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Comparison of various methods to extract ringdown frequency from gravitational wave data

Authors :
Nakano, Hiroyuki
Narikawa, Tatsuya
Oohara, Ken-ichi
Sakai, Kazuki
Shinkai, Hisa-aki
Takahashi, Hirotaka
Tanaka, Takahiro
Uchikata, Nami
Yamamoto, Shun
Yamamoto, Takahiro S.
Source :
Phys. Rev. D 99, 124032 (2019)
Publication Year :
2018

Abstract

The ringdown part of gravitational waves in the final stage of merger of compact objects tells us the nature of strong gravity which can be used for testing the theories of gravity. The ringdown waveform, however, fades out in a very short time with a few cycles, and hence it is challenging for gravitational wave data analysis to extract the ringdown frequency and its damping time scale. We here propose to build up a suite of mock data of gravitational waves to compare the performance of various approaches developed to detect quasi-normal modes from a black hole. In this paper we present our initial results of comparisons of the following five methods; (1) plain matched filtering with ringdown part (MF-R) method, (2) matched filtering with both merger and ringdown parts (MF-MR) method, (3) Hilbert-Huang transformation (HHT) method, (4) autoregressive modeling (AR) method, and (5) neural network (NN) method. After comparing their performance, we discuss our future projects.<br />Comment: 15 pages, 4 figures

Details

Database :
arXiv
Journal :
Phys. Rev. D 99, 124032 (2019)
Publication Type :
Report
Accession number :
edsarx.1811.06443
Document Type :
Working Paper
Full Text :
https://doi.org/10.1103/PhysRevD.99.124032