Tailoring Space-Time Nonlocality for Event-Based Image Processing Metasurfaces

Analog computation with passive optical components can enhance processing speeds and reduce power consumption, recently attracting renewed interest thanks to the opportunities enabled by metasurfaces. Basic image processing tasks, such as spatial differentiation, have been recently demonstrated based on engineered nonlocalities in metasurfaces, but next-generation computational schemes require more advanced capabilities. Here, by simultaneously tailoring the nonlocal electromagnetic response of a metasurface in space and time, we demonstrate a passive ultrathin silicon-based device that performs mixed spatiotemporal differentiation of input images, realizing event-based edge detection. The metasurface performs spatial differentiation only when the input image is evolving in time, resulting in spatiotemporal image processing on subpicosecond timescales. Moreover, the metasurface design can be tailored to selectively enhance objects moving at desired speeds. Our results point towards fully passive processing of spatiotemporal signals, for highly compact neuromorphic cameras.