Microlocal analysis with applications to seismic inverse problems

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Abstract/Contents

Abstract
This thesis considers the travel time tomography problem for elastic media, particularly in the transversely isotropic setting. A pseudo-linearization argument reduces the problem to the microlocal analysis of certain operators, bringing the problem in line with certain problems in X-ray tomography and boundary rigidity studied by de Hoop, Stefanov, Uhlmann, Vasy, et al.. In this thesis, we will consider two versions of the travel time tomography problem, with the two versions using different kinds of assumptions, thus leading to the usage of different kinds of mathematical analysis. The analysis involves asking whether we can provide parametrices for certain classes of operators that are not quite elliptic. In one version of the problem, we show recovery under "global" assumptions using an operator calculus first developed by Boutet de Monvel used to provide parametrices for parabolic operators, while in the second version of the problem, we localize the problem by adding an artificial boundary; the analysis then concerns finding parametrices to certain classes of non-elliptic scattering pseudodifferential operators.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2021; ©2021
Publication date 2021; 2021
Issuance monographic
Language English

Creators/Contributors

Author Zou, Yuzhou
Degree supervisor Vasy, András
Thesis advisor Vasy, András
Thesis advisor Luk, Jonathan, (Professor)
Thesis advisor Mazzeo, Rafe
Degree committee member Luk, Jonathan, (Professor)
Degree committee member Mazzeo, Rafe
Associated with Stanford University, Department of Mathematics

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Yuzhou Zou.
Note Submitted to the Department of Mathematics.
Thesis Thesis Ph.D. Stanford University 2021.
Location https://purl.stanford.edu/tp697xc0955

Access conditions

Copyright
© 2021 by Yuzhou Zou
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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