Exploring Gamma-Ray Burst Diversity: Clustering Analysis of the Emission Characteristics of Fermi- and BATSE-detected Gamma-Ray Bursts

Abstract

Gamma-ray bursts (GRBs), often attributed to massive star collapse or binary compact object mergers, exhibit diverse emission characteristics hinting at multiple GRB classes based on various factors like progenitors, radiation mechanisms, and central engines. This study employs unsupervised clustering using the nested Gaussian mixture model algorithm to analyze data from Fermi and BATSE, identifying four classes (A–D) based on duration, spectral peak, and spectral index of time-integrated spectra of GRBs. Class proportions are approximately 70%, 10%, 3%, and 17%, respectively, with A and B comprising mostly long GRBs, C mainly short GRBs, and D encompassing both types. The classes are further assessed based on spectral index α, indicating distinct radiation mechanisms: α > −0.67 for photospheric emission, α ≤ −1.5 for fast-cooling synchrotron, and −1.5 < α ≤ −0.67 for slow-cooling synchrotron. Classes B and C align with photospheric emission, while A and D predominantly exhibit synchrotron radiation. Short GRBs are predominantly photospheric emission, whereas long GRBs tend to favor synchrotron emission. Overall, 63% of the total bursts exhibit α profiles indicative of synchrotron emission, with the remaining 37% associated with photospheric emission. Considering the limited data of kilonova and supernova associated with GRBs, classes are examined for progenitor origins, suggesting a hybrid nature for A and D, and collapsar and merger origins for B and C, respectively. This clustering analysis results in four GRB classes, which, upon investigation, reveal the diverse and complex nature of GRBs in terms of their radiation, duration, and progenitor.