Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/154812
Title: Photonic integrated circuit for quantum and optical computing
Authors: Zhang, Hui
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Zhang, H. (2022). Photonic integrated circuit for quantum and optical computing. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154812
Abstract: In recent years, optical computing becomes a powerful task-specific platform, under the increasing demand for computing power (especially for neural networks). This doctoral thesis is devoted to the design, simulation, and testing of integrated silicon photonic circuits for optical neural networks and machine-learning-assisted quantum computing tasks. In Chapter 3, we demonstrate an optical neural chip that implements complex-valued neural networks and benchmark its performance under practical settings, proving strong learning capabilities. In Chapter 4, we demonstrate an efficient, physics-agnostic, and closed-loop protocol for training optical neural networks on chip. In Chapter 5, we demonstrate a silicon photonic chip that achieves chip-to-chip teleportation of high-dimensional quantum states, using the trainable quantum autoencoders. High fidelities are achieved between the input qutrit and the qutrit decoded from the teleported state. Our results present a promising avenue towards realizing deep optical neural networks and challenging quantum computing tasks with dedicated integrated silicon photonic circuits.
URI: https://hdl.handle.net/10356/154812
DOI: 10.32657/10356/154812
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: embargo_20240110
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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  Until 2024-01-10
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