Searching for Massive Black Hole Binaries in the first Mock LISA Data Challenge

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dc.creatorCornish, Neil J.
dc.creatorPorter, Edward K.
dc.date2007-01-30
dc.date.accessioned2026-07-07T10:37:13Z
dc.date.available2026-07-07T10:37:13Z
dc.descriptionThe Mock LISA Data Challenge is a worldwide effort to solve the LISA data analysis problem. We present here our results for the Massive Black Hole Binary (BBH) section of Round 1. Our results cover Challenge 1.2.1, where the coalescence of the binary is seen, and Challenge 1.2.2, where the coalescence occurs after the simulated observational period. The data stream is composed of Gaussian instrumental noise plus an unknown BBH waveform. Our search algorithm is based on a variant of the Markov Chain Monte Carlo method that uses Metropolis-Hastings sampling and thermostated frequency annealing. We present results from the training data sets and the blind data sets. We demonstrate that our algorithm is able to rapidly locate the sources, accurately recover the source parameters, and provide error estimates for the recovered parameters.
dc.description11 pages, 6 figures, Submitted to CQG proceedings of GWDAW 11, AEI, Germany, Dec 2006
dc.identifierhttps://arxiv.org/abs/gr-qc/0701167
dc.identifierhttp://arxiv.org/abs/gr-qc/0701167
dc.identifierClass.Quant.Grav.24:S501-S512,2007
dc.identifierdoi:10.1088/0264-9381/24/19/S13
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/180307
dc.subjectGeneral Relativity and Quantum Cosmology
dc.titleSearching for Massive Black Hole Binaries in the first Mock LISA Data Challenge
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