Waveform reconstruction of core-collapse supernova gravitational waves with ensemble empirical mode decomposition

Abstract

ABSTRACT Gravitational waves (GWs) from core-collapse supernovae (CCSNe) have been proposed as a probe to investigate the physical properties inside supernovae. However, how to search for and extract the GW signals from CCSNe remains an open question owing to their complicated time–frequency structure. In this paper, we apply the ensemble empirical mode decomposition (EEMD) method to decompose and reconstruct simulated GW data generated by the magnetorotational mechanism and the neutrino-driven mechanism within the Advanced LIGO, using the match score as the criterion for assessing the quality of the reconstruction. The results indicate that by decomposing the data, the sum of the first six intrinsic mode functions (IMFs) can be used as the reconstructed waveform. To determine the probability that our reconstructed waveform corresponds to a real GW waveform, we calculate the false alarm probability of reconstruction (FAPR). By setting the threshold of the match score to be 0.75, we obtain the FAPRs of GW sources at distances of 5 and 10 kpc to be 6 × 10−3 and 1 × 10−2, respectively. If we normalize the maximum amplitude of the GW signal to 5 × 10−21, the FAPR at this threshold is 4 × 10−3. Furthermore, in our study, the reconstruction distance is not equivalent to the detection distance. When the strain of GWs reaches 7 × 10−21, and the match score threshold is set at 0.75, we can reconstruct GW waveforms up to approximately 36 kpc.