Marcus Tamura, Hugh Morison, Alexander N. Tait, Bhavin J. Shastri
{"title":"设计单片硅绝缘体谐振器尖峰神经元","authors":"Marcus Tamura, Hugh Morison, Alexander N. Tait, Bhavin J. Shastri","doi":"10.1038/s42005-024-01769-5","DOIUrl":null,"url":null,"abstract":"Increasingly, artificial intelligent systems look to neuromorphic photonics for its speed and its low loss, high bandwidth interconnects. Silicon photonics has shown promise to enable the creation of large scale neural networks. Here, we propose a monolithic silicon opto-electronic resonator spiking neuron. Existing designs of photonic spiking neurons have difficulty scaling due to their dependence on certain nonlinear effects, materials, and devices. The design discussed here uses optical feedback from the transmission of a continuously pumped microring PN modulator to achieve excitable dynamics. It is cascadable, capable of operating at GHz speeds, and compatible with wavelength-division multiplexing schemes for linear weighting. It is a Class 2 excitable device via a subcritical Hopf bifurcation constructed from devices commonly found in many silicon photonic chip foundries. Silicon photonics can be used to create high-speed large-scale neuromorphic systems for artificial intelligent tasks. Here, the authors discuss the design details and behavior of a resonator spiking neuron that can be fabricated in a commercial silicon photonics foundry process.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01769-5.pdf","citationCount":"0","resultStr":"{\"title\":\"Design of a monolithic silicon-on-insulator resonator spiking neuron\",\"authors\":\"Marcus Tamura, Hugh Morison, Alexander N. Tait, Bhavin J. Shastri\",\"doi\":\"10.1038/s42005-024-01769-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Increasingly, artificial intelligent systems look to neuromorphic photonics for its speed and its low loss, high bandwidth interconnects. Silicon photonics has shown promise to enable the creation of large scale neural networks. Here, we propose a monolithic silicon opto-electronic resonator spiking neuron. Existing designs of photonic spiking neurons have difficulty scaling due to their dependence on certain nonlinear effects, materials, and devices. The design discussed here uses optical feedback from the transmission of a continuously pumped microring PN modulator to achieve excitable dynamics. It is cascadable, capable of operating at GHz speeds, and compatible with wavelength-division multiplexing schemes for linear weighting. It is a Class 2 excitable device via a subcritical Hopf bifurcation constructed from devices commonly found in many silicon photonic chip foundries. Silicon photonics can be used to create high-speed large-scale neuromorphic systems for artificial intelligent tasks. Here, the authors discuss the design details and behavior of a resonator spiking neuron that can be fabricated in a commercial silicon photonics foundry process.\",\"PeriodicalId\":10540,\"journal\":{\"name\":\"Communications Physics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s42005-024-01769-5.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications Physics\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.nature.com/articles/s42005-024-01769-5\",\"RegionNum\":1,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHYSICS, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications Physics","FirstCategoryId":"101","ListUrlMain":"https://www.nature.com/articles/s42005-024-01769-5","RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
Design of a monolithic silicon-on-insulator resonator spiking neuron
Increasingly, artificial intelligent systems look to neuromorphic photonics for its speed and its low loss, high bandwidth interconnects. Silicon photonics has shown promise to enable the creation of large scale neural networks. Here, we propose a monolithic silicon opto-electronic resonator spiking neuron. Existing designs of photonic spiking neurons have difficulty scaling due to their dependence on certain nonlinear effects, materials, and devices. The design discussed here uses optical feedback from the transmission of a continuously pumped microring PN modulator to achieve excitable dynamics. It is cascadable, capable of operating at GHz speeds, and compatible with wavelength-division multiplexing schemes for linear weighting. It is a Class 2 excitable device via a subcritical Hopf bifurcation constructed from devices commonly found in many silicon photonic chip foundries. Silicon photonics can be used to create high-speed large-scale neuromorphic systems for artificial intelligent tasks. Here, the authors discuss the design details and behavior of a resonator spiking neuron that can be fabricated in a commercial silicon photonics foundry process.
期刊介绍:
Communications Physics is an open access journal from Nature Research publishing high-quality research, reviews and commentary in all areas of the physical sciences. Research papers published by the journal represent significant advances bringing new insight to a specialized area of research in physics. We also aim to provide a community forum for issues of importance to all physicists, regardless of sub-discipline.
The scope of the journal covers all areas of experimental, applied, fundamental, and interdisciplinary physical sciences. Primary research published in Communications Physics includes novel experimental results, new techniques or computational methods that may influence the work of others in the sub-discipline. We also consider submissions from adjacent research fields where the central advance of the study is of interest to physicists, for example material sciences, physical chemistry and technologies.