2016
DOI: 10.1051/0004-6361/201527642
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Individual power density spectra ofSwiftgamma-ray bursts

Abstract: Context. Timing analysis can be a powerful tool with which to shed light on the still obscure emission physics and geometry of the prompt emission of gamma-ray bursts (GRBs). Fourier power density spectra (PDS) characterise time series as stochastic processes and can be used to search for coherent pulsations and, more in general, to investigate the dominant variability timescales in astrophysical sources. Because of the limited duration and of the statistical properties involved, modelling the PDS of individua… Show more

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Cited by 44 publications
(54 citation statements)
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“…The bent power law has a break at around x b , below which the slope is approximately a constant, and above which it behaves as a simple power law. The bent power law was used to fit the power density spectra of gamma-ray bursts [36]. As shown in Figure 1, the cumulative distributions of fluence, peak flux and duration are well fitted with the bent power law.…”
Section: Statistical Properties Of Sgr J1550-5418mentioning
confidence: 93%
“…The bent power law has a break at around x b , below which the slope is approximately a constant, and above which it behaves as a simple power law. The bent power law was used to fit the power density spectra of gamma-ray bursts [36]. As shown in Figure 1, the cumulative distributions of fluence, peak flux and duration are well fitted with the bent power law.…”
Section: Statistical Properties Of Sgr J1550-5418mentioning
confidence: 93%
“…where N is a normalization factor, f the frequency, α the PL index and G is the uncorrelated statistical noise that has a value of 2 for pure Poissonian noise with the adopted normalization (see also Guidorzi et al 2016). We computed the best-fitting parameters for our PDS in a Bayesian framework.…”
Section: Methodsmentioning
confidence: 99%
“…The values of α and log(f bend ) are 3.1 ± 0.9 and −3.5 ± 0.3, respectively. To check the parameters, we also employ a maximum likelihood method (proposed by Stella et al (1994); Israel & Stella (1996); Vaughan (2010); Barret & Vaughan (2012); Guidorzi et al (2016)) to derive the values of power spectral. And the parameters of α and log(f bend ) are 3.3 ± 0.5 and −3.3 ± 0.2, respectively.…”
Section: Observations and Data Reductionmentioning
confidence: 99%