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arXiv 2402.09135physics.opticscs.LG
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基于高非线性波导中四波混频的非常规计算

Unconventional Computing based on Four Wave Mixing in Highly Nonlinear Waveguides

University of the Aegean(爱琴大学);University of West Attica(西阿提卡大学)

Kostas Sozos, Stavros Deligiannidis, Charis Mesaritakis, Adonis Bogris

AI总结:

提出基于高非线性波导四波混频效应的光子非常规加速器,直接在光域进行非线性信号处理,在混沌预测和全光非线性补偿中表现优于机器学习算法,并可用作可重构非线性激活模块。

摘要:

在这项工作中,我们数值分析了一种基于高非线性波导中四波混频效应的光子非常规加速器。该方案可作为完全模拟系统,直接在光域进行非线性信号处理。通过利用丰富的Kerr诱导非线性,可生成输入信号的多种非线性变换,用于解决复杂的非线性任务。我们首先评估了该方案在Santa-Fe混沌时间序预测中的性能。该处理器的真正威力在光通信场景下的全光非线性补偿中得以展现,其结果优于强机器学习算法,且降低了功耗和计算复杂度。最后,我们展示了FWM模块如何用作可重构的非线性激活模块,能够复现sigmoid或修正线性单元等特征函数。

英文摘要:

In this work we numerically analyze a photonic unconventional accelerator based on the four-wave mixing effect in highly nonlinear waveguides. The proposed scheme can act as a fully analogue system for nonlinear signal processing directly in the optical domain. By exploiting the rich Kerr-induced nonlinearities, multiple nonlinear transformations of an input signal can be generated and used for solving complex nonlinear tasks. We first evaluate the performance of our scheme in the Santa-Fe chaotic time-series prediction. The true power of this processor is revealed in the all-optical nonlinearity compensation in an optical communication scenario where we provide results superior to those offered by strong machine learning algorithms with reduced power consumption and computational complexity. Finally, we showcase how the FWM module can be used as a reconfigurable nonlinear activation module being capable of reproducing characteristic functions such as sigmoid or rectified linear unit.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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