A Bayesian approach to multi-messenger astronomy: Identification of gravitational-wave host galaxies

TL;DR

This paper introduces a Bayesian framework that integrates host galaxy information into gravitational wave data analysis, improving source localization and parameter estimation for multi-messenger astronomy.

Contribution

It presents a novel Bayesian method to incorporate galaxy data into gravitational wave analysis, enhancing localization and inclination angle estimates.

Findings

Top ten candidate galaxies contain ~50% of the probability of hosting a source.

True host galaxy is in the top ten candidates ~10% of the time.

Including galaxy information improves inclination angle estimation.

Abstract

We present a general framework for incorporating astrophysical information into Bayesian parameter estimation techniques used by gravitational wave data analysis to facilitate multi-messenger astronomy. Since the progenitors of transient gravitational wave events, such as compact binary coalescences, are likely to be associated with a host galaxy, improvements to the source sky location estimates through the use of host galaxy information are explored. To demonstrate how host galaxy properties can be included, we simulate a population of compact binary coalescences and show that for ~8.5% of simulations with in 200Mpc, the top ten most likely galaxies account for a ~50% of the total probability of hosting a gravitational wave source. The true gravitational wave source host galaxy is in the top ten galaxy candidates ~10% of the time. Furthermore, we show that by including host galaxy information, a better estimate of the inclination angle of a compact binary gravitational wave source can be obtained. We also demonstrate the flexibility of our method by incorporating the use of either B or K band into our analysis.