Reanalysis of LIGO black-hole coalescences with alternative prior assumptions

TL;DR

This paper reevaluates LIGO's black-hole merger data using alternative Bayesian priors, providing new insights into the intrinsic parameters of detected events and highlighting the impact of prior choices on astrophysical inferences.

Contribution

It offers a critical reanalysis of LIGO black-hole merger data with different priors, expanding on previous work and presenting new marginalized posterior distributions.

Findings

Different prior assumptions affect the inferred parameters.

Additional marginalized posterior distributions are provided.

Reanalysis confirms some previous results while highlighting prior sensitivity.

Abstract

We present a critical reanalysis of the black-hole binary coalescences detected during LIGO's first observing run under different Bayesian prior assumptions. We summarize the main findings of Vitale et al. (2017) and show additional marginalized posterior distributions for some of the binaries' intrinsic parameters.