Bayesian Time-Resolved Spectroscopy of GRB Pulses
Hoi-Fung Yu, H\"usne Dereli-B\'egu\'e, Felix Ryde

TL;DR
This study applies a fully Bayesian time-resolved spectral analysis to 38 gamma-ray burst pulses, revealing preferred models, spectral parameter distributions, and relationships, with implications for emission mechanisms.
Contribution
First application of a fully Bayesian approach to time-resolved GRB spectroscopy, providing detailed parameter distributions and model comparisons.
Findings
The cutoff power law model is preferred for spectral fitting.
60% of low-energy spectral indexes are incompatible with synchrotron emission.
Parameter relations show consistent behavior across pulses.
Abstract
We performed time-resolved spectroscopy on a sample of 38 single pulses from 37 gamma-ray bursts detected by the Fermi/Gamma-ray Burst Monitor during its first 9 years of mission. For the first time a fully Bayesian approach is applied. A total of 577 spectra are obtained and their properties studied using two empirical photon models, namely the cutoff power law and Band model. We present the obtained parameter distributions, spectral evolution properties, and parameter relations. We also provide the result files containing this information for usage in further studies. It is found that the cutoff power law model is the preferred model, based on the deviance information criterion and the fact that it consistently provides constrained posterior density maps. In contrast to previous works, the high-energy power-law index of the Band model, , has in general a lower value for the…
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