[1008.5280] Bayesian parameter estimation in the second LISA Pathfinder Mock Data Challenge

Authors: M. Nofrarias, C. Röver, M. Hewitson, A. Monsky, G. Heinzel, K. Danzmann, L. Ferraioli, M. Hueller, S. Vitale

Date: 31 Aug 2010

Abstract: A main scientific output of the LISA Pathfinder mission is to provide a noise model that can be extended to the future gravitational wave observatory, LISA. The success of the mission depends thus upon a deep understanding of the instrument, especially the ability to correctly determine the parameters of the underlying noise model. In this work we estimate the parameters of a simplified model of the LISA Technology Package (LTP) instrument. We describe the LTP by means of a closed-loop model that is used to generate the data, both injected signals and noise. Then, parameters are estimated using a Bayesian framework and it is shown that this method reaches the optimal attainable error, the Cramer-Rao bound. We also address an important issue for the mission: how to efficiently combine the results of different experiments to obtain a unique set of parameters describing the instrument.

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Sep 01, 2010

1008.5280 (/preprints)
2010-09-01, 08:40 [edit]

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