# 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.

## Key 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.

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Source: https://tomesphere.com/paper/1907.00957