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Journal Article

Implementing a semicoherent search for continuous gravitational waves using optimally-constructed template banks

MPS-Authors
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Wette,  K.
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;
Searching for Continuous Gravitational Waves, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

Walsh,  S.
Searching for Continuous Gravitational Waves, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

/persons/resource/persons40534

Prix,  R.
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;
Searching for Continuous Gravitational Waves, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

/persons/resource/persons20662

Papa,  M. A.
Searching for Continuous Gravitational Waves, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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1804.03392.pdf
(Preprint), 2MB

1804.03392v3.pdf
(Preprint), 740KB

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Citation

Wette, K., Walsh, S., Prix, R., & Papa, M. A. (2018). Implementing a semicoherent search for continuous gravitational waves using optimally-constructed template banks. Physical Review D, 97: 123016. doi:10.1103/PhysRevD.97.123016.


Cite as: https://hdl.handle.net/21.11116/0000-0001-4085-0
Abstract
All-sky surveys for isolated continuous gravitational waves present a
significant data-analysis challenge. Semicoherent search methods are commonly
used to efficiently perform the computationally-intensive task of searching for
these weak signals in the noisy data of gravitational-wave detectors such as
LIGO and Virgo. We present a new implementation of a semicoherent search
method, Weave, that for the first time makes full use of a parameter-space
metric to generate search templates in the correct resolution, combined with
optimal lattices to minimize the required number of templates and hence the
computational cost of the search. We describe the implementation of Weave and
associated design choices, and characterize its behavior using semi-analytic
models.