Current physical neuromorphic computing faces critical challenges of how to reconfigure key physical dynamics of a system to adapt computational performance to match a diverse range of tasks. Here the authors present a task-adaptive approach to physical neuromorphic computing based on on-demand control of computing performance using various magnetic phases of chiral magnets.
- Oscar Lee
- Tianyi Wei
- Hidekazu Kurebayashi