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Markov chain Monte Carlo searches for galactic binaries in Mock LISA Data Challenge 1B data sets

Miquel Trias1, Alberto Vecchio2 and John Veitch2

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We are developing a Bayesian approach based on Markov chain Monte Carlo techniques to search for and extract information about white dwarf binary systems with the laser interferometer space antenna (LISA). Here we present results obtained by applying an initial implementation of this method to some of the data sets released in round 1B of the Mock LISA Data Challenges. For Challenges 1B.1.1a and 1b the signals were recovered with parameters lying within the 95.5% posterior probability interval and the correlation between the true and recovered waveform is in excess of 99%. Results were not submitted for Challenge 1B.1.1c due to some convergence problems of the algorithm; despite this, the signal was detected in a search over a 2 mHz band.


PACS

04.80.Nn Gravitational wave detectors and experiments

95.30.Sf Relativity and gravitation

98.35.-a Characteristics and properties of the Milky Way galaxy

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

97.20.Rp Faint blue stars (including blue stragglers), white dwarfs, degenerate stars, nuclei of planetary nebulae

97.80.-d Binary and multiple stars

MSC

85A15 Galactic and stellar structure

83C35 Gravitational waves

85A05 Galactic and stellar dynamics

Subjects

Instrumentation and measurement

Gravitation and cosmology

Astrophysics and astroparticles

Dates

Issue 18 (21 September 2008)

Received 21 April 2008, in final form 26 June 2008

Published 2 September 2008



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