Bayesian statistics for the calibration of the LISA Pathfinder experiment
| Autor: | M Armano, H Audley, G Auger, P Binetruy, M Born, D Bortoluzzi, N Brandt, A Bursi, M Caleno, A Cavalleri, A Cesarini, M Cruise, K Danzmann, I Diepholz, R Dolesi, N Dunbar, L Ferraioli, V Ferroni, E Fitzsimons, M Freschi, C García Marirrodriga, R Gerndt, L Gesa, F Gibert, D Giardini, R Giusteri, C Grimani, I Harrison, G Heinzel, M Hewitson, D Hollington, M Hueller, J Huesler, H Inchauspé, O Jennrich, P Jetzer, B Johlander, N Karnesis, B Kaune, N Korsakova, C Killow, I Lloro, R Maarschalkerweerd, S Madden, D Mance, V Martin, F Martin-Porqueras, I Mateos, P McNamara, J Mendes, E Mitchell, A Moroni, M Nofrarias, S Paczkowski, M Perreur-Lloyd, P Pivato, E Plagnol, P Prat, U Ragnit, J Ramos-Castro, J Reiche, J A Romera Perez, D Robertson, H Rozemeijer, G Russano, P Sarra, A Schleicher, J Slutsky, C F Sopuerta, T Sumner, D Texier, J Thorpe, C Trenkel, H B Tu, D Vetrugno, S Vitale, G Wanner, H Ward, S Waschke, P Wass, D Wealthy, S Wen, W Weber, A Wittchen, C Zanoni, T Ziegler, P Zweifel |
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| Přispěvatelé: | AstroParticule et Cosmologie (APC (UMR_7164)), Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité) |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
History
MATLAB detector: satellite Calibration (statistics) Astronomy Bayesian probability Lisa technology packages Gravity waves computer.software_genre Astrophysics Bayesian statistics 01 natural sciences Degrees of freedom (mechanics) LISA Pathfinder Education Physics Applied Gravitational wave detectors Theoretical physics Matlab toolboxes Operational simulations 0103 physical sciences numerical methods ddc:530 [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det] noise: acceleration 010306 general physics Dewey Decimal Classification::500 | Naturwissenschaften Konferenzschrift Mathematics Data processing 010308 nuclear & particles physics Design of experiments System identification statistical analysis: Bayesian Analysis strategies gravitational radiation detector Computer Science Applications Pathfinder LISA: calibration gravitational radiation: emission [PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc] Bayesian Analysis Noise (video) Data mining ddc:500 Dewey Decimal Classification::500 | Naturwissenschaften::530 | Physik computer Space probes |
| Zdroj: | J.Phys.Conf.Ser. Journal of Physics Conference Series 610 (2015) Journal of Physics: Conference Series 610 (2015), Nr. 1 |
| ISSN: | 1742-6588 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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