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

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.

6 pages, 5 figures

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• Multivariate analysis of BATSE gamma-ray burst properties using skewed distributions
• Properties of Gamma-Ray Bursts Associated with Supernovae and Kilonovae
• Graph-based clustering of gamma-ray bursts
• A new nonparametric interpoint distance-based measure for assessment of clustering
• A new interpoint distance-based clustering algorithm using kernel density estimation
• Fast model-based clustering of partial records
• Evaluation of the number of clusters in a data set using $p$-values from Multiple Tests of Hypotheses
• Confirmation of Binary Clustering in Gamma-Ray Bursts through an Integrated $p$-value from Multiple Nonparametric Tests of Hypotheses
• How does the shape of gamma-ray bursts' pulses affect the duration distribution?
• Calibration of luminosity correlations of gamma-ray bursts using quasars
• Latent characterisation of the complete BATSE gamma ray bursts catalogue using Gaussian mixture of factor analysers and model-estimated overlap-based syncytial clustering
• Modeling quasar variability through self-organizing map-based process