Practical Machine Learning for Multi-Scale Optical Design

Pawel Latawiec; Ali Forouzmand; Mohammad Mahdi Salary

doi:10.1364/FIO.2023.FW1A.2

Frontiers in Optics + Laser Science 2023 (FiO, LS)
Technical Digest Series (Optica Publishing Group, 2023),
paper FW1A.2
•https://doi.org/10.1364/FIO.2023.FW1A.2

Practical Machine Learning for Multi-Scale Optical Design

Pawel Latawiec, Ali Forouzmand, and Mohammad Mahdi Salary

Frontiers in Optics 2023

Tacoma, Washington United States
9–12 October 2023
ISBN: 978-1-957171-29-6

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Machine Learning Theme: Metaoptics and Machine Learning (FW1A)

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P. Latawiec, A. Forouzmand, and M. M. Salary, "Practical Machine Learning for Multi-Scale Optical Design," in Frontiers in Optics + Laser Science 2023 (FiO, LS), Technical Digest Series (Optica Publishing Group, 2023), paper FW1A.2.

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Abstract

The tooling available to optical system designers has advanced light years beyond first-order optics and raytracing, but these techniques have not fallen by the wayside. We discuss the practical synthesis of proven methods with cutting-edge machine learning models to tackle problems in meta-optic design, tolerancing, and yield analysis as relevant to industry.

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