Statistical search for angular non-stationarities of long gamma-ray burst jets using Swift data
Abstract
In Budai et al. (2020) we argued that angular non-stationarities of gamma-ray burst (GRB) jets can result in a statistical connection between the angle values deduced from jet break times and the variabilities of prompt light curves. The connection should be an anti-correlation if luminosity densities of jets follow a power-law or a uniform profile, and a correlation if they have a Gaussian profile. In this follow-up paper, we search for the connection by measuring Spearman's rank correlation coefficient in a sample of 19 long GRBs observed by the Swift satellite. Using 16 of the GRBs with well-defined angle measurements, we find and . Adding three more GRBs to the sample, each with a pair of equally possible angle values, can strengthen the anti-correlation to and . We show that these results are incompatible with non-stationary jets having Gaussian profiles, and that GRBs with observed afterglows would be needed to confirm the potential existence of the angle-variability anti-correlation with significance. If the connection is real, GRB jet angles would be constrainable from prompt gamma light curves, without the need of afterglow observations.
Cite
@article{arxiv.2103.16209,
title = {Statistical search for angular non-stationarities of long gamma-ray burst jets using Swift data},
author = {Andor Budai and Peter Raffai and Balint Borgulya and Brian Albert Dawes and Gabor Szeifert},
journal= {arXiv preprint arXiv:2103.16209},
year = {2021}
}
Comments
4 pages, 1 figure, published in MNRAS, The codes we used to produce the results of Budai et al. (2020) and this paper can be accessed at https://github.com/BMetod