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  Improved time–frequency analysis of extreme-mass-ratio inspiral signals in mock LISA data

Gair, J. R., Mandel, I., & Wen, L. (2008). Improved time–frequency analysis of extreme-mass-ratio inspiral signals in mock LISA data. Classical and Quantum Gravity, 25(18): 184031. doi:10.1088/0264-9381/25/18/184031.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-1479-B Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-147B-7
Genre: Conference Paper

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 Creators:
Gair, Jonathan R.1, Author
Mandel, Ilya1, Author
Wen, Linqing2, Author
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1External Organizations, ou_persistent22              
2MPI for Gravitational Physics, Max Planck Society, Golm, DE, ou_24007              

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 Abstract: The planned Laser Interferometer Space Antenna (LISA) is expected to detect gravitational wave signals from ~100 extreme-mass-ratio inspirals (EMRIs) of stellar-mass compact objects into massive black holes. The long duration and large parameter space of EMRI signals make data analysis for these signals a challenging problem. One approach to EMRI data analysis is to use time–frequency methods. This consists of two steps: (i) searching for tracks from EMRI sources in a time–frequency spectrogram and (ii) extracting parameter estimates from the tracks. In this paper we discuss the results of applying these techniques to the latest round of the Mock LISA Data Challenge, Round 1B. This analysis included three new techniques not used in previous analyses: (i) a new chirp-based algorithm for track search for track detection; (ii) estimation of the inclination of the source to the line of sight; (iii) a Metropolis–Hastings Monte Carlo over the parameter space in order to find the best fit to the tracks.

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 Dates: 2008-09-02
 Publication Status: Published online
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 Rev. Method: Peer
 Identifiers: DOI: 10.1088/0264-9381/25/18/184031
eDoc: 399771
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Title: 12th Annual Gravitational Wave Data Analysis Workshop (GWDAW 2007)
Place of Event: Cambridge, Massachusetts
Start-/End Date: 2007-12-13 - 2007-12-16

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Title: Classical and Quantum Gravity
Source Genre: Journal
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Pages: - Volume / Issue: 25 (18) Sequence Number: 184031 Start / End Page: - Identifier: ISSN: 0264-9381