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.
@article{arxiv.1008.5280,
title = {Bayesian parameter estimation in the second LISA Pathfinder Mock Data Challenge},
author = {M. Nofrarias and C. Röver and M. Hewitson and A. Monsky and G. Heinzel and K. Danzmann and L. Ferraioli and M. Hueller and S. Vitale},
journal= {arXiv preprint arXiv:1008.5280},
year = {2010}
}