All‐Optical Multiplexed Meta‐Differentiator for Tri‐Mode Surface Morphology Observation

Abstract Current optical differentiators are generally limited to realizing a single differential function once fabricated. Herein, a minimalist strategy in designing multiplexed differentiators (1^st‐ and 2^nd‐order differentiations), implemented with a Malus metasurface consisting of single‐sized nanostructures is proposed, thus improving the functionality of optical computing devices without the cost of complex design and nanofabrication. It is found that the proposed meta‐differentiator exhibits excellent differential‐computation performance and can be used for simultaneous outline detection and edge positioning of objects, corresponding to the functions of the 1^st‐ and 2^nd‐order differentiations respectively. Experiments with biological specimens showcase that boundaries of biological tissues can not only be identified, but also the edge information for realizing high‐precision edge positioning is highlighted. The study provides a paradigm in designing all‐optical multiplexed computing meta‐devices, and initiates tri‐mode surface morphology observation by combining meta‐differentiator with optical microscopes, which can find their applications in advanced biological imaging, large‐scale defect detection, and high‐speed pattern recognition, etc.