Individual power density spectra of Swift gamma-ray bursts
C. Guidorzi (1), S. Dichiara (1,2), L. Amati (3) ((1) Ferrara, University, (2) ICRANet, (3) INAF IASF-Bologna)

TL;DR
This study analyzes the power density spectra of 215 Swift gamma-ray bursts to identify variability patterns, search for periodic signals, and compare their stochastic properties with active galactic nuclei, revealing new insights into GRB emission physics.
Contribution
It introduces a Bayesian method to model individual GRB PDS and systematically searches for periodic signals, revealing two classes of GRBs and similarities with AGNs.
Findings
Two classes of GRBs with or without a dominant timescale
No significant periodic signals detected in the sample
Similar PDS slope distributions between GRBs and AGNs
Abstract
Timing analysis is a powerful tool with which to shed light on the still obscure emission physics and geometry of the prompt emission of GRBs. Fourier power density spectra (PDS) characterise time series as stochastic processes and can be used to search for coherent pulsations and to investigate the dominant variability timescales. Because of the limited duration and of the statistical properties, modelling the PDS of individual GRBs is challenging, and only average PDS of large samples have been discussed in the literature. We characterise the individual PDS of GRBs in terms of a stochastic process, and carry out for the first time a systematic search for periodic signals and for a link between the PDS and other observables. We present a Bayesian procedure that uses a Markov chain Monte Carlo technique and apply it to study 215 bright long GRBs detected with the Swift Burst Alert…
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