin parameter credible intervals.

Using stellar-mass function priors yields tighter mass constraints.

No evidence found for black holes below 5 solar masses in the data.

Abstract

In a regime where data are only mildly informative, prior choices can play a significant role in Bayesian statistical inference, potentially affecting the inferred physics. We show this is indeed the case for some of the parameters inferred from current gravitational-wave measurements of binary black hole coalescences. We reanalyze the first detections performed by the twin LIGO interferometers using alternative (and astrophysically motivated) prior assumptions. We find different prior distributions can introduce deviations in the resulting posteriors that impact the physical interpretation of these systems. For instance, (i) limits on the $90\%$ credible interval on the effective black hole spin $\chi_{\rm eff}$ are subject to variations of $\sim 10\%$ if a prior with black hole spins mostly aligned to the binary's angular momentum is considered instead of the standard choice of isotropic spin directions, and (ii) under priors motivated by the initial stellar mass function, we infer tighter constraints on the black hole masses, and in particular, we find no support for any of the inferred masses within the putative mass gap $M \lesssim 5 M_\odot$.