The Swift Gamma-Ray Burst redshift distribution: selection biases or rate evolution at high-z?

TL;DR

This paper models the true distribution of Gamma-Ray Burst redshifts by accounting for various selection biases, revealing dust extinction as a key factor shaping observed distributions.

Contribution

It introduces a comprehensive model incorporating multiple selection effects to better understand the intrinsic GRB redshift distribution.

Findings

Selection effects can fully explain the observed redshift distribution.

Dust extinction is identified as the primary astrophysical bias.

The model aligns well with Swift and TOUGH survey data.

Abstract

We employ realistic constraints on selection effects to model the Gamma-Ray Burst (GRB) redshift distribution using {\it Swift} triggered redshift samples acquired from optical afterglows and the TOUGH survey. Models for the Malmquist bias, redshift desert, and the fraction of afterglows missing because of host galaxy dust extinction, are used to show how the "true" GRB redshift distribution is distorted to its presently observed biased distribution. Our analysis, which accounts for the missing fraction of redshifts in the two data subsets, shows that a combination of selection effects (both instrumental and astrophysical) can describe the observed GRB redshift distribution. The observed distribution supports the case for dust extinction as the dominant astrophysical selection effect that shapes the redshift distribution.