Parameter estimation on gravitational waves from multiple coalescing binaries

TL;DR

This paper presents a Bayesian method for aggregating parameter estimates from multiple gravitational wave events to infer properties of the overall binary coalescence population, aiding astrophysical studies.

Contribution

It introduces a robust Bayesian framework for combining multiple event data into a population parameter distribution, suitable for rapid post-processing.

Findings

Framework effectively aggregates multiple event data

Enables rapid population inference

Supports astrophysical parameter estimation

Abstract

Future ground-based and space-borne interferometric gravitational-wave detectors may capture between tens and thousands of binary coalescence events per year. There is a significant and growing body of work on the estimation of astrophysically relevant parameters, such as masses and spins, from the gravitational-wave signature of a single event. This paper introduces a robust Bayesian framework for combining the parameter estimates for multiple events into a parameter distribution of the underlying event population. The framework can be readily deployed as a rapid post-processing tool.