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Inverse design of nanophotonic devices using generative adversarial networks

Authors
Kim, WonsukKim, SoojeongLee, MinhyeokSeok, Junhee
Issue Date
10월-2022
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Generative adversarial networks; Inverse design; Maxwell equation; Deep learning
Citation
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, v.115
Indexed
SCIE
SCOPUS
Journal Title
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume
115
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/145717
DOI
10.1016/j.engappai.2022.105259
ISSN
0952-1976
Abstract
The efficient design of structures that exhibit desired properties is challenging across various engineering and scientific applications. Traditional methods employ experts in a specific domain to design new structures with desired properties. Then, simulations are performed for the designed structures to evaluate whether they show desired properties, and such a process is with until the structures exhibit desired properties. Advances in computing power and machine learning have made these simulations and optimizations faster, but challenges remain that the researchers must perform optimizations in each iteration, which generally takes time and cost. A new framework called inverse design has been studied to address the limitations. In inverse design, structures with desired properties can directly be constructed. In this work, as an inverse design framework, we introduce a controllable generative adversarial network (ControlGAN) based model to generate nanophotonic devices with user-defined properties. As a result, the proposed model outperforms other GAN-based models when the model is evaluated by producing structures with maximum transmittance at specific wavelengths. Specifically, the proposed model achieves a mean F1-score of 0.357, corresponding to a 260% improvement compared to the second-best model. The proposed model for inverse design can accelerate device designs not only in the field of nanophotonics but also in other nanostructures.
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SEOK, Jun hee
공과대학 (전기전자공학부)
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