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A constrained Metropolis–Hastings search for EMRIs in the Mock LISA Data Challenge 1B

Jonathan R Gair1, Edward Porter2, Stanislav Babak2 and Leor Barack3

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We describe a search for the extreme-mass-ratio inspiral sources in the Round 1B Mock LISA Data Challenge data sets. The search algorithm is a Monte Carlo search based on the Metropolis–Hastings algorithm, but also incorporates simulated, thermostated and time annealing, plus a harmonic identification stage designed to reduce the chance of the chain locking onto secondary maxima. In this paper, we focus on describing the algorithm that we have been developing. We give the results of the search of the Round 1B data, although parameter recovery has improved since that deadline. Finally, we describe several modifications to the search pipeline that we are currently investigating for incorporation in future searches.


PACS

04.80.Nn Gravitational wave detectors and experiments

97.20.Pm Supergiant stars

95.55.Br Astrometric and interferometric instruments

97.60.Lf Black holes

95.55.Ym Gravitational radiation detectors; mass spectrometers; and other instrumentation and techniques

97.10.Nf Masses

MSC

83C35 Gravitational waves

85A15 Galactic and stellar structure

Subjects

Instrumentation and measurement

Gravitation and cosmology

Astrophysics and astroparticles

Dates

Issue 18 (21 September 2008)

Received 2 April 2008, in final form 8 June 2008

Published 2 September 2008



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