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Witt, Donald

University of British Columbia

In this thesis, I present two new approaches to achieving high optical coupling efficiency to and from silicon photonic devices. The first approach is a new way of optimizing silicon photonic devices by using machine learning trained with measured data obtained from fabricated devices. I call this new approach, fab-in-the-loop reinforcement learning. I show that by applying fab-in-the-loop reinforcement learning to grating coupler design, I am able to make grating couplers with a lower insertion loss and higher bandwidth then by traditional design methods. The second approach is based on a technology called photonic wire bonding. Photonic wire bonding consists of 3D printing a polymer waveguide between two photonic components using two photon polymerization. I show that it is possible to successfully use photonic wire bonds in cryogenic environments by a careful selection of materials and the appropriate techniques for installation of these bonds.

Text

2023-07-20

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/85287

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/