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An On-Demand Inverse Design Method for Nanophotonic Devices Based on Generative Model and Hybrid Optimization Algorithm

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Abstract

The inverse design of nanophotonic devices has been widely concerned by researchers, and on-demand design is the difficulty of inverse design. In inverse design, researchers usually define a target spectrum based on the performance indicators and experiences and then inverse design the structural parameters from the target spectrum. Due to the uncertainty of inverse design and “one-to-many” problem, it is not usually possible to guarantee that the target spectrum is sure to correspond to a real nanostructure. In order to solve these problems, an inverse design method combining generative model and genetic algorithm is proposed in this paper. Before the inverse design, the real spectrum is compressed into a latent space by the generation model, and then, the target spectrum is decoded from the latent space according to the performance index. Finally, the hybrid optimization algorithm combining genetic algorithm and forward prediction network is used to optimize the generated spectrum. The design method follows the process from performance indicators to target spectrum to structural parameter, and we successfully realized the inverse design of multilayer nanofilms on demand by using this method in the experimental part. The inverse design method proposed in this paper provides a possible solution for the inverse design of nanophotonic devices on demand.

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Data Availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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Funding

This work is supported by the National Natural Science Foundation of China (61967007, 61963016, 62366015) and the Key Research and Development Program of Jiangxi Province (20201BBF61012).

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Authors and Affiliations

  1. Department of Information Engineering, East China Jiaotong University, Nanchang, 330013, China

    Lu Zhu, Yue Li, Zhikang Yang, Danlong Zong & Yuanyuan Liu

Authors
  1. Lu Zhu
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  2. Yue Li
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  3. Zhikang Yang
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  4. Danlong Zong
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  5. Yuanyuan Liu
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Contributions

All authors contributed to the conception and design of the study. Data set collection and simulation analysis were performed by (Yue Li) and (Danlong Zong), the first draft of the paper was written by (Yue Li) and (Lu Zhu), the experimental part was performed by (Zhikang Yang), and the revision and integration of the paper was performed by (Yuanyuan Liu). All authors have commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yuanyuan Liu.

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Zhu, L., Li, Y., Yang, Z. et al. An On-Demand Inverse Design Method for Nanophotonic Devices Based on Generative Model and Hybrid Optimization Algorithm. Plasmonics (2023). https://doi.org/10.1007/s11468-023-02075-6

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