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基于硅微环和时间复用的水库计算,用于二进制和模拟运算。

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

作者信息

Borghi Massimo, Biasi Stefano, Pavesi Lorenzo

机构信息

Nanoscience Laboratory, Department of Physics, University of Trento, Via Sommarive 14, 38123, Trento, Italy.

出版信息

Sci Rep. 2021 Aug 2;11(1):15642. doi: 10.1038/s41598-021-94952-5.

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.

摘要

储层计算(RC)的光子实现有望通过适度的训练努力达到超高的运行带宽。一些光电演示报告了在语音识别、物体分类和时间序列预测等艰巨任务方面的先进性能。在空间和时间上扩展这些系统在控制复杂性、尺寸和功率需求方面面临挑战,而集成光学解决方案可以缓解这些挑战。硅光子学可能是实现这一目标的颠覆性技术。然而,迄今为止的实验演示主要集中在空间分布的储层上,其中大量使用分束器/合束器以及互连损耗限制了节点数量。在此,我们提出并验证了一种基于硅微环(MR)和时间复用的全光RC方案。输入层编码在泵浦光束的强度中,该强度被非线性转移到MR中的自由载流子浓度,并印刻在次级探测上。我们利用自由载流子动力学创建了一个具有50个虚拟节点的链状储层拓扑结构。我们通过解决两个非平凡任务:延迟异或和鸢尾花分类,给出了RC的概念验证演示。这构成了基本构建模块,利用有限的资源集可以实现具有数千个节点的更大的混合时空储层。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e99/8329232/c94dc538cfc9/41598_2021_94952_Fig1_HTML.jpg

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