Photonic perceptron based on a Kerr microcomb for high-speed, scalable, optical neural networks

被引：0

作者：

Xu, Xingyuan ^{[1
,2
]}

Tan, Mengxi ^{[1
]}

Wu, Jiayang ^{[1
]}

Boes, Andreas ^{[3
]}

Corcoran, Bill ^{[2
]}

Nguyen, Thach G. ^{[3
]}

Chu, Sai T. ^{[4
]}

Little, Brent E. ^{[5
]}

Morandotti, Roberto ^{[6
]}

Mitchell, Arnan ^{[3
]}

Hicks, Damien G. ^{[1
,7
]}

Moss, David J. ^{[1
]}

机构：

[1] Swinburne Univ Technol, Opt Sci Ctr, Hawthorn, Vic 3122, Australia

[2] Monash Univ, Dept Elect & Comp Syst Engn, Clayton, Vic 3800, Australia

[3] RMIT Univ, Sch Engn, Melbourne, Vic 3001, Australia

[4] City Univ Hong Kong, Dept Phys & Mat Sci, Tat Chee Ave, Hong Kong, Peoples R China

[5] Chinese Acad Sci, Xian Inst Opt & Precis Mech Precis Mech, Xian, Peoples R China

[6] INRS Energie Mat & Telecommun, 1650 Blvd Lionel Boulet, Varennes, PQ J3X 1S2, Canada

[7] Walter & Eliza Hall Inst Med Res, Bioinformat Div, Parkville, Vic 3052, Australia

来源：

2020 INTERNATIONAL TOPICAL MEETING ON MICROWAVE PHOTONICS (MWP 2020) | 2020年

关键词：

WAVELENGTH CONVERSION; HILBERT TRANSFORMER; TUNABLE DISPERSION; COMB; MICROWAVE; RF; FILTER; LASER; GENERATION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Optical artificial neural networks (ONNs) have significant potential for ultra-high computing speed and energy efficiency. We report a new approach to ONNs based on integrated Kerr micro-combs that is programmable, highly scalable and capable of reaching ultra-high speeds, demonstrating the building block of the ONN - a single neuron perceptron - by mapping synapses onto 49 wavelengths to achieve a single-unit throughput of 11.9 Giga-OPS at 8 bits per OP, or 95.2 Gbps. We test the perceptron on handwritten-digit recognition and cancer-cell detection - achieving over 90% and 85% accuracy, respectively. By scaling the perceptron to a deep learning network using off-the-shelf telecom technology we can achieve high throughput operation for matrix multiplication for real-time massive data processing.

引用

页码：220 / 224

页数：5

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