Efficient multi-objective design method for optical coatings
•An efficient adaptive multi-objective design method for optical coating design is proposed.•The spectrum, group delay dispersion, and electric field distribution performances are improved simultaneously, achieving higher laser-induced damage threshold.•Gradient based algorithm and Deep learning met...
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| Vydáno v: | Optics and lasers in engineering Ročník 184; s. 108626 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.01.2025
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| ISSN: | 0143-8166 |
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| Abstract | •An efficient adaptive multi-objective design method for optical coating design is proposed.•The spectrum, group delay dispersion, and electric field distribution performances are improved simultaneously, achieving higher laser-induced damage threshold.•Gradient based algorithm and Deep learning method are employed to improve the design's universality and efficiency.
The modern design of high-performance optical coatings demands a comprehensive consideration of multiple properties. We propose an efficient multi-objective optimization method utilizing an adaptive weighted sum method, exploring the lexicographic optimization and geometry-based adaptive weights determination method. Broadband negative dispersive mirrors have been designed that demonstrates notable improvements in performances of spectrum, group delay dispersion and electric field distribution. In addition, we employ Deep-learning method to enhance the optimization. The mapping between different design parameters and results has been learned, which helps the optimization to directly approach the optimal design. It extends the novel method to diverse designs utilizing the similar kinds of merit functions and subsequently accelerates the design by 120 times. |
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| AbstractList | •An efficient adaptive multi-objective design method for optical coating design is proposed.•The spectrum, group delay dispersion, and electric field distribution performances are improved simultaneously, achieving higher laser-induced damage threshold.•Gradient based algorithm and Deep learning method are employed to improve the design's universality and efficiency.
The modern design of high-performance optical coatings demands a comprehensive consideration of multiple properties. We propose an efficient multi-objective optimization method utilizing an adaptive weighted sum method, exploring the lexicographic optimization and geometry-based adaptive weights determination method. Broadband negative dispersive mirrors have been designed that demonstrates notable improvements in performances of spectrum, group delay dispersion and electric field distribution. In addition, we employ Deep-learning method to enhance the optimization. The mapping between different design parameters and results has been learned, which helps the optimization to directly approach the optimal design. It extends the novel method to diverse designs utilizing the similar kinds of merit functions and subsequently accelerates the design by 120 times. |
| ArticleNumber | 108626 |
| Author | Wang, Zhanshan Zhang, Jinlong Dai, Jianglin Jiao, Hongfei Niu, Xinshang Ji, Xiaochuan Cheng, Xinbin |
| Author_xml | – sequence: 1 givenname: Jianglin surname: Dai fullname: Dai, Jianglin organization: MOE Key Laboratory of Advanced Micro-Structured Materials, Tongji University, Shanghai, 200092, China – sequence: 2 givenname: Xiaochuan surname: Ji fullname: Ji, Xiaochuan organization: MOE Key Laboratory of Advanced Micro-Structured Materials, Tongji University, Shanghai, 200092, China – sequence: 3 givenname: Xinshang surname: Niu fullname: Niu, Xinshang organization: MOE Key Laboratory of Advanced Micro-Structured Materials, Tongji University, Shanghai, 200092, China – sequence: 4 givenname: Hongfei surname: Jiao fullname: Jiao, Hongfei organization: MOE Key Laboratory of Advanced Micro-Structured Materials, Tongji University, Shanghai, 200092, China – sequence: 5 givenname: Xinbin surname: Cheng fullname: Cheng, Xinbin organization: MOE Key Laboratory of Advanced Micro-Structured Materials, Tongji University, Shanghai, 200092, China – sequence: 6 givenname: Zhanshan surname: Wang fullname: Wang, Zhanshan organization: MOE Key Laboratory of Advanced Micro-Structured Materials, Tongji University, Shanghai, 200092, China – sequence: 7 givenname: Jinlong surname: Zhang fullname: Zhang, Jinlong email: jinlong@tongji.edu.cn organization: MOE Key Laboratory of Advanced Micro-Structured Materials, Tongji University, Shanghai, 200092, China |
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| Keywords | Multi-objective design Deep-learning Adaptive weights Optical coatings |
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