Magnetic skyrmion artificial synapse for neuromorphic computing

TL;DR

This paper demonstrates a room-temperature, electrically-operable skyrmion-based artificial synapse that can perform neuromorphic pattern recognition with high accuracy, advancing spintronics-based bio-inspired computing.

Contribution

It introduces a novel skyrmion-based artificial synapse device capable of mimicking biological synapses for neuromorphic computing at room temperature.

Findings

Achieved controlled creation, motion, detection, and deletion of skyrmions in ferrimagnetic multilayers.

Demonstrated neuromorphic pattern recognition with ~89% accuracy on handwritten data.

Showcased potential advantages of skyrmion synapses over existing technologies through simulations.

Abstract

Since the experimental discovery of magnetic skyrmions achieved one decade ago, there have been significant efforts to bring the virtual particles into all-electrical fully functional devices, inspired by their fascinating physical and topological properties suitable for future low-power electronics. Here, we experimentally demonstrate such a device: electrically-operating skyrmion-based artificial synaptic device designed for neuromorphic computing. We present that controlled current-induced creation, motion, detection and deletion of skyrmions in ferrimagnetic multilayers can be harnessed in a single device at room temperature to imitate the behaviors of biological synapses. Using simulations, we demonstrate that such skyrmion-based synapses could be used to perform neuromorphic pattern-recognition computing using handwritten recognition data set, reaching to the accuracy of ~89 percents, comparable to the software-based training accuracy of ~94 percents. Chip-level simulation then highlights the potential of skyrmion synapse compared to existing technologies. Our findings experimentally illustrate the basic concepts of skyrmion-based fully functional electronic devices while providing a new building block in the emerging field of spintronics-based bio-inspired computing.