Magnetic skyrmion artificial synapse for neuromorphic computing
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.
Cite
@article{arxiv.1907.00957,
title = {Magnetic skyrmion artificial synapse for neuromorphic computing},
author = {Kyung Mee Song and Jae-Seung Jeong and Biao Pan and Xichao Zhang and Jing Xia and Sun Kyung Cha and Tae-Eon Park and Kwangsu Kim and Simone Finizio and Joerg Raabe and Joonyeon Chang and Yan Zhou and Weisheng Zhao and Wang Kang and Hyunsu Ju and Seonghoon Woo},
journal= {arXiv preprint arXiv:1907.00957},
year = {2020}
}
Comments
11 pages, 4 figures