The Minimum Variability Time Scale and its Relation to Pulse Profiles of Fermi GRBs

TL;DR

This paper establishes a connection between the minimum variability time scale in GRB light curves, derived via wavelet analysis, and the pulse rise times obtained through pulse fitting, providing a new method to differentiate signal from noise.

Contribution

It introduces a novel approach linking wavelet-based variability measures with pulse fitting parameters in Fermi GRB data, enhancing analysis techniques.

Findings

Wavelet analysis correlates with pulse rise times in GRB light curves.

A corrective filter improves the agreement between different analysis methods.

The method helps distinguish genuine signals from noise in GRB data.

Abstract

We present a direct link between the minimum variability time scales extracted through a wavelet decomposition and the rise times of the shortest pulses extracted via fits of 34 Fermi GBM GRB light curves comprised of 379 pulses. Pulses used in this study were fitted with log-normal functions whereas the wavelet technique used employs a multiresolution analysis that does not rely on identifying distinct pulses. By applying a corrective filter to published data fitted with pulses we demonstrate agreement between these two independent techniques and offer a method for distinguishing signal from noise.