Bayesian statistics for the calibration of the LISA Pathfinder experiment. (June 2015)

• Record Type: Journal Article
• Authors: Armano, M; Audley, H; Auger, G; Binetruy, P; Born, M; Bortoluzzi, D; Brandt, N; Bursi, A; Caleno, M; Cavalleri, A; Cesarini, A; Cruise, M; Danzmann, K; Diepholz, I; Dolesi, R; Dunbar, N; Ferraioli, L; Ferroni, V; Fitzsimons, E; Freschi, M; García Marirrodriga, C; Gerndt, R; Gesa, L; Gibert, F; Giardini, D; Giusteri, R; Grimani, C; Harrison, I; Heinzel, G; Hewitson, M; Hollington, D; Hueller, M; Huesler, J; Inchauspé, H; Jennrich, O; Jetzer, P; Johlander, B; Karnesis, N; Kaune, B; Korsakova, N; Killow, C; Lloro, I; Maarschalkerweerd, R; Madden, S; Mance, D; Martin, V; Martin-Porqueras, F; Mateos, I; McNamara, P; Mendes, J; Mitchell, E; Moroni, A; Nofrarias, M; Paczkowski, S; Perreur-Lloyd, M; Pivato, P; Plagnol, E; Prat, P; Ragnit, U; Ramos-Castro, J; Reiche, J; Romera Perez, J A; Robertson, D; Rozemeijer, H; Russano, G; Sarra, P; Schleicher, A; Slutsky, J; Sopuerta, C F; Sumner, T; Texier, D; Thorpe, J; Trenkel, C; Tu, H B; Vetrugno, D; Vitale, S; Wanner, G; Ward, H; Waschke, S; Wass, P; Wealthy, D; Wen, S; Weber, W; Wittchen, A; Zanoni, C; Ziegler, T; Zweifel, P;
• Is Part Of: Journal of physics. Number 610(2015)
• Publication Date: 2015-06
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/610/1/012027
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The main goal of LISA Pathfinder (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. A post-publication change was made to this article on 26 Jun 2020 to add an author.