# Gaussian-mixture-model-based cluster analysis of gamma-ray bursts in the BATSE catalog

## TL;DR

This paper applies Gaussian mixture models to classify gamma-ray bursts in the BATSE catalog, revealing that the known three types are subdivided into more detailed groups based on brightness and other variables.

## Contribution

It introduces a Gaussian-mixture-model-based clustering approach to analyze GRB data, providing a refined classification that uncovers subgroups within known categories.

## Key findings

- Identified that the three main GRB types are subdivided into dim and bright groups.
- Reaffirmed the existence of short, long, and intermediate GRB types with additional brightness-based subgroups.
- Found that brightness distribution is asymmetric and not correlated with duration or spectral hardness.

## Abstract

Clustering is an important tool to describe gamma-ray bursts (GRBs). We analyzed the Final BATSE Catalog using Gaussian-mixture-models-based clustering methods for six variables (durations, peak flux, total fluence and spectral hardness ratios) that contain information on clustering. Our analysis found that the five kinds of GRBs previously found by other authors are only the cut groups of the previously well-known three types (short, long and intermediate in duration). The two short and intermediate duration groups differ mostly in the peak flux. Therefore, the reanalysis of the BATSE data finds similar group structures than previously. Because the brightness distribution is asymmetric and not correlated with durations or hardnesses the Gaussian mixture model cuts the Short and the Intermediate duration groups into two subgroups, the dim ones and the bright ones.