Replacing electrons with photons is a compelling route toward high-speed,massively parallel,and low-power artificial intelligence computing.Recently,diffractive networks composed of phase surfaces were trained to perf...Replacing electrons with photons is a compelling route toward high-speed,massively parallel,and low-power artificial intelligence computing.Recently,diffractive networks composed of phase surfaces were trained to perform machine learning tasks through linear optical transformations.However,the existing architectures often comprise bulky components and,most critically,they cannot mimic the human brain for multitasking.Here,we demonstrate a multi-skilled diffractive neural network based on a metasurface device,which can perform on-chip multi-channel sensing and multitasking in the visible.The polarization multiplexing scheme of the subwavelength nanostructures is applied to construct a multi-channel classifier framework for simultaneous recognition of digital and fashionable items.The areal density of the artificial neurons can reach up to 6.25×10^(6)mm^(-2) multiplied by the number of channels.The metasurface is integrated with the mature complementary metal-oxide semiconductor imaging sensor,providing a chip-scale architecture to process information directly at physical layers for energy-efficient and ultra-fast image processing in machine vision,autonomous driving,and precision medicine.展开更多
基金support by the National Natural Science Foundarion of China(Grant No.52005175,5211101255)Natural gcience Foundation of Hunan Province of China(Grant No.2020J15059)+1 种基金Shenzhen Science and Technology Program(Grant No.RCBS20200714114855118)the Tribology Science Fund of State Key Laboratory of Tribology(SKILTKF20B04)。
文摘Replacing electrons with photons is a compelling route toward high-speed,massively parallel,and low-power artificial intelligence computing.Recently,diffractive networks composed of phase surfaces were trained to perform machine learning tasks through linear optical transformations.However,the existing architectures often comprise bulky components and,most critically,they cannot mimic the human brain for multitasking.Here,we demonstrate a multi-skilled diffractive neural network based on a metasurface device,which can perform on-chip multi-channel sensing and multitasking in the visible.The polarization multiplexing scheme of the subwavelength nanostructures is applied to construct a multi-channel classifier framework for simultaneous recognition of digital and fashionable items.The areal density of the artificial neurons can reach up to 6.25×10^(6)mm^(-2) multiplied by the number of channels.The metasurface is integrated with the mature complementary metal-oxide semiconductor imaging sensor,providing a chip-scale architecture to process information directly at physical layers for energy-efficient and ultra-fast image processing in machine vision,autonomous driving,and precision medicine.
