Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations

Abstract Photonic implementations of reservoir computing (RC) promise to reach ultra-high bandwidth of operation with moderate training efforts. Several optoelectronic demonstrations reported state of the art performances for hard tasks as speech recognition, object classification and time series pr...

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Autores principales:	Massimo Borghi, Stefano Biasi, Lorenzo Pavesi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c712ec5af1eb4eafa98a58af37b7d010
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spelling	oai:doaj.org-article:c712ec5af1eb4eafa98a58af37b7d0102021-12-02T17:06:24ZReservoir computing based on a silicon microring and time multiplexing for binary and analog operations10.1038/s41598-021-94952-52045-2322https://doaj.org/article/c712ec5af1eb4eafa98a58af37b7d0102021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94952-5https://doaj.org/toc/2045-2322Abstract Photonic implementations of reservoir computing (RC) promise to reach ultra-high bandwidth of operation with moderate training efforts. Several optoelectronic demonstrations reported state of the art performances for hard tasks as speech recognition, object classification and time series prediction. Scaling these systems in space and time faces challenges in control complexity, size and power demand, which can be relieved by integrated optical solutions. Silicon photonics can be the disruptive technology to achieve this goal. However, the experimental demonstrations have been so far focused on spatially distributed reservoirs, where the massive use of splitters/combiners and the interconnection loss limits the number of nodes. Here, we propose and validate an all optical RC scheme based on a silicon microring (MR) and time multiplexing. The input layer is encoded in the intensity of a pump beam, which is nonlinearly transferred to the free carrier concentration in the MR and imprinted on a secondary probe. We harness the free carrier dynamics to create a chain-like reservoir topology with 50 virtual nodes. We give proof of concept demonstrations of RC by solving two nontrivial tasks: the delayed XOR and the classification of Iris flowers. This forms the basic building block from which larger hybrid spatio-temporal reservoirs with thousands of nodes can be realized with a limited set of resources.Massimo BorghiStefano BiasiLorenzo PavesiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Massimo Borghi Stefano Biasi Lorenzo Pavesi Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations
description	Abstract Photonic implementations of reservoir computing (RC) promise to reach ultra-high bandwidth of operation with moderate training efforts. Several optoelectronic demonstrations reported state of the art performances for hard tasks as speech recognition, object classification and time series prediction. Scaling these systems in space and time faces challenges in control complexity, size and power demand, which can be relieved by integrated optical solutions. Silicon photonics can be the disruptive technology to achieve this goal. However, the experimental demonstrations have been so far focused on spatially distributed reservoirs, where the massive use of splitters/combiners and the interconnection loss limits the number of nodes. Here, we propose and validate an all optical RC scheme based on a silicon microring (MR) and time multiplexing. The input layer is encoded in the intensity of a pump beam, which is nonlinearly transferred to the free carrier concentration in the MR and imprinted on a secondary probe. We harness the free carrier dynamics to create a chain-like reservoir topology with 50 virtual nodes. We give proof of concept demonstrations of RC by solving two nontrivial tasks: the delayed XOR and the classification of Iris flowers. This forms the basic building block from which larger hybrid spatio-temporal reservoirs with thousands of nodes can be realized with a limited set of resources.
format	article
author	Massimo Borghi Stefano Biasi Lorenzo Pavesi
author_facet	Massimo Borghi Stefano Biasi Lorenzo Pavesi
author_sort	Massimo Borghi
title	Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations
title_short	Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations
title_full	Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations
title_fullStr	Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations
title_full_unstemmed	Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations
title_sort	reservoir computing based on a silicon microring and time multiplexing for binary and analog operations
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c712ec5af1eb4eafa98a58af37b7d010
work_keys_str_mv	AT massimoborghi reservoircomputingbasedonasiliconmicroringandtimemultiplexingforbinaryandanalogoperations AT stefanobiasi reservoircomputingbasedonasiliconmicroringandtimemultiplexingforbinaryandanalogoperations AT lorenzopavesi reservoircomputingbasedonasiliconmicroringandtimemultiplexingforbinaryandanalogoperations
_version_	1718381637038768128

Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations

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