Do gamma-ray burst measurements provide a useful test of cosmological models?
arXiv:2105.12692 · doi:10.1088/1475-7516/2021/09/042
Abstract
We study eight different gamma-ray burst (GRB) data sets to examine whether current GRB measurements -- that probe a largely unexplored part of cosmological redshift () space -- can be used to reliably constrain cosmological model parameters. We use three Amati-correlation samples and five Combo-correlation samples to simultaneously derive correlation and cosmological model parameter constraints. The intrinsic dispersion of each GRB data set is taken as a goodness measurement. We examine the consistency between the cosmological bounds from GRBs with those determined from better-established cosmological probes, such as baryonic acoustic oscillation (BAO) and Hubble parameter measurements. We use the Markov chain Monte Carlo method implemented in \textsc{MontePython} to find best-fit correlation and cosmological parameters, in six different cosmological models, for the eight GRB samples, alone or in conjunction with BAO and data. For the Amati correlation case, we compile a data set of 118 bursts, the A118 sample, which is the largest -- about half of the total Amati-correlation GRBs -- current collection of GRBs suitable for constraining cosmological parameters. This updated GRB compilation has the smallest intrinsic dispersion of the three Amati-correlation GRB data sets we examined. We are unable to define a collection of reliable bursts for current Combo-correlation GRB data. Cosmological constraints determined from the A118 sample are consistent with -- but significantly weaker than -- those from BAO and data. They also are consistent with the spatially-flat CDM model as well as with dynamical dark energy models and non-spatially-flat models. Since GRBs probe a largely unexplored region of , it is well worth acquiring more and better-quality burst data which will give a more definitive answer to the question of the title.
arXiv comment48 pages, 12 figures, GRB data are given
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