Master Thesis Online
Gravitational lensing of gravitational waves: Theoretical review and identification with deep learning
Master_Thesis_Offermans2022.pdf
Offermans, Arthur 
Promotor(s) :
Cudell, Jean-René
Date of defense : 30-Jun-2022/1-Jul-2022 • Permalink : http://hdl.handle.net/2268.2/14778
Details
| Title : | Gravitational lensing of gravitational waves: Theoretical review and identification with deep learning |
| Author : | Offermans, Arthur
|
| Date of defense : | 30-Jun-2022/1-Jul-2022 |
| Advisor(s) : | Cudell, Jean-René
|
| Committee's member(s) : | De Becker, Michaël
Fays, Maxime
Sluse, Dominique
|
| Language : | English |
| Number of pages : | 104 |
| Keywords : | [en] Gravitational lensing [en] Gravitational waves [en] Convolutional neural network |
| Discipline(s) : | Physical, chemical, mathematical & earth Sciences > Space science, astronomy & astrophysics |
| Target public : | Researchers Professionals of domain Student |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en sciences spatiales, à finalité approfondie |
| Faculty: | Master thesis of the Faculté des Sciences |
Abstract
[en] This master thesis aims at providing a basic understanding of the phenomenon of gravitational lensing of gravitational waves, as well as providing a concrete tool to analyse the data and identify it, namely a neural network. First, the basic concepts of the gravitational lensing effect are introduced. Then, the particular case of the lensing of gravitational waves is investigated mathematically and the results are discussed. Once this concept is understood, a neural network model designed to identify lensed gravitational waves is presented and its performance are discussed. Finally, the importance of detecting this effect is stressed and some improvements of the proposed model are suggested for future works.
Cite this master thesis
APA
Offermans, A. (2022). Gravitational lensing of gravitational waves: Theoretical review and identification with deep learning. (Unpublished master's thesis). Université de Liège, Liège, Belgique. Retrieved from https://matheo.uliege.be/handle/2268.2/14778
Chicago
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The University of Liège does not guarantee the scientific quality of these students' works or the accuracy of all the information they contain.