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A stochastic template bank for gravitational wave searches for precessing neutron star - black hole coalescence events

MPG-Autoren

Indik,  Nathaniel
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

Dal Canton,  Tito
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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Fehrmann,  Henning
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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Krishnan,  Badri
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Lundgren,  Andrew
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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Nielsen,  Alex B.
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Volltexte (frei zugänglich)

1612.05173.pdf
(Preprint), 4MB

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Zitation

Indik, N., Haris, K., Dal Canton, T., Fehrmann, H., Krishnan, B., Lundgren, A., et al. (2017). A stochastic template bank for gravitational wave searches for precessing neutron star - black hole coalescence events. Physical Review D, 95: 064056. doi:10.1103/PhysRevD.95.064056.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-002C-59DE-9
Zusammenfassung
Gravitational wave searches to date have largely focused on non-precessing systems. Including precession effects greatly increases the number of templates to be searched over. This leads to a corresponding increase in the computational cost and can increase the false alarm rate of a realistic search. On the other hand, there might be astrophysical systems that are entirely missed by non-precessing searches. In this paper we consider the problem of constructing a template bank using stochastic methods for neutron star - black hole binaries allowing for generic precession, but with the restriction that the total angular momentum of the binary is pointing towards the detector. We quantify the number of templates required for the search, and we explicitly construct the template bank. We show that despite the large number of templates, stochastic methods can be adapted to solve the problem. We quantify the parameter space region over which the non-precessing search might miss signals.