Accounting for Selection Bias and Redshift Evolution in GRB Radio Afterglow Data

Dainotti, Maria ; Levine, Delina ; Fraija, Nissim ; Chandra, Poonam (2021) Accounting for Selection Bias and Redshift Evolution in GRB Radio Afterglow Data Galaxies, 9 (4). p. 95. ISSN 2075-4434

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Official URL: http://doi.org/10.3390/galaxies9040095

Related URL: http://dx.doi.org/10.3390/galaxies9040095

Abstract

Gamma-ray Bursts (GRBs) are highly energetic events that can be observed at extremely high redshift. However, inherent bias in GRB data due to selection effects and redshift evolution can significantly skew any subsequent analysis. We correct for important variables related to the GRB emission, such as the burst duration, T∗90, the prompt isotropic energy, Eiso, the rest-frame end time of the plateau emission, T∗a,radio, and its correspondent luminosity La,radio, for radio afterglow. In particular, we use the Efron–Petrosian method presented in 1992 for the correction of our variables of interest. Specifically, we correct Eiso and T∗90 for 80 GRBs, and La,radio and T∗a,radio for a subsample of 18 GRBs that present a plateau-like flattening in their light curve. Upon application of this method, we find strong evolution with redshift in most variables, particularly in La,radio, with values similar to those found in past and current literature in radio, X-ray and optical wavelengths, indicating that these variables are susceptible to observational bias. This analysis emphasizes the necessity of correcting observational data for evolutionary effects to obtain the intrinsic behavior of correlations to use them as discriminators among the most plausible theoretical models and as reliable cosmological tools.

Item Type:Article
Source:Copyright of this article belongs to MDPI
Keywords:GRB; radio; redshift evolution
ID Code:125588
Deposited On:29 Sep 2022 06:23
Last Modified:29 Sep 2022 06:23

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