Generalized Linear Models of T-T relation to classify GRBs
arXiv:2305.03947 · doi:10.1093/mnras/stae2371
Abstract
Gamma-ray bursts (GRBs) can be classified with their linearly dependent parameters alongside the standard distribution. The Generalized linear mixture model(GLM) identifies the number of linear dependencies in a two-parameter space. Classically, GRBs are classified into two classes by the presence of bimodality in the histogram of T. However, additional classes and sub-classes of GRBs are fascinating topics to explore. In this work, we investigate the GRBs classes in the plane using the Generalized Linear Models(GLM) for Fermi GBM and BATSE catalogs. This study shows five linear features for the Fermi GBM catalog and four linear features for the BATSE catalog, directing towards the possibility of more than two GRB classes.
8 figures, 1 table
References in corpus (11)
- GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral
- Swope Supernova Survey 2017a (SSS17a), the Optical Counterpart to a Gravitational Wave Source
- No supernovae associated with two long-duration gamma ray bursts
- A Kilonova Following a Long-Duration Gamma-Ray Burst at 350 Mpc
- Multilevel functional principal component analysis
- The First Swift BAT Gamma-Ray Burst Catalog
- Gamma-ray burst progenitors
- Classification of Swift's gamma-ray bursts
- Statistical Study of Observed and Intrinsic Durations among BATSE and Swift/BAT GRBs
- Classification of BeppoSAX's Gamma-Ray Bursts
- Eighteen Years of Kilonova Discoveries with Swift