Comparison of Models for Training Optical Matrix Multipliers in Neuromorphic PICs

• URL: http://arxiv.org/abs/2111.14787v1
• Date: Tue, 23 Nov 2021 12:15:21 GMT
• Title: Comparison of Models for Training Optical Matrix Multipliers in Neuromorphic PICs
• Authors: Ali Cem, Siqi Yan, Uiara Celine de Moura, Yunhong Ding, Darko Zibar and Francesco Da Ros
• Abstract summary: We compare simple physics-based vs. data-driven neural-network-based models for offline training of programmable photonic chips. The neural-network model outperforms physics-based models for a chip with thermal crosstalk, yielding increased testing accuracy.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We experimentally compare simple physics-based vs. data-driven neural-network-based models for offline training of programmable photonic chips using Mach-Zehnder interferometer meshes. The neural-network model outperforms physics-based models for a chip with thermal crosstalk, yielding increased testing accuracy.

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