Bayesian statistics for the calibration of the LISA Pathfinder experiment

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Armano, M.; Audley, H.; Auger, G.; Binetruy, P.; Born, M. et al.: A Bayesian statistics for the calibration of the LISA Pathfinder experiment. In: Journal of Physics Conference Series 610 (2015), 12027. DOI: http://dx.doi.org/10.1088/1742-6596/610/1/012027

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/404

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Sum total of downloads: 135




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Abstract: 
The main goal of LISA Path finder (LPF) mission is to estimate the acceleration noise models of the overall LISA Technology Package (LTP) experiment on-board. This will be of crucial importance for the future space-based Gravitational-Wave (GW) detectors, like eLISA. Here, we present the Bayesian analysis framework to process the planned system identification experiments designed for that purpose. In particular, we focus on the analysis strategies to predict the accuracy of the parameters that describe the system in all degrees of freedom. The data sets were generated during the latest operational simulations organised by the data analysis team and this work is part of the LTPDA Matlab toolbox.
License of this version: CC BY 3.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2015
Appears in Collections:Fakultät für Mathematik und Physik

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 85 62.96%
2 image of flag of United States United States 26 19.26%
3 image of flag of France France 5 3.70%
4 image of flag of China China 3 2.22%
5 image of flag of No geo information available No geo information available 2 1.48%
6 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 2 1.48%
7 image of flag of Poland Poland 1 0.74%
8 image of flag of Latvia Latvia 1 0.74%
9 image of flag of India India 1 0.74%
10 image of flag of Indonesia Indonesia 1 0.74%
    other countries 8 5.93%

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