Editors: Pau Amaro-Seoane & Bernard Schutz
The last GW Note is a Special Issues on eLISA/NGO

Bayesian parameter estimation in the second LISA Pathfinder Mock Data Challenge

arXiv:1008.5280

by Nofrarias, M. and Röver, C. and Hewitson, M. and Monsky, A. and Heinzel, G. and Danzmann, K. and Ferraioli, L. and Hueller, M. and Vitale, S.
14 pages, 4 figures, submitted to PRD

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.

Comments are closed.