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Journal Article

Frequency-domain gravitational waveform models for inspiraling binary neutron stars

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Kawaguchi,  Kyohei
Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Shibata,  Masaru
Computational Relativistic Astrophysics, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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1802.06518.pdf
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Citation

Kawaguchi, K., Kiuchi, K., Kyutoku, K., Sekiguchi, Y., Shibata, M., & Taniguchi, K. (2018). Frequency-domain gravitational waveform models for inspiraling binary neutron stars. Physical Review D, 97: 044044. doi:10.1103/PhysRevD.97.044044.


Cite as: http://hdl.handle.net/21.11116/0000-0000-BA46-0
Abstract
We develop a model for frequency-domain gravitational waveforms from inspiraling binary neutron stars. Our waveform model is calibrated by comparison with hybrid waveforms constructed from our latest high-precision numerical-relativity waveforms and the SEOBNRv2T waveforms in the frequency range of $10$--$1000\,{\rm Hz}$. We show that the phase difference between our waveform model and the hybrid waveforms is always smaller than $0.1\, {\rm rad}$ for the binary tidal deformability, ${\tilde \Lambda}$, in the range $300\lesssim{\tilde \Lambda}\lesssim1900$ and for the mass ratio between 0.73 and 1. We show that, for $10$--$1000\,{\rm Hz}$, the distinguishability for the signal-to-noise ratio $\lesssim50$ and the mismatch between our waveform model and the hybrid waveforms are always smaller than 0.25 and $1.1\times10^{-5}$, respectively. The systematic error of our waveform model in the measurement of ${\tilde \Lambda}$ is always smaller than $20$ with respect to the hybrid waveforms for $300\lesssim{\tilde \Lambda}\lesssim1900$. The statistical error in the measurement of binary parameters is computed employing our waveform model, and we obtain results consistent with the previous studies. We show that the systematic error of our waveform model is always smaller than $20\%$ (typically smaller than $10\%$) of the statistical error for events with the signal-to-noise ratio of $50$.