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An adaptive clustering procedure for continuous gravitational wave searches

MPG-Autoren
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Singh,  Avneet
Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Papa,  Maria Alessandra
Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Eggenstein,  Heinz-Bernd
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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

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1707.02676.pdf
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Zitation

Singh, A., Papa, M. A., Eggenstein, H.-B., & Walsh, S. (2017). An adaptive clustering procedure for continuous gravitational wave searches. Physical Review D, 96: 082003. doi:10.1103/PhysRevD.96.082003.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-002D-DB9C-5
Zusammenfassung
In hierarchical searches for continuous gravitational waves, clustering of candidates is an important postprocessing step because it reduces the number of noise candidates that are followed-up at successive stages [1][7][12]. Previous clustering procedures bundled together nearby candidates ascribing them to the same root cause (be it a signal or a disturbance), based on a predefined cluster volume. In this paper, we present a procedure that adapts the cluster volume to the data itself and checks for consistency of such volume with what is expected from a signal. This significantly improves the noise rejection capabilities at fixed detection threshold, and at fixed computing resources for the follow-up stages, this results in an overall more sensitive search. This new procedure was employed in the first Einstein@Home search on data from the first science run of the advanced LIGO detectors (O1) [11].