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A Comprehensive Analysis of Insight-HXMT Gamma-Ray Burst Data. I. Power Density Spectrum

High Energy Astrophysical Phenomena 2024-10-21 v1 High Energy Physics - Phenomenology

Abstract

Power Density Spectrum (PDS) is one of the powerful tools to study light curves of gamma-ray bursts (GRBs). We show the average PDS and individual PDS analysis with {\it Hard X-ray Modulation Telescope} (also named \insighthxmt) GRBs data. The values of power-law index of average PDS (αPˉ\alpha_{\bar{P}}) for long GRBs (LGRBs) vary from 1.58-1.29 (for 100-245, 245-600, and 600-2000 keV). The \insighthxmt\ data allow us to extend the energy of the LGRBs up to 2000 keV, and a relation between αPˉ\alpha_{\bar{P}} and energy EE, αPˉE0.09\alpha_{\bar{P}}\propto E^{-0.09} (8-2000 keV) is obtained. We first systematically investigate the average PDS and individual PDS for short GRBs (SGRBs), and obtain αPˉE0.07\alpha_{\bar{P}}\propto E^{-0.07} (8-1000 keV), where the values of αPˉ\alpha_{\bar{P}} vary from 1.86 to 1.34. The distribution of power-law index of individual PDS (α\alpha) of SGRB, is consistent with that of LGRB, and the α\alpha value for the dominant timescale group (the bent power-law, BPL) is higher than that for the no-dominant timescale group (the single power-law, PL). Both LGRBs and SGRBs show similar α\alpha and αPˉ\alpha_{\bar{P}}, which indicates that they may be the result of similar stochastic processes. The typical value of dominant timescale τ\tau for LGRBs and SGRBs is 1.58 s and 0.02 s, respectively. It seems that the τ\tau in proportion to the duration of GRBs T90T_{90}, with a relation τT900.86\tau \propto T_{90}^{0.86}. The GRB light curve may result from superposing a number of pulses with different timescales. No periodic and quasi-periodical signal above the 3σ\sigma significance threshold is found in our sample.

Keywords

Cite

@article{arxiv.2410.14119,
  title  = {A Comprehensive Analysis of Insight-HXMT Gamma-Ray Burst Data. I. Power Density Spectrum},
  author = {Zi-Min Zhou and Xiang-Gao Wang and En-Wei Liang and Jia-Xin Cao and Hui-Ya Liu and Cheng-Kui Li and Bing Li and Da-Bin Lin and Tian-Ci Zheng and Rui-Jing Lu},
  journal= {arXiv preprint arXiv:2410.14119},
  year   = {2024}
}