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Numerical Modeling and Inverse Design of Complex Nanophotonic Systems

Nanophotonics is the study and technological application of the interaction of electromagnetic waves (light) and matter at the nanometer scale. The field's extensive research focuses on generating, detecting, and controlling light using nanoscale features such as nanoparticles, waveguides, resonators, nanoantennas, and more. Exploration in the field is highly dependent on computational methods, which simulate how light will interact with matter in specific situations. However, as nanophotonics advances, so must the computational techniques. In this thesis, I present my work in various numerical studies in nanophotonics, sorted into three categories; plasmonics, inverse design, and deep learning. In plasmonics, I have developed methods for solving advanced material models (including nonlinearities) for small metallic and epsilon-near-zero features and validated them with other theoretical and experimental results. For inverse design, I introduce new methods for designing optical pulse shapes and metalenses for focusing high-harmonic generation. Finally, I used deep learning to model plasmonic colour generation from structured metal surfaces and to predict plasmonic nanoparticle multipolar responses.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/45819
Date10 January 2024
CreatorsBaxter, Joshua Stuart Johannes
ContributorsRamunno, Lora
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf
RightsAttribution-NoDerivatives 4.0 International

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