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arXiv · 2401.03564

Experimental Demonstration of Imperfection-Agnostic Local Learning Rules on Photonic Neural Networks with Mach-Zehnder Interferometric Meshes

Luis El Srouji·Mehmet Berkay On·Yun-Jhu Lee·Mahmoud Abdelghany·S. J. Ben Yoo
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Abstract

Mach-Zehnder Interferometric meshes are attractive for low-loss photonic matrix multiplication but are challenging to program. Using least-squares optimization of directional derivatives, we experimentally demonstrate that desired matrix updates can be implemented agnostic to hardware imperfections. \c{opyright} 2024 The Author(s)

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Luis El Srouji, Mehmet Berkay On, Yun-Jhu Lee, Mahmoud Abdelghany, S. J. Ben Yoo. 2024-01-07. Experimental Demonstration of Imperfection-Agnostic Local Learning Rules on Photonic Neural Networks with Mach-Zehnder Interferometric Meshes. https://arxiv.org/abs/2401.03564

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