Diffractive integrated photonics for analog computing and machine learning
Date
2022
Authors
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Publisher
University of Delaware
Abstract
Recently, optical analog signal processing draws a lot of attentions due to the rising of deep learning, and integrated photonics is a promising platform. In this thesis, the author propose a design method combining the metasurface with the integrated photonics, and demonstrate the analog computing and machine learning meta-systems. The author demonstrate both forward and inversely design methods for different applications: spatial differentiation, pattern classification and wavelength demultiplexing. Compared with free-space optical systems, the proposed on-chip meta-system allows more compact footprint and better mechanical robustness.
Description
Keywords
Integrated photonics, Machine learning, Metasurface, Spatial differentiation, Wavelength demultiplexing