Tackling multimodal device distributions in inverse photonic design using invertible neural networks

Tackling multimodal device distributions in inverse photonic design using invertible neural networks

We show how conditional generative neural networks can be used to efficiently find nanophotonic devices with desired properties, also known as inverse photonic design. Machine learning has emerged as a promising approach to overcome limitations imposed by the dimensionality and topology of the param...

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Bibliographic Details
Main Authors: Michel Frising, Jorge Bravo-Abad, Ferry Prins
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:Machine Learning: Science and Technology
Subjects:
nanotechnology
inverse design
multimodality
machine learning
invertible neural networks
nanophotonics
Online Access:https://doi.org/10.1088/2632-2153/acd619

Internet

https://doi.org/10.1088/2632-2153/acd619

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