Generalized Linear Models of T$_{90}$-T$_{50}$ relation to classify GRBs

TL;DR

This paper uses generalized linear models to analyze the relationship between T90 and T50 in gamma-ray bursts, revealing potential for more than two classes beyond traditional bimodal classification.

Contribution

It introduces a novel application of GLMs to classify GRBs based on T90 and T50, identifying multiple linear features indicating additional classes.

Findings

Five linear features in Fermi GBM data

Four linear features in BATSE data

Evidence for more than two GRB classes

Abstract

Gamma-ray bursts (GRBs) can be classified with their linearly dependent parameters alongside the standard $T_{90}$ distribution. The Generalized linear mixture model(GLM) identifies the number of linear dependencies in a two-parameter space. Classically, GRBs are classified into two classes by the presence of bimodality in the histogram of T$_{90}$. However, additional classes and sub-classes of GRBs are fascinating topics to explore. In this work, we investigate the GRBs classes in the $ T_{90} {-}T_{50}$ plane using the Generalized Linear Models(GLM) for Fermi GBM and BATSE catalogs. This study shows five linear features for the Fermi GBM catalog and four linear features for the BATSE catalog, directing towards the possibility of more than two GRB classes.