2012ApJ...748..134G

Gamma-ray bursts (GRBs) have variable light curves. Although most models attribute the observed variability to one physical origin (e.g., central engine activity, clumpy circumburst medium, or relativistic turbulence), some models invoke two physically distinct variability components. We develop a method, namely, the stepwise filter correlation method, to decompose the variability components in a GRB light curve. Based on a low-pass filter technique, we progressively filter the high-frequency signals from the light curve, and then perform a correlation analysis between each adjunct pair of filtered light curves. Our simulations suggest that if a mock light curve contains a "slow" variability component superposed on a rapidly varying time sequence, the correlation coefficient as a function of the filter frequency would display a prominent "dip" feature around the frequency of the slow component. Through simulations, we demonstrate that this method can identify significant clustering structures of a light curve in the frequency domain, and we prove that it can catch superposed signals that are otherwise not easy to retrieve based on other methods (e.g., the power density spectrum analysis method). We apply this method to 266 Burst and Transient Source Experiment bright GRBs. We find that the majority of the bursts have clear evidence of such a superposition effect. We perform a statistical analysis of the identified variability components and discuss the implications for GRB physics.