Fast Radio Burst Dispersion Measure Distribution as a Probe of Helium Reionization

TL;DR

This paper proposes using the statistical distribution of dispersion measures from fast radio bursts to probe the history of helium reionization in the universe, demonstrating that large surveys can distinguish different reionization scenarios.

Contribution

It introduces a novel approach to study helium reionization using FRB dispersion measure distributions, including analysis without redshift data, through Monte Carlo simulations.

Findings

A survey of 10^4 FRBs can differentiate helium reionization models at ~6σ without redshift info.

Including redshift data increases the discrimination significance to ~10σ.

The method is robust against variations in source redshift distributions and host galaxy models.

Abstract

Fast radio burst (FRB) discoveries are occurring rapidly, with thousands expected from upcoming surveys. The dispersion measures (DM) observed for FRB include important information on cosmological distances and the ionization state of the universe from the redshift of emission until today. Rather than considering the DM--redshift relation, we investigate the statistical ensemble of the distribution of dispersion measures. We explore the use of this abundance information, with and without redshift information, to probe helium reionization. Carrying out Monte Carlo simulations of FRB survey samples, we examine the effect of different source redshift distributions, host galaxy models, sudden vs gradual reionization, and covariance with cosmological parameters on determination of helium reionization properties. We find that a fluence limited survey with 10$^4$ FRBs can discriminate different helium reionization histories at $\sim6\sigma$ using the DM-distribution of bursts, without redshift information (and $\sim10\sigma$ with redshifts).