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High-speed multiwavelength adjoint optimization with surrogate solver
- Seo, Joonhyuk;
- Kang, Chanik;
- Seo, Dongjin;
- Chung, Haejun
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0초록
We propose a neural network designed to learn the field simulation across multiple wavelengths. The model shows high accuracy in predicted fields and rapidly performs adjoint optimization for various wavelengths.
키워드
Adjoint optimizations; Field simulation; High Speed; High-accuracy; Learn+; Multiple wavelengths; Multiwavelength; Neural-networks
- 제목
- High-speed multiwavelength adjoint optimization with surrogate solver
- 저자
- Seo, Joonhyuk; Kang, Chanik; Seo, Dongjin; Chung, Haejun
- 발행일
- 2024-09
- 유형
- Proceedings Paper
- 저널명
- 2024 CONFERENCE ON LASERS AND ELECTRO-OPTICS PACIFIC RIM, CLEO-PR
- 페이지
- 1 ~ 2
- 언어
- ENG
- 출판사
- IEEE
- 발행국가
- 미국
- 분량
- 2 페이지
- ISSN
- P 2997-7053