Gravitational-wave population studies have become more important in gravitational-wave
astronomy because of the rapid growth of the observed catalog. In recent studies, emulators
based on different machine learning techniques are used to emulate the outcomes of the
population synthesis simulation quickly. In this study, we benchmark the performance of two
emulators that learn the truncated power-law phenomenological model by using Gaussian
process regression and normalizing flows technique to see which one is a more capable�…

The recent release of the second Gravitational-Wave Transient Catalog (GWTC-2) has
increased significantly the number of known events, enabling unprecedented constraints on
formation models of compact binaries. By analyzing the newest catalogue of gravitational-
wave events with a deep-learning enhanced hierarchical Bayesian modelling framework
and population synthesis simulations, we present constraints on astrophysical quantities for
various black-hole binary formation channels using a population of events observed by the�…