Snakes in the Plane: Controllable Gliders in a Nanomagnetic Metamaterial

TL;DR

This paper introduces a new magnetic structure called the 'snake' glider in Artificial Spin Ice, enabling controlled information transmission and manipulation at nanoscale, with potential for ultra-low power computing devices.

Contribution

The paper discovers and demonstrates the 'snake' glider in pinwheel ASI, combining simulation and experimental validation, inspired by cellular automata for data transmission.

Findings

The 'snake' glider moves in a single direction driven by a global field.

Experimental and simulation results confirm the snake's motion mechanism.

The snake enables magnetic texture manipulation at ~100 nm resolution.

Abstract

The magnetic metamaterials known as Artificial Spin Ice (ASI) are promising candidates for neuromorphic computing, composed of vast numbers 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, reliable transmission and storage has proven difficult to achieve. Here, we take inspiration from the Cellular Automaton (CA), an abstract computing model reminiscent of ASI. In CAs, information transmission and storage can be realised by the ``glider'', a simple structure capable of propagating while maintaining its form. Employing an evolutionary algorithm, we search for gliders in pinwheel ASI and present the simplest glider discovered: the ``snake''. Driven by a global field protocol, the snake moves strictly in one direction, determined by its orientation. We demonstrate the snake, both in simulation and experimentally, and analyse the mechanism behind its motion. The snake provides a means of manipulating a magnetic texture in an ASI with resolution on the order of 100 nm, which could in turn be utilised to precisely control other magnetic phenomena. The integration of data transmission, storage and modification into the same magnetic substrate unlocks the potential for ultra-low power computing devices.