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Silicon-Based Metastructure Optical Scattering Multiply–Accumulate Computation Chip
Optical neural networks (ONN) have become the most promising solution to replacing electronic neural networks, which have the advantages of large bandwidth, low energy consumption, strong parallel processing ability, and super high speed. Silicon-based micro-nano integrated photonic platforms have d...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268426/ https://www.ncbi.nlm.nih.gov/pubmed/35807971 http://dx.doi.org/10.3390/nano12132136 |
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author | Liu, Xu Zhu, Xudong Wang, Chunqing Cao, Yifan Wang, Baihang Ou, Hanwen Wu, Yizheng Mei, Qixun Zhang, Jialong Cong, Zhe Liu, Rentao |
author_facet | Liu, Xu Zhu, Xudong Wang, Chunqing Cao, Yifan Wang, Baihang Ou, Hanwen Wu, Yizheng Mei, Qixun Zhang, Jialong Cong, Zhe Liu, Rentao |
author_sort | Liu, Xu |
collection | PubMed |
description | Optical neural networks (ONN) have become the most promising solution to replacing electronic neural networks, which have the advantages of large bandwidth, low energy consumption, strong parallel processing ability, and super high speed. Silicon-based micro-nano integrated photonic platforms have demonstrated good compatibility with complementary metal oxide semiconductor (CMOS) processing. Therefore, without completely changing the existing silicon-based fabrication technology, optoelectronic hybrid devices or all-optical devices of better performance can be achieved on such platforms. To meet the requirements of smaller size and higher integration for silicon photonic computing, the topology of a four-channel coarse wavelength division multiplexer (CWDM) and an optical scattering unit (OSU) are inversely designed and optimized by Lumerical software. Due to the random optical power splitting ratio and incoherency, the intensities of different input signals from CWDM can be weighted and summed directly by the subsequent OSU to accomplish arbitrary multiply–accumulate (MAC) operations, therefore supplying the core foundation for scattering ONN architecture. |
format | Online Article Text |
id | pubmed-9268426 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92684262022-07-09 Silicon-Based Metastructure Optical Scattering Multiply–Accumulate Computation Chip Liu, Xu Zhu, Xudong Wang, Chunqing Cao, Yifan Wang, Baihang Ou, Hanwen Wu, Yizheng Mei, Qixun Zhang, Jialong Cong, Zhe Liu, Rentao Nanomaterials (Basel) Article Optical neural networks (ONN) have become the most promising solution to replacing electronic neural networks, which have the advantages of large bandwidth, low energy consumption, strong parallel processing ability, and super high speed. Silicon-based micro-nano integrated photonic platforms have demonstrated good compatibility with complementary metal oxide semiconductor (CMOS) processing. Therefore, without completely changing the existing silicon-based fabrication technology, optoelectronic hybrid devices or all-optical devices of better performance can be achieved on such platforms. To meet the requirements of smaller size and higher integration for silicon photonic computing, the topology of a four-channel coarse wavelength division multiplexer (CWDM) and an optical scattering unit (OSU) are inversely designed and optimized by Lumerical software. Due to the random optical power splitting ratio and incoherency, the intensities of different input signals from CWDM can be weighted and summed directly by the subsequent OSU to accomplish arbitrary multiply–accumulate (MAC) operations, therefore supplying the core foundation for scattering ONN architecture. MDPI 2022-06-21 /pmc/articles/PMC9268426/ /pubmed/35807971 http://dx.doi.org/10.3390/nano12132136 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Xu Zhu, Xudong Wang, Chunqing Cao, Yifan Wang, Baihang Ou, Hanwen Wu, Yizheng Mei, Qixun Zhang, Jialong Cong, Zhe Liu, Rentao Silicon-Based Metastructure Optical Scattering Multiply–Accumulate Computation Chip |
title | Silicon-Based Metastructure Optical Scattering Multiply–Accumulate Computation Chip |
title_full | Silicon-Based Metastructure Optical Scattering Multiply–Accumulate Computation Chip |
title_fullStr | Silicon-Based Metastructure Optical Scattering Multiply–Accumulate Computation Chip |
title_full_unstemmed | Silicon-Based Metastructure Optical Scattering Multiply–Accumulate Computation Chip |
title_short | Silicon-Based Metastructure Optical Scattering Multiply–Accumulate Computation Chip |
title_sort | silicon-based metastructure optical scattering multiply–accumulate computation chip |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268426/ https://www.ncbi.nlm.nih.gov/pubmed/35807971 http://dx.doi.org/10.3390/nano12132136 |
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