A Space-efficient Optical Computing Chip Based on Diffractive Neural Network

H. H. Zhu; J. Zou; H. Zhang; H. Cai; A. Q. Liu

A Space-efficient Optical Computing Chip Based on Diffractive Neural Network

H. H. Zhu
, J. Zou
, H. Zhang
, H. Cai
, A. Q. Liu

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

A the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing is demonstrated and achieved ~ 10-fold reduction in both footprint and energy consumption. It has high potential in optical-artificial-intelligence.

Original language	English
Title of host publication	2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781957171050
Publication status	Published - May 2022
Externally published	Yes
Event	2022 Conference on Lasers and Electro-Optics, CLEO 2022 - San Jose, United States Duration: 15 May 2022 → 20 May 2022

Publication series

Name	2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings

Conference

Conference	2022 Conference on Lasers and Electro-Optics, CLEO 2022
Country/Territory	United States
City	San Jose
Period	15/05/22 → 20/05/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

ASJC Scopus subject areas

Instrumentation
Spectroscopy
Biomedical Engineering
Electrical and Electronic Engineering
Management, Monitoring, Policy and Law
Materials Science (miscellaneous)
Acoustics and Ultrasonics
Atomic and Molecular Physics, and Optics

Cite this

@inproceedings{fa81b4e25cf640ec9ead54c1c6b632e7,

title = "A Space-efficient Optical Computing Chip Based on Diffractive Neural Network",

abstract = "A the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing is demonstrated and achieved \textasciitilde{} 10-fold reduction in both footprint and energy consumption. It has high potential in optical-artificial-intelligence.",

author = "Zhu, \{H. H.\} and J. Zou and H. Zhang and H. Cai and Liu, \{A. Q.\}",

note = "Funding Information: This work was supported by the Singapore National Research Foundation under the Competitive Research Program (NRFCRP13-2014-01) and the Singapore Ministry of Education (MOE) Tier 3 grant (MOE2017-T3-1-001). Publisher Copyright: {\textcopyright} Optica Publishing Group 2022, {\textcopyright} 2022 The Author(s); 2022 Conference on Lasers and Electro-Optics, CLEO 2022 ; Conference date: 15-05-2022 Through 20-05-2022",

year = "2022",

month = may,

language = "English",

series = "2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings",

}

Zhu, HH, Zou, J, Zhang, H, Cai, H & Liu, AQ 2022, A Space-efficient Optical Computing Chip Based on Diffractive Neural Network. in 2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings., SF1C.1, 2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2022 Conference on Lasers and Electro-Optics, CLEO 2022, San Jose, United States, 15/05/22.

A Space-efficient Optical Computing Chip Based on Diffractive Neural Network. / Zhu, H. H.; Zou, J.; Zhang, H. et al.
2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. SF1C.1 (2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - A Space-efficient Optical Computing Chip Based on Diffractive Neural Network

AU - Zhu, H. H.

AU - Zou, J.

AU - Zhang, H.

AU - Cai, H.

AU - Liu, A. Q.

N1 - Funding Information: This work was supported by the Singapore National Research Foundation under the Competitive Research Program (NRFCRP13-2014-01) and the Singapore Ministry of Education (MOE) Tier 3 grant (MOE2017-T3-1-001). Publisher Copyright: © Optica Publishing Group 2022, © 2022 The Author(s)

PY - 2022/5

Y1 - 2022/5

N2 - A the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing is demonstrated and achieved ~ 10-fold reduction in both footprint and energy consumption. It has high potential in optical-artificial-intelligence.

AB - A the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing is demonstrated and achieved ~ 10-fold reduction in both footprint and energy consumption. It has high potential in optical-artificial-intelligence.

UR - https://www.scopus.com/pages/publications/85139908885

M3 - Conference article published in proceeding or book

AN - SCOPUS:85139908885

T3 - 2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings

BT - 2022 Conference on Lasers and Electro-Optics, CLEO 2022 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 Conference on Lasers and Electro-Optics, CLEO 2022

Y2 - 15 May 2022 through 20 May 2022

ER -

A Space-efficient Optical Computing Chip Based on Diffractive Neural Network

Abstract

Publication series

Conference

UN SDGs

ASJC Scopus subject areas

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