Eye accommodation-inspired neuro-metasurface focusing

The human eye, which relies on a flexible and controllable lens to focus light onto the retina, has inspired many scientific researchers to understand better and imitate the biological vision system. However, real-time environmental adaptability presents an enormous challenge for artificial eye-like focusing systems. Inspired by the mechanism of eye accommodation, we propose a supervised-evolving learning algorithm and design a neuro-metasurface focusing system. Driven by on-site learning, the system exhibits a rapid response to ever-changing incident waves and surrounding environments without any human intervention. Adaptive focusing is achieved in several scenarios with multiple incident wave sources and scattering obstacles. Our work demonstrates the unprecedented potential for real-time, fast, and complex electromagnetic (EM) wave manipulation for various purposes, such as achromatic, beam shaping, 6 G communication, and intelligent imaging. Here the authors propose for the first time the concept of supervised-evolving learning (SEL) and a corresponding SEL-driven adaptive focusing (SELAF) system. This metasurface can adaptively realize focusing at any specified position for waves incident from any direction. This work demonstrates unprecedented potential for tasks involving real-time, fast and complex electromagnetic wave manipulation.