Diffractive integrated photonics for analog computing and machine learning
| Author(s) | Wang, Zi | |
| Date Accessioned | 2023-01-24T14:15:20Z | |
| Date Available | 2023-01-24T14:15:20Z | |
| Publication Date | 2022 | |
| SWORD Update | 2022-09-21T16:08:23Z | |
| 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. | |
| Advisor | Gu, Tingyi | |
| Degree | Ph.D. | |
| Department | University of Delaware, Department of Electrical and Computer Engineering | |
| DOI | https://doi.org/10.58088/k4q0-mv60 | |
| Unique Identifier | 1365075077 | |
| URL | https://udspace.udel.edu/handle/19716/32140 | |
| Language | en | |
| Publisher | University of Delaware | |
| URI | https://login.udel.idm.oclc.org/login?url=https://www.proquest.com/dissertations-theses/diffractive-integrated-photonics-analog-computing/docview/2717673702/se-2 | |
| Keywords | Integrated photonics | |
| Keywords | Machine learning | |
| Keywords | Metasurface | |
| Keywords | Spatial differentiation | |
| Keywords | Wavelength demultiplexing | |
| Title | Diffractive integrated photonics for analog computing and machine learning | |
| Type | Thesis |