Waveform Reconstruction of Core-Collapse Supernovae Gravitational-Waves with Ensemble Empirical Mode Decomposition
arXiv (Cornell University)(2023)
摘要
The gravitational waves (GW) from core-collapse supernovae (CCSN) have been
proposed as a probe to investigate physical properties inside of the supernova.
However, how to search and extract the GW signals from core-collapse supernovae
remains an open question due to its 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 magnetorotational
mechanism and 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 FAPR of GW
sources at a distance of 5 kpc 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 GW reaches 7 × 10^-21, and the
match score threshold is set at 0.75, we can reconstruct GW waveform up to
approximately 36 kpc.
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关键词
ensemble empirical mode decomposition,core-collapse,gravitational-waves
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