Characteristic time scales in Gamma-Ray Bursts
Power spectral density with wavelet techniques
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Gamma-Ray Bursts (GRBs) light curve temporal analysis provides useful information about the nature of the phenomenon and the physics behind it. We investigate the presence of characteristic time scales in GRB prompt light curves using wavelets, a relatively new analysis technique with the property of decomposing the input signal on a set of localised basis functions, which are best suited than long waves to analyise transient phenomena such as GRBs. Wavelets are used to perform wavelet filtering and wavelet power spectra on the 50 brightest GRBs detected by BeppoSAX, looking for the dominant t...
Gamma-Ray Bursts (GRBs) light curve temporal analysis provides useful information about the nature of the phenomenon and the physics behind it. We investigate the presence of characteristic time scales in GRB prompt light curves using wavelets, a relatively new analysis technique with the property of decomposing the input signal on a set of localised basis functions, which are best suited than long waves to analyise transient phenomena such as GRBs. Wavelets are used to perform wavelet filtering and wavelet power spectra on the 50 brightest GRBs detected by BeppoSAX, looking for the dominant time scales in the GRB prompt emission. We found that GRBs can be classified based on their power spectra shape. We looked for correlations between the temporal power and the peak energy of the GRB energy spectrum. We tentatively found that what seems to be mostly important is the temporal power at shorter time scales: a large power at these time scales is more likely to be associated to large values of the time-averaged peak energy.
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