AI Article Synopsis
- Nonlinear phenomena in physical systems, like skyrmions, show potential for low-energy brain-inspired computing, but their practical application has been underexplored.
- This study successfully demonstrates neuromorphic computing using skyrmions, achieving a high accuracy of 94.7% in recognizing handwritten digits and other patterns.
- The research highlights a positive correlation between recognition accuracy and the number of skyrmions, suggesting that the complexity and flexibility of skyrmion systems enhance their performance in neuromorphic computing applications.
Article Abstract
Nonlinear phenomena in physical systems can be used for brain-inspired computing with low energy consumption. Response from the dynamics of a topological spin structure called skyrmion is one of the candidates for such a neuromorphic computing. However, its ability has not been well explored experimentally. Here, we experimentally demonstrate neuromorphic computing using nonlinear response originating from magnetic field-induced dynamics of skyrmions. We designed a simple-structured skyrmion-based neuromorphic device and succeeded in handwritten digit recognition with the accuracy as large as 94.7% and waveform recognition. Notably, there exists a positive correlation between the recognition accuracy and the number of skyrmions in the devices. The large degrees of freedom of skyrmion systems, such as the position and the size, originate from the more complex nonlinear mapping, the larger output dimension, and, thus, high accuracy. Our results provide a guideline for developing energy-saving and high-performance skyrmion neuromorphic computing devices.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524829 | PMC |
| http://dx.doi.org/10.1126/sciadv.abq5652 | DOI Listing |
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