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Revisiting the luminosity and redshift distributions of long gamma-ray bursts

2021/09/02 by Guang-Xuan Lan, Jun-Jie Wei, Houdun Zeng +3 · 2 citations
Physics and Astronomy · #Akaike information criterion #Astro and Planetary Science #Astrophysics #Galaxy #Gamma-ray burst #Gamma-ray bursts and supernovae #Luminosity #Luminosity function #Physics #Power law #Pulsars and Gravitational Waves Research #Redshift #Statistical physics #Statistics #astro-ph.HE

paper · pdf · doi:10.1093/mnras/stab2508

17 pages, 6 figures, 2 tables, accepted by MNRAS

arxiv created 2021/09/02 · openalex publication_date 2021/09/07 · arxiv updated 2021/09/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

ABSTRACT In this work, we update and enlarge the long gamma-ray burst (GRB) sample detected by the Swift satellite. Given the incomplete sampling of the faint bursts and the low completeness in redshift measurement, we carefully select a subsample of bright Swift bursts to revisit the GRB luminosity function (LF) and redshift distribution by taking into account the probability of redshift measurement. Here we also explore two general expressions for the GRB LF, i.e. a broken power-law LF and a triple power-law LF. Our results suggest that a strong redshift evolution in luminosity (with an evolution index of δ =1.92+0.25-0.37) or in density (δ =1.26+0.33-0.34) is required in order to well account for the observations, independent of the assumed expression of the GRB LF. However, in a one-to-one comparison using the Akaike Information Criterion, the best-fitting evolution model involving the triple power-law LF is statistically preferred over the best-fitting one involving the broken power-law LF with a relative probability of ∼94.3 per cent versus ∼5.7 per cent. Extrapolating our fitting results to the flux limit of the whole Swift sample, and considering the trigger probability of Swift/Burst Alert Telescope in detail, we find that the expectations from our evolution models provide a good representation of the observed distributions of the whole sample without the need for any adjustment of the model free parameters. This further confirms the reliability of our analysis results.

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