PhD Comprehensive Exam | Dorsa Sadat Hosseini Khajouei, Connection between Binary Black Hole Mergers (BBHs) and astrophysical properties of galaxies

Thursday, August 22, 2024 11:00 am - 12:00 pm EDT (GMT -04:00)

Location

MC 6460

Candidate

Dorsa Sadat Hosseini Khajouei | Applied Mathematics, University of Waterloo

Title

Connection between Binary Black Hole Mergers (BBHs) and astrophysical properties of galaxies

Abstract

Investigating the distribution of dark matter in the universe has always been a crucial task. One approach to achieve this is by examining its astrophysical tracers, which provide not only insight into matter distribution but also hold rich information regarding the astrophysical processes involved in their formation and evolution. We present a comprehensive analysis of the gravitational wave (GW) bias parameter for binary black holes (BBHs). The bias parameter of astrophysical tracers is a useful quantity that connects the underlying distribution of matter in our universe to the astrophysical objects that trace it. The connection between GW sources and their host galaxies is influenced by the formation channels of the GW sources and the characteristics of the parent stars, leading to varying occupation fractions in galaxies based on properties like stellar mass, star formation rate, and metallicity. By examining the spatial clustering of GW sources with galaxies through the GW bias parameter, this relationship can be explored.

To accomplish this, we first generated a mock catalog of BBHs using photometric and spectroscopic galaxy surveys (2MPZ, WISC, and SDSS DR7) based on physically motivated statistical selection functions. These functions compute the probability of a galaxy hosting a BBH merger based on the astrophysical properties of the host galaxy, such as galaxy mass, star formation rate, and metallicity. We then computed the GW bias parameter by estimating the 2D and 3D power spectrum of the generated BBH catalog and compared it with the theoretical power spectrum of galaxies using CAMB.