Short versus long gamma-ray bursts: a comprehensive study of energetics and prompt gamma-ray correlations
Abstract
We present the results of a comprehensive study of the luminosity function, energetics, prompt gamma-ray correlations, and classification methodology of short-hard and long-soft gamma-ray bursts (GRBs), based on observational data in the largest catalogue of GRBs available to this date: BATSE catalogue of 2702 GRBs. We find that (1) the least-biased classification method of GRBs into short and long, solely based on prompt-emission properties, appears to be the ratio of the observed spectral peak energy to the observed duration (R = Ep/T90) with the dividing line at R ≃ 50[keV s-1]; (2) once data is carefully corrected for the effects of the detection threshold of gamma-ray instruments, the population distribution of short gamma-ray bursts (SGRBs) and long gamma-ray bursts (LGRBs) can be individually well described as multivariate lognormal distribution in the four-dimensional space of the isotropic peak gamma-ray luminosity, total isotropic gamma-ray emission, the intrinsic spectral peak energy, and the intrinsic duration; (3) relatively large fractions of SGRBs and LGRBs with moderate-to-low spectral peak energies have been missed by BATSE detectors; (4) relatively strong and highly significant intrinsic hardness-brightness and duration-brightness correlations likely exist in both populations of SGRBs and LGRBs, once data is corrected for selection effects. The strengths of these correlations are very similar in both populations, implying similar mechanisms at work in both GRB classes, leading to the emergence of these prompt gamma-ray correlations.
- Publication:
-
Monthly Notices of the Royal Astronomical Society
- Pub Date:
- July 2015
- DOI:
- 10.1093/mnras/stv714
- arXiv:
- arXiv:1412.5630
- Bibcode:
- 2015MNRAS.451..126S
- Keywords:
-
- methods: analytical;
- methods: numerical;
- methods: statistical;
- gamma-ray burst: general;
- Astrophysics - High Energy Astrophysical Phenomena;
- Physics - Data Analysis;
- Statistics and Probability;
- Physics - Instrumentation and Detectors
- E-Print:
- Accepted to MNRAS