Revised Constraints on the fast radio burst population from the first CHIME/FRB catalog

TL;DR

This study analyzes the FRB population using the first CHIME/FRB catalog, reconstructing the DM-z relation, modeling energy and redshift distributions, and applying Bayesian inference to constrain key parameters, but cannot definitively determine the population characteristics.

Contribution

It introduces a Bayesian framework to jointly constrain FRB energy and redshift distributions using CHIME/FRB data, considering multiple star formation history models.

Findings

Power-law index constrained to 1.8-1.9

Cutoff energy around 10^42 erg

Pure star formation history model is disfavored

Abstract

In this paper, we investigate the FRB population using the first CHIME/FRB catalog. We first reconstruct the extragalactic dispersion measure -- redshift relation ($\mathrm{DM_E} - z$ relation) from well-localized FRBs, then use it to infer redshift and isotropic energy of the first CHIME/FRB catalog. The intrinsic energy distribution is modeled by the power law with an exponential cutoff, and the selection effect of the CHIME telescope is modeled by a two-parametric function of specific fluence. For the intrinsic redshift distribution, the star formation history (SFH) model, as well as other five SFH-related models are considered. We construct the joint likelihood of fluence, energy and redshift, and all the free parameters are constrained simultaneously using Bayesian inference method. The Bayesian information criterion (BIC) is used to choose the model that best matches the observational data. For comparison, we fit our models with two data samples, i.e. the Full sample and the Gold sample. The power-law index and cutoff energy are tightly constrained to be $1.8 \lesssim \alpha \lesssim 1.9$ and $\mathrm{log}(E_c/{\rm erg}) \approx 42$, which are almost independent of the redshift distribution model and the data sample we choose. The parameters involving the selection effect strongly depends on the data sample, but are insensitive to the redshift distribution model. According to BIC, the pure SFH model is strongly disfavored by both the Full sample and Gold sample. For the rest five SFH-related redshift distribution models, most of them can match the data well if the parameters are properly chosen. Therefore, with the present data, it is still premature to draw a conclusive conclusion on the FRB population.