A Comparative Study of Long and Short GRBs. II. A Multi-wavelength Method to distinguish Type II (massive star) and Type I (compact star) GRBs

TL;DR

This study develops a multi-wavelength Naive Bayes classification method to distinguish Type I and Type II gamma-ray bursts, improving physical categorization beyond duration-based criteria with high accuracy.

Contribution

It introduces a novel multi-wavelength classification approach with a specific probabilistic parameter, achieving low error rates and clarifying ambiguous GRB classifications.

Findings

0.5% training error rate achieved

1% test error rate achieved

Proposed parameter effectively separates GRB types

Abstract

Gamma Ray Burst (GRBs) are empirically classified as long-duration GRBs (LGRBs, $>$ 2s) and short-duration GRBs (SGRBs, $<$ 2s). Physically they can be grouped into two distinct progenitor categories: those originating from collapse of massive stars (also known as Type II) and those related to mergers of compact stars (also known as Type I). Even though most LGRBs are Type II and most SGRBs are Type I, the duration criterion is not always reliable to determine the physical category of a certain GRB. Based on our previous comprehensive study of the multi-wavelength properties of long and short GRBs, here we utilize the Naive Bayes method to physically classify GRBs as Type I and Type II GRBs based on multi-wavelength criteria. It results in 0.5\% training error rate and 1\% test error rate. Moreover, there is a gap [-1.2, -0.16] in the distribution of the posterior Odds, $\log O({\rm II:I})$, the Type II to Type I probability ratio. Therefore, we propose to use ${\cal O} = \log O({\rm II:I})+0.7$ as the parameter to classify GRBs into Type I ($<0$) or Type II ($>0$). The only confirmed Type I GRB, GRB 170817A, has log $O({\rm II:I})=-10$. According to this criterion, the supernova-less long GRBs 060614 and 060505 belong to Type I, and two controversial short GRBs 090426 and 060121 belong to Type II.