Deep learning has significantly accelerated the automation of metasurface design and reduced its dependence on empirical approaches.However,it still has not fully demonstrated its capabilities in the most challenging ...Deep learning has significantly accelerated the automation of metasurface design and reduced its dependence on empirical approaches.However,it still has not fully demonstrated its capabilities in the most challenging light field manipulation:3D holography.In this paper,we present a framework that integrates a fully connected forward prediction network with a 3D convolutional inverse design network to design terahertz 3D holographic metasurfaces.展开更多
基金National Natural Science Foundation of China(62027820,61975143,62375203,62175180,61735012)。
文摘Deep learning has significantly accelerated the automation of metasurface design and reduced its dependence on empirical approaches.However,it still has not fully demonstrated its capabilities in the most challenging light field manipulation:3D holography.In this paper,we present a framework that integrates a fully connected forward prediction network with a 3D convolutional inverse design network to design terahertz 3D holographic metasurfaces.
