paper

Identifying Host Galaxies of Binary Black Hole Mergers with Next-Generation Gravitational Wave Detector Networks

arXiv:2602.08459 · doi:10.1093/mnras/stag1079

Abstract

Identifying the host galaxy of a binary black hole (BBH) merger detected via gravitational waves (GWs) remains a challenge due to the absence of electromagnetic counterparts and the large localization volumes produced by current-generation detectors. A confident host association would provide stellar population properties to constrain BBH formation channels and enable measurements of cosmological parameters such as the Hubble constant, H0. We simulate BBH mergers in nearby (z<0.25) host galaxies to evaluate the feasibility of host identification with future GW detector networks, including configurations with the planned LIGO-India detector and third-generation detectors such as the Einstein Telescope (ET) and Cosmic Explorer (CE). We construct two injection grids to explore variations in BBH mass, distance, and directional sensitivity, and infer localization volumes using the Fisher Information Matrix (FIM)-based parameter estimation implemented through BILBY. To assess the prospects for unique host identification, we introduce a set of diagnostics: theoretical comoving volume thresholds for galaxies of a given stellar mass, derived from galaxy stellar mass functions, a metallicity-based volume threshold motivated by progenitor environment models, stellar mass fractions to quantify candidate host prominence, and the probability of chance alignment (p_c). These metrics provide ways to evaluate host associations and constrain BBH formation channels. We find that future networks that include ET and CE localize BBH mergers to volumes smaller than those theoretical thresholds, implying potentially unique host identification, out to ~1000 Mpc at a rate of ~100 yr^{-1}. While associations for individual events may remain uncertain, our framework is well-suited to population-level analyses, enabling constraints on BBH formation scenarios in the era of next-generation GW detector networks.

19 pages, 12 figures; Submitted to MNRAS;

References in corpus (173)