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First-stage LISA data processing and gravitational wave data analysis[electronic resource] :ultraprecise inter-satellite laser ranging, clock synchronization and novel gravitational wave data analysis algorithms /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	539.754
書名/作者:	First-stage LISA data processing and gravitational wave data analysis : ultraprecise inter-satellite laser ranging, clock synchronization and novel gravitational wave data analysis algorithms // by Yan Wang.
作者:	Wang, Yan.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	xxx, 228 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Gravitational waves - Data processing.
標題:	Gravitational waves - Mathematical models.
標題:	Physics.
標題:	Astrophysics and Astroparticles.
標題:	Laser Technology, Photonics.
標題:	Data Mining and Knowledge Discovery.
標題:	Classical and Quantum Gravitation, Relativity Theory.
標題:	Measurement Science and Instrumentation.
標題:	Quantum Optics.
ISBN:	9783319263892
ISBN:	9783319263885
內容註:	Introduction -- LISA data processing chain -- Applying the Kalman filter to a simple case -- The inter-spacecraft measurements -- Design a hybrid extended Kalman filter for the entire LISA constellation -- Alternative Kalman filter models -- Broken laser links and robustness -- Optimal filtering for LISA with effective system models -- Clock noise and disordered measurements -- Octahedron configuration for a displacement noise-canceling gravitational wave detector in space -- EMRI data analysis with a phenomenological waveform -- Fast detection and automatic parameter estimation of a gravitational wave signal with a novel method -- Likelihood transform: making optimization and parameter estimation easier.
摘要、提要註:	This thesis covers a diverse set of topics related to space-based gravitational wave detectors such as the Laser Interferometer Space Antenna (LISA) The core of the thesis is devoted to the preprocessing of the interferometric link data for a LISA constellation, specifically developing optimal Kalman filters to reduce arm length noise due to clock noise. The approach is to apply Kalman filters of increasing complexity to make optimal estimates of relevant quantities such as constellation arm length, relative clock drift, and Doppler frequencies based on the available measurement data. Depending on the complexity of the filter and the simulated data, these Kalman filter estimates can provide up to a few orders of magnitude improvement over simpler estimators. While the basic concept of the LISA measurement (Time Delay Interferometry) was worked out some time ago, this work brings a level of rigor to the processing of the constellation-level data products. The thesis concludes with some topics related to the eLISA such as a new class of phenomenological waveforms for extreme mass-ratio inspiral sources (EMRIs, one of the main source for eLISA), an octahedral space-based GW detector that does not require drag-free test masses, and some efficient template-search algorithms for the case of relatively high SNR signals.
電子資源:	http://dx.doi.org/10.1007/978-3-319-26389-2

First-stage LISA data processing and gravitational wave data analysis[electronic resource] :ultraprecise inter-satellite laser ranging, clock synchronization and novel gravitational wave data analysis algorithms /
Wang, Yan.

First-stage LISA data processing and gravitational wave data analysisultraprecise inter-satellite laser ranging, clock synchronization and novel gravitational wave data analysis algorithms /[electronic resource] :by Yan Wang. - Cham :Springer International Publishing :2016. - xxx, 228 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- LISA data processing chain -- Applying the Kalman filter to a simple case -- The inter-spacecraft measurements -- Design a hybrid extended Kalman filter for the entire LISA constellation -- Alternative Kalman filter models -- Broken laser links and robustness -- Optimal filtering for LISA with effective system models -- Clock noise and disordered measurements -- Octahedron configuration for a displacement noise-canceling gravitational wave detector in space -- EMRI data analysis with a phenomenological waveform -- Fast detection and automatic parameter estimation of a gravitational wave signal with a novel method -- Likelihood transform: making optimization and parameter estimation easier.

This thesis covers a diverse set of topics related to space-based gravitational wave detectors such as the Laser Interferometer Space Antenna (LISA) The core of the thesis is devoted to the preprocessing of the interferometric link data for a LISA constellation, specifically developing optimal Kalman filters to reduce arm length noise due to clock noise. The approach is to apply Kalman filters of increasing complexity to make optimal estimates of relevant quantities such as constellation arm length, relative clock drift, and Doppler frequencies based on the available measurement data. Depending on the complexity of the filter and the simulated data, these Kalman filter estimates can provide up to a few orders of magnitude improvement over simpler estimators. While the basic concept of the LISA measurement (Time Delay Interferometry) was worked out some time ago, this work brings a level of rigor to the processing of the constellation-level data products. The thesis concludes with some topics related to the eLISA such as a new class of phenomenological waveforms for extreme mass-ratio inspiral sources (EMRIs, one of the main source for eLISA), an octahedral space-based GW detector that does not require drag-free test masses, and some efficient template-search algorithms for the case of relatively high SNR signals.

ISBN: 9783319263892

Standard No.: 10.1007/978-3-319-26389-2doiSubjects--Topical Terms:

654664
Gravitational waves
--Data processing.

LC Class. No.: QC179

Dewey Class. No.: 539.754

First-stage LISA data processing and gravitational wave data analysis[electronic resource] :ultraprecise inter-satellite laser ranging, clock synchronization and novel gravitational wave data analysis algorithms /
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