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作者机构:Photonics Initiative Advanced Science Research Center City University of New York New York NY 10031 USA The Institute of Optics University of Rochester Rochester NY 14627 USA Physics Program Graduate Center of the City University of New York New York NY 10016 USA
出 版 物:《npj Nanophotonics》
年 卷 期:2024年第1卷第1期
页 面:1-9页
摘 要:Nonlocal metasurfaces have recently enabled an ultra-compact, low-power and high-speed platform to perform analog image processing. While several computational tasks have been demonstrated based on this platform, most of the previous studies have focused only on spatial operations, such as spatial differentiation and edge detection. Here, we demonstrate that metasurfaces with temporal nonlocalities – that is, with a tailored dispersive response – can be used to implement time-domain signal processing in deeply subwavelength footprints. In particular, we experimentally demonstrate a passive metasurface performing first-order differentiation of input signals with high-fidelity and high-efficiency. We also show that this approach is prone to scalability and cascaded computation. Our work paves the way to a new generation of ultra-compact, passive devices for all-optical computation, with applications in neural networks and neuromorphic computing.