Exploring Binary Black Hole Mergers and Host Galaxies with Shark and COMPAS

We explore the connection between the gravitational wave (GW) merger rates of stellar-mass binary black holes (BBHs) and galaxy properties. We do this by generating populations of stars using the binary population synthesis code COMPAS and evolving them in galaxies from the semi-analytic galaxy formation model Shark, to determine the number of mergers occurring in each simulation time-step. We find that metal-rich and massive galaxies with star formation rate (SFR) greater than $1\, {\rm M}_{\odot }\, \rm yr^{-1}$ are 10 times more likely to have GW events compared to younger, less massive, and metal-poor galaxies. Our simulation with the default input parameters predicts a higher local merger rate density compared to the third GW transient catalogue (GWTC-3) prediction from LIGO, VIRGO, and KAGRA, due to short coalescence times, low metallicities, and a high SFR at low redshift in the simulation, which produces more BBHs that merge within the age of the Universe compared to observations. We identify alternate remnant mass models that more accurately reproduce the volumetric rate and provide updated fits to the merger rate as a function of redshift. We then investigate the relative fraction of GW events in our simulation that are in observable host galaxies from upcoming galaxy surveys, determining which of those are ideal for tracing host galaxies with high merger rates. The implications of this work can be utilized for constraining stellar evolution models, better informing follow-up programs, and placing informative priors on host galaxies when measuring cosmological parameters such as the Hubble constant.