A mixture-density-based tandem optimization network for on-demand inverse design of thin-film high reflectors

Deep learning (DL) has emerged as a promising tool for photonic inverse design. Nevertheless, despite the initial success in retrieving spectra of modest complexity with nearly instantaneous readout, DL-assisted design methods often underperform in accuracy compared with advanced optimization techni...

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Auteurs principaux: Unni Rohit, Yao Kan, Han Xizewen, Zhou Mingyuan, Zheng Yuebing
Format: article
Langue:EN
Publié: De Gruyter 2021
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Accès en ligne:https://doaj.org/article/3a69ffa99f924ab8bbdc9fb92a288007
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