Space-efficient optical computing with an integrated chip diffractive neural network
Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more important for realizing optical neural networks (ONNs) capable of advanced optical computing. Traditional experimental implementations need N2 units such as Mach-Zehnder interferometers (MZIs) for an input...
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Main Authors: | Zhu, Hanhan, Zou, Jun, Zhang, Hengyi, Shi, Yuzhi, Luo, Shibo, Wang, N., Cai, H., Wan, Liangxia, Wang, Bo, Jiang, Xudong, Thompson, Jayne, Luo, Xianshu, Zhou, Xuanhe, Xiao, Limin, Huang, W., Patrick, Lento, Gu, Mile, Kwek, Leong Chuan, Liu, Ai Qun |
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Other Authors: | School of Physical and Mathematical Sciences |
Format: | Article |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/160409 |
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Institution: | Nanyang Technological University |
Language: | English |
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