Graph-based clustering of gamma-ray bursts
arXiv:2109.13204 · doi:10.1051/0004-6361/202038645
Abstract
Aims. An attempt to classify gamma-ray bursts (GRBs) with a low level of supervision using the state-of-the-start approaches stemming from graph theory was undertaken. Methods. Graph-based classification methods, relying on different variants of the -nearest neighbour graph, were applied to various GRB samples in the duration-hardness ratio parameter space to infer the optimal partitioning. Results. In most cases it is found that both two and three groups are feasible, with the outcome being more ambiguous with an increasing sample size. Conclusions. There is no clear indication of the presence of a third GRB class; however, such a possibility cannot be ruled out with the employed methodology. There are no hints at more than three classes though.
8 pages, 6 figures; accepted in A&A
References in corpus (12)
- A new definition of the intermediate group of gamma-ray bursts
- Further Study of the Gamma-Ray Bursts Duration Distribution
- Classification of Swift's gamma-ray bursts
- An analysis of the durations of Swift Gamma-Ray Bursts
- An Unambiguous Separation of Gamma-Ray Bursts into Two Classes from Prompt Emission Alone
- A MST algorithm for source detection in gamma-ray images
- Gaussian-mixture-model-based cluster analysis of gamma-ray bursts in the BATSE catalog
- An Evolutionary Paradigm for Dusty Active Galaxies at Low Redshift
- Multivariate analysis of BATSE gamma-ray burst properties using skewed distributions
- Two Dimensional Classification of the Swift/BAT GRBs
- On the Connection of Gamma-Ray Bursts and X-Ray Flashes in the BATSE and RHESSI Databases
- Multidimensional analysis of Fermi GBM gamma-ray bursts