Computation at the speed of light: metamaterials for all-optical calculations and neural networks

被引:53
|
作者
Badloe, Trevon [1 ]
Lee, Seokho [1 ]
Rho, Junsuk [1 ,2 ,3 ]
机构
[1] Pohang Univ Sci & Technol, Dept Mech Engn, Pohang, South Korea
[2] Pohang Univ Sci & Technol, Dept Chem Engn, Pohang, South Korea
[3] POSCO POSTECH RIST Convergence Res Ctr Flat Opt &, Pohang, South Korea
来源
ADVANCED PHOTONICS | 2022年 / 4卷 / 06期
基金
新加坡国家研究基金会;
关键词
photonic computing; all-optical calculation; optical neural network; programmable metasurface; SPATIAL DIFFERENTIATION; MATHEMATICAL OPERATIONS; LAPLACE OPERATOR; EDGE-DETECTION; PHASE; METASURFACE; DESIGN; GENERATION; PHOTONICS; SLAB;
D O I
10.1117/1.AP.4.6.064002
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The explosion in the amount of information that is being processed is prompting the need for new computing systems beyond existing electronic computers. Photonic computing is emerging as an attractive alternative due to performing calculations at the speed of light, the change for massive parallelism, and also extremely low energy consumption. We review the physical implementation of basic optical calculations, such as differentiation and integration, using metamaterials, and introduce the realization of all-optical artificial neural networks. We start with concise introductions of the mathematical principles behind such optical computation methods and present the advantages, current problems that need to be overcome, and the potential future directions in the field. We expect that our review will be useful for both novice and experienced researchers in the field of all-optical computing platforms using metamaterials.
引用
收藏
页数:21
相关论文
共 50 条
  • [1] Computation at the speed of light:metamaterials for all-optical calculations and neural networks
    Trevon Badloe
    Seokho Lee
    Junsuk Rho
    Advanced Photonics , 2022, (06) : 27 - 47
  • [2] Role of all-optical neural networks
    Matuszewski, M.
    Prystupiuk, A.
    Opala, A.
    PHYSICAL REVIEW APPLIED, 2024, 21 (01)
  • [3] Scalability of All-Optical Neural Networks Based on Spatial Light Modulators
    Zuo, Ying
    Zhao, Yujun
    Chen, You-Chiuan
    Du, Shengwang
    Liu, Junwei
    PHYSICAL REVIEW APPLIED, 2021, 15 (05):
  • [4] Hopfield neural networks for routing in all-optical networks
    Bastos-Filho, Carmelo J. A.
    Santana, Robson A.
    Silva, Dennis R. C.
    Martins-Filho, Joaquim F.
    Chaves, Daniel A. R.
    2010 12TH INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS (ICTON), 2011,
  • [5] A NEW OPTICAL NEURON DEVICE FOR ALL-OPTICAL NEURAL NETWORKS
    AKIYAMA, K
    TAKIMOTO, A
    MIYAUCHI, M
    KURATOMI, Y
    ASAYAMA, J
    OGAWA, H
    JAPANESE JOURNAL OF APPLIED PHYSICS PART 1-REGULAR PAPERS SHORT NOTES & REVIEW PAPERS, 1991, 30 (12B): : 3887 - 3892
  • [6] All-Optical WDM Recurrent Neural Networks With Gating
    Mourgias-Alexandris, George
    Dabos, George
    Passalis, Nikolaos
    Totovic, Angelina
    Tefas, Anastasios
    Pleros, Nikos
    IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS, 2020, 26 (05)
  • [7] All-optical computing based on convolutional neural networks
    Kun Liao
    Ye Chen
    Zhongcheng Yu
    Xiaoyong Hu
    Xingyuan Wang
    Cuicui Lu
    Hongtao Lin
    Qingyang Du
    Juejun Hu
    Qihuang Gong
    Opto-Electronic Advances, 2021, 4 (11) : 50 - 58
  • [8] All-Optical Assay to Study Biological Neural Networks
    Saber, Wardiya Afshar
    Gasparoli, Federico M.
    Dirks, Marjet G.
    Gunn-Moore, Frank J.
    Antkowiak, Maciej
    FRONTIERS IN NEUROSCIENCE, 2018, 12
  • [9] All-Optical Signal Processing for UltraHigh Speed Optical Systems and Networks
    Yan, Lianshan
    Willner, Alan E.
    Wu, Xiaoxia
    Yi, Anlin
    Bogoni, Antonella
    Chen, Z. -Y.
    Jiang, H. -Y.
    JOURNAL OF LIGHTWAVE TECHNOLOGY, 2012, 30 (24) : 3760 - 3770
  • [10] All-optical buffering using laser neural networks
    Liu, Y
    Hill, MT
    de Waardt, H
    Khoe, GD
    Dorren, HJS
    IEEE PHOTONICS TECHNOLOGY LETTERS, 2003, 15 (04) : 596 - 598