TL;DR
This paper develops a Bayesian statistical method to estimate redshifts and infer properties of intergalactic magnetic fields from fast radio burst observations, highlighting the need for dense environments and large samples for accurate cosmological insights.
Contribution
It introduces a probabilistic approach combining Monte-Carlo simulations and Bayesian inference to analyze FRB data for cosmological and astrophysical parameters.
Findings
Lower limits on FRB redshifts with extragalactic DM ≥ 400 pc cm$^{-3}$
Intervening galaxies alone cannot explain all highly scattered FRBs
Large samples of FRBs can tighten constraints on intergalactic magnetic fields
Abstract
Context: Fast Radio Bursts are transient radio pulses from presumably compact stellar sources of extragalactic origin. With new telescopes detecting multiple events per day, statistical methods are required in order to interpret observations and make inferences regarding astrophysical and cosmological questions. Purpose: We present a method that uses probability estimates of fast radio burst observables to obtain likelihood estimates for the underlying models. Method: Considering models for all regions along the line-of-sight, including intervening galaxies, we perform Monte-Carlo simulations to estimate the distribution of the dispersion measure, rotation measure and temporal broadening. Using Bayesian statistics, we compare these predictions to observations of Fast Radio Bursts. Results: By applying Bayes theorem, we obtain lower limits on the redshift of Fast Radio Bursts with…
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