Award Date
5-1-2020
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Mathematical Sciences
First Committee Member
Jichun Li
Second Committee Member
Hongtao Yang
Third Committee Member
Pengtao Sun
Fourth Committee Member
Monika Neda
Fifth Committee Member
Robert Schill
Number of Pages
109
Abstract
This dissertation study three different approaches for stochastic electromagnetic fields based on the time domain Maxwell's equations and Drude's model: stochastic Galerkin method, stochastic collocation method, and Monte Carlo class methods. For each method, we study its regularity, stability, and convergence rates. Numerical experiments have been presented to verify our theoretical results. For stochastic collocation method, we also simulate the backward wave propagation in metamaterial phenomenon. It turns out that the stochastic Galerkin method admits the best accuracy property but hugest computational workload as the resultant PDEs system is usually coupled. The Monte Carlo class methods are easy to implement and do parallel computing but the accuracy is relatively low. The stochastic collocation method inherits the advantages of both of these two methods.
Keywords
Maxwell's equations; Uncertainty quantification
Disciplines
Mathematics
File Format
File Size
1.7 MB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Fang, Zhiwei, "Uncertainty Quantification for Maxwell's Equations" (2020). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3892.
http://dx.doi.org/10.34917/19412069
Rights
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