Neil J Cornish and Edward K Porter 2007 Class. Quantum Grav. 24 S501 doi:10.1088/0264-9381/24/19/S13
Searching for massive black hole binaries in the first Mock LISA Data Challenge
Neil J Cornish1 and Edward K Porter1,2
Show affiliationsThe 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 where we know the parameter values a priori and the blind data sets where we were informed of the parameter values after the challenge had finished. 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.
- PACS
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04.80.Nn Gravitational wave detectors and experiments
04.70.-s Physics of black holes
- MSC
- Subjects
- Dates
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Issue 19 (7 October 2007)
Received 30 January 2007, in final form 4 May 2007
Published 19 September 2007
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Searching for massive black hole binaries in the first Mock LISA Data Challenge
Neil J Cornish and Edward K Porter 2007 Class. Quantum Grav. 24 S501
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