Distribution of gamma-ray bursts on the t90-hardness ratio plane and their classification revisited
arXiv:2210.16864 · doi:10.1093/mnras/stac3131
Abstract
Using four mixed bivariate distributions (Normal distribution, Skew-Normal distribution, Student distribution, Skew-Student distribution) and bootstrap re-sampling analysis, we analyze the samples of CGRO/BATSE, Swift/BAT and Fermi/GBM gamma-ray bursts in detail on the t90-hardness ratio plane. The Bayesian information criterion is used to judge the goodness of fit for each sample, comprehensively. It is found that all the three samples show a symmetric (either normal or student) distribution. It is also found that the existence of three classes of gamma-ray bursts is preferred by the three samples, but the strength of this preference varies with the sample size: when the sample size of the data set is larger, the preference of three classes scheme becomes weaker. Therefore, the appearance of an intermediate class may be caused by a small sample size and the possibility that there are only two classes of gamma-ray bursts still cannot be expelled yet. A further bootstrap re-sampling analysis also confirms this result.
10 pages, 9 figures
References in corpus (13)
- Multi-messenger Observations of a Binary Neutron Star Merger
- An Ordinary Short Gamma-Ray Burst with Extraordinary Implications: Fermi-GBM Detection of GRB 170817A
- Distributions generated by perturbation of symmetry with emphasis on a multivariate skew distribution
- A Complete Catalog of Swift GRB Spectra and Durations: Demise of a Physical Origin for Pre-Swift High-Energy Correlations
- A new definition of the intermediate group of gamma-ray bursts
- A new type of long gamma--ray burst
- Further Study of the Gamma-Ray Bursts Duration Distribution
- Classification of Swift's gamma-ray bursts
- An Unambiguous Separation of Gamma-Ray Bursts into Two Classes from Prompt Emission Alone
- Statistical Study of Observed and Intrinsic Durations among BATSE and Swift/BAT GRBs
- Classification of Gamma-Ray Burst durations using robust model-comparison techniques
- Searching for differences in Swift's intermediate GRBs
- A maximum likelihood estimate of the parameters of the FRB population