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Search strategies for long gravitational-wave transients: Hidden Markov model tracking and seedless clustering

Banagiri, Sharan and Sun, Ling and Coughlin, Michael W. and Melatos, Andrew (2019) Search strategies for long gravitational-wave transients: Hidden Markov model tracking and seedless clustering. Physical Review D, 100 (2). Art. No. 024034. ISSN 2470-0010. doi:10.1103/physrevd.100.024034.

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A number of detections have been made in the past few years of gravitational waves from compact binary coalescences. While there exist well-understood waveform models for signals from compact binary coalescences, many sources of gravitational waves are not well modeled, including potential long-transient signals from a binary neutron star postmerger remnant. Searching for these sources requires robust detection algorithms that make minimal assumptions about any potential signals. In this paper, we compare two unmodeled search schemes for long-transient gravitational waves, operating on cross-power spectrograms. One is an efficient algorithm first implemented for continuous wave searches, based on a hidden Markov model. The other is a seedless clustering method, which has been used in transient gravitational wave analysis in the past. We quantify the performance of both algorithms, including sensitivity and computational cost, by simulating synthetic signals with a special focus on sources like binary neutron star postmerger remnants. We demonstrate that the hidden Markov model tracking is a good option in model-agnostic searches for low signal-to-noise ratio signals. We also show that it can outperform the seedless method for certain categories of signals while also being computationally more efficient.

Item Type:Article
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URLURL TypeDescription Paper
Sun, Ling0000-0001-7959-892X
Coughlin, Michael W.0000-0002-8262-2924
Additional Information:© 2019 American Physical Society. Received 11 March 2019; published 16 July 2019. We are grateful to Maxime Fays, Rich Ormiston, Stuart Anderson and Vuk Mandic for comments and informative discussions. S. B. acknowledges support in part by the Hoff Lu Fellowship at the university of Minnesota, and by NSF Grant No. PHY-1806630. L. S. is a member of the LIGO Laboratory. M.W. C. is supported by the David and Ellen Lee Postdoctoral Fellowship at the California Institute of Technology. The authors are thankful for the computing resources provided by LIGO Laboratory. LIGO was constructed by the California Institute of Technology and Massachusetts Institute of Technology with funding from the National Science Foundation, and operates under cooperative agreement No. PHY-0757058. Advanced LIGO was built under Grant No. PHY-0823459. The research was also supported by Australian Research Council (ARC) Discovery Project DP170103625 and the ARC Centre of Excellence for Gravitational Wave Discovery CE170100004. This paper carries LIGO Document Number LIGO-P1900047.
Funding AgencyGrant Number
University of MinnesotaUNSPECIFIED
David and Ellen Lee Postdoctoral ScholarshipUNSPECIFIED
Australian Research CouncilDP170103625
Australian Research CouncilCE170100004
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Other Numbering System NameOther Numbering System ID
LIGO DocumentLIGO-P1900047
Issue or Number:2
Record Number:CaltechAUTHORS:20190716-105803651
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:97171
Deposited By: Tony Diaz
Deposited On:16 Jul 2019 18:38
Last Modified:16 Nov 2021 17:27

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