# Multifunctional movable-type coding metasurface enabling reconfigurable diffractive neural networks

## TL;DR

This paper introduces a reconfigurable optical computing system using movable-type metasurfaces for versatile applications like neural networks and sensing.

## Contribution

The novel contribution is the development of a movable-type coding metasurface enabling reconfigurable diffractive neural networks and multifunctional operations.

## Key findings

- The metasurface can switch between computing, holography, and sensing tasks through modular rearrangement.
- Replacing meta-atoms in the last layer adapts the system for different classification tasks like digits or letters.
- The system offers high flexibility and scalability for electromagnetic applications.

## Abstract

Optical computing holds significant promise across diverse applications due to its low latency, power efficiency, and multidimensional processing capabilities. However, current diffraction neural networks (DNNs) generally lack reconfigurability, limiting the scalability of the optical computing systems. Inspired by movable-type printing technology, here we propose a movable-type coding metasurface to enable multiple functionalities such as electromagnetic (EM) computing, holography, and sensing. By cascading multiple layers of the proposed metasurfaces, we further develop a movable-type reconfigurable DNN (MT-RDNN). It can be seamlessly adapted from handwritten digit to letter classification tasks by replacing the meta-atoms in the last hidden metasurface layer. Moreover, a single-layer movable-type coding metasurface can be reconfigured to perform EM holography and multi-person vital sign sensing through modular meta-atom rearrangement. Featuring simple reconfiguration, high flexibility, and modular scalability, the proposed movable-type coding metasurface enables versatile and reusable EM computing, holography, and sensing applications.

Inspired by movable-type printing, we propose movable-type coding metasurfaces for reconfigurable DNN in computing, holography, and sensing.