Coupled waveguides geometry retrieval using neural networks

Tom Coen; Tom Coen; Tom Coen; Hadar Greener; Hadar Greener; Michael Mrejen; Michael Mrejen; Lior Wolf; Lior Wolf; Haim Suchowski; Haim Suchowski

doi:10.1364/CLEO_AT.2020.JTh2B.2

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2020),
paper JTh2B.2
•https://doi.org/10.1364/CLEO_AT.2020.JTh2B.2

Coupled waveguides geometry retrieval using neural networks

Tom Coen, Hadar Greener, Michael Mrejen, Lior Wolf, and Haim Suchowski

CLEO: Science and Innovations 2020

Washington, DC United States
10–15 May 2020
ISBN: 978-1-943580-76-7

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Joint Poster Session 13 (JTh2B)

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T. Coen, H. Greener, M. Mrejen, L. Wolf, and H. Suchowski, "Coupled waveguides geometry retrieval using neural networks," in Conference on Lasers and Electro-Optics, OSA Technical Digest (Optica Publishing Group, 2020), paper JTh2B.2.

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Abstract

This work presents a data driven method to retrieve the geometry of a coupled waveguide system from the measured intensity of the electric field. It is shown that neural networks perform better than kNN regression.

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