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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2309.06011 |
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| _version_ | 1866917595486093312 |
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| author | Yuan, Yong Fan, Xi-Long Lü, Hou-Jun Sun, Yang-Yi Lin, Kai |
| author_facet | Yuan, Yong Fan, Xi-Long Lü, Hou-Jun Sun, Yang-Yi Lin, Kai |
| contents | 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 $6\times10^{-3}$ and $1\times10^{-2}$ respectively. If we normalize the maximum amplitude of the GW signal to $5\times10^{-21}$, the FAPR at this threshold is $4\times10^{-3}$. Furthermore, in our study, the reconstruction distance is not equivalent to the detection distance. When the strain of GW reaches $7 \times 10^{-21}$, and the match score threshold is set at 0.75, we can reconstruct GW waveform up to approximately 36 kpc. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_06011 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Waveform Reconstruction of Core-Collapse Supernovae Gravitational-Waves with Ensemble Empirical Mode Decomposition Yuan, Yong Fan, Xi-Long Lü, Hou-Jun Sun, Yang-Yi Lin, Kai High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology 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 $6\times10^{-3}$ and $1\times10^{-2}$ respectively. If we normalize the maximum amplitude of the GW signal to $5\times10^{-21}$, the FAPR at this threshold is $4\times10^{-3}$. Furthermore, in our study, the reconstruction distance is not equivalent to the detection distance. When the strain of GW reaches $7 \times 10^{-21}$, and the match score threshold is set at 0.75, we can reconstruct GW waveform up to approximately 36 kpc. |
| title | Waveform Reconstruction of Core-Collapse Supernovae Gravitational-Waves with Ensemble Empirical Mode Decomposition |
| topic | High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology |
| url | https://arxiv.org/abs/2309.06011 |