Identifying the Host Galaxy of Gravitational Wave Signals

TL;DR

This paper introduces a new statistical method to identify the most likely host galaxy of gravitational wave signals, enhancing the efficiency of follow-up electromagnetic observations.

Contribution

It proposes a novel statistic that ranks potential host galaxies based on position, distance, and luminosity, tested through simulations for neutron star and black hole mergers.

Findings

Correctly identifies true host ~20-50% of the time with a single galaxy.

Increases identification probability to ~50-80% with five narrow-field images.

Achieves ~70-90% success rate when imaging groups of galaxies with large field-of-view telescopes.

Abstract

One of the goals of the current LIGO-GEO-Virgo science run is to identify transient gravitational wave (GW) signals in near real time to allow follow-up electromagnetic (EM) observations. An EM counterpart could increase the confidence of the GW detection and provide insight into the nature of the source. Current GW-EM campaigns target potential host galaxies based on overlap with the GW sky error box. We propose a new statistic to identify the most likely host galaxy, ranking galaxies based on their position, distance, and luminosity. We test our statistic with Monte Carlo simulations of GWs produced by coalescing binaries of neutron stars (NS) and black holes (BH), one of the most promising sources for ground-based GW detectors. Considering signals accessible to current detectors, we find that when imaging a single galaxy, our statistic correctly identifies the true host ~20% to ~50% of the time, depending on the masses of the binary components. With five narrow-field images the probability of imaging the true host increases to ~50% to ~80%. When collectively imaging groups of galaxies using large field-of-view telescopes, the probability improves to ~30% to ~60% for a single image and to ~70% to ~90% for five images. For the advanced generation of detectors (c. 2015+), and considering binaries within 100 Mpc (the reach of the galaxy catalogue used), the probability is ~40% for one narrow-field image, ~75% for five narrow-field images, ~65% for one wide-field image, and ~95% for five wide-field images, irrespective of binary type.