Constraints on Fast Radio Burst Population from the First CHIME/FRB Catalog with the Hierarchical Bayesian Inference

Fast radio bursts (FRBs) have emerged as one of the most dynamic areas of research in astronomy and cosmology. Despite increasing number of FRBs having been reported, the exact origin of FRBs remains elusive. Investigating the intrinsic redshift distributions of FRBs could provide valuable insights into their possible origins and enhance the power of FRBs as a cosmological probe. In this paper, we propose a hierarchical Bayesian inference approach combining with several viable models to investigate the redshift distribution of the Canadian Hydrogen Intensity Mapping Experiment/FRB catalog 1. By utilizing this method, we aim to uncover the underlying patterns and characteristics of the FRB population, i.e., the intrinsic redshift distribution of FRB. Taking uncertainties within the observational data and selection effects into consideration, we found that the redshift distribution of FRBs is significantly delayed with respect to that of the star formation history.