Mie Resonance-based Meta-atom Design with Machine Learning Method
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Li, W; Sedeh, HB; Padilla, WJ; Malof, J; Litchinitser, NM
Published in: 2023 Conference on Lasers and Electro-Optics, CLEO 2023
January 1, 2023
Forward prediction machine learning models were developed to predict the scattering behaviors and electromagnetic field of meta-atoms, while an inverse design model was built for reconstructing meta-atoms under the guidance of multipole expansion theory.
Duke Scholars
Published In
2023 Conference on Lasers and Electro-Optics, CLEO 2023
Publication Date
January 1, 2023
Citation
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MLA
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Li, W., Sedeh, H. B., Padilla, W. J., Malof, J., & Litchinitser, N. M. (2023). Mie Resonance-based Meta-atom Design with Machine Learning Method. In 2023 Conference on Lasers and Electro-Optics, CLEO 2023.
Li, W., H. B. Sedeh, W. J. Padilla, J. Malof, and N. M. Litchinitser. “Mie Resonance-based Meta-atom Design with Machine Learning Method.” In 2023 Conference on Lasers and Electro-Optics, CLEO 2023, 2023.
Li W, Sedeh HB, Padilla WJ, Malof J, Litchinitser NM. Mie Resonance-based Meta-atom Design with Machine Learning Method. In: 2023 Conference on Lasers and Electro-Optics, CLEO 2023. 2023.
Li, W., et al. “Mie Resonance-based Meta-atom Design with Machine Learning Method.” 2023 Conference on Lasers and Electro-Optics, CLEO 2023, 2023.
Li W, Sedeh HB, Padilla WJ, Malof J, Litchinitser NM. Mie Resonance-based Meta-atom Design with Machine Learning Method. 2023 Conference on Lasers and Electro-Optics, CLEO 2023. 2023.
Published In
2023 Conference on Lasers and Electro-Optics, CLEO 2023
Publication Date
January 1, 2023