Analysis of gamma-ray burst duration distribution using mixtures of skewed distributions

Abstract

Two classes of GRBs have been confidently identified thus far and are prescribed to different physical scenarios -NS-NS or NS-BH mergers, and collapse of massive stars, for short and long GRBs, respectively. A third, intermediate in duration class, was suggested to be present in previous catalogs, such as BATSE and Swift, based on statistical tests regarding a mixture of two or three log-normal distributions of T 90 . However, this might possibly not be an adequate model. This paper investigates whether the distributions of log T 90 from BATSE, Swift, and Fermi are described better by a mixture of skewed distributions rather than standard Gaussians. Mixtures of standard normal, skew-normal, sinh-arcsinh and alpha-skew-normal distributions are fitted using a maximum likelihood method. The preferred model is chosen based on the Akaike information criterion. It is found that mixtures of two skew-normal or two sinharcsinh distributions are more likely to describe the observed duration distribution of Fermi than a mixture of three standard Gaussians, and that mixtures of two sinharcsinh or two skew-normal distributions are models competing with the conventional three-Gaussian in the case of BATSE and Swift. Based on statistical reasoning, and it is shown that other phenomenological models may describe the observed Fermi, BATSE, and Swift duration distributions at least as well as a mixture of standard normal distributions, and the existence of a third (intermediate) class of GRBs in Fermi data is rejected.

New results in applying the machine learning to GRB redshift estimation

“…It is generally accepted that there are short and long GRBs [2], the former is thought to be originating from binary neutron star mergers and the latter from hypernovas. Lately, with the help of multi-and uni-variate statistical analysis techniques an intermediate group was found [3,4,5,6,7,8,9,10,11,12,13]. Furthermore, recent publications have discovered large structures based on GRBs: the HerculesBorealis great wall at z ≈ 2 [14,15] and the Giant GRB ring at z ≈ 0.8 [16,17].…”

Spectral classification and variation of Fermi GRBs

“…It seems that short GRBs are caused by the collision of two massive stars, and hypernovas can explain long GRBs. Nowadays using multi-and uni-variate statistical analysis techniques an intermediate group was found [3,4,5,6,7,8,9,10,11,12]. Moreover, more huge structures have been published recently which were created by GRBs: the Hercules-Borealis great wall at z ≈ 2 [13,14] and the GRB ring at z ≈ 0.8 [15,16].…”

Statistical properties of Fermi GBM GRBs’ spectra

“…Several papers have said that a third group is possible based on the T90 distribution (Horváth 1998(Horváth , 2009Horváth et al 2010;Hakkila et al 2003). Nevertheless, there are some concerns on its existence (Tarnopolski 2016). We can see that these GRBs (from the third class) are similar to the long GRBs and these also show the difference of E peak .…”