Controllable gliders in a nanomagnetic metamaterial

Abstract

Abstract Artificial Spin Ice (ASI) are promising metamaterials for neuromorphic computing, composed of interacting nanomagnets arranged in the plane. Every computing device requires the ability to transform, transmit and store information. While ASI excel at data transformation, their transmission and storage capabilities have been lacking. Here, we take inspiration from Cellular Automata, where information transmission and storage can be realised by the glider, a simple moving structure. Employing an evolutionary algorithm, we discover the snake, a glider in pinwheel ASI. The snake is controlled by a global field protocol, providing precise manipulation of a magnetic texture on the order of 100 nm. We present the snake, both in simulation and experimentally, investigate the mechanism behind its movement and its robustness to disorder. Finally, we demonstrate how the snake can be exploited for computation and memory. The snake enables the integration of information transmission, storage and transformation into one magnetic substrate, unlocking the potential for ultra-low power computing devices.