神经形态工程学
自旋电子学
实现(概率)
反铁磁性
一致性(知识库)
物理
Spike(软件开发)
人工神经网络
自旋(空气动力学)
拓扑(电路)
计算机科学
尖峰神经网络
凝聚态物理
人工智能
铁磁性
电气工程
数学
工程类
软件工程
统计
热力学
作者
Shu Zhang,Yaroslav Tserkovnyak
标识
DOI:10.1103/physrevlett.125.207202
摘要
We propose a spintronics-based hardware implementation of neuromorphic computing, specifically, the spiking neural network, using topological winding textures in one-dimensional antiferromagnets. The consistency of such a network is emphasized in light of the conservation of topological charges, and the natural spatiotemporal interconversions of magnetic winding. We discuss the realization of the leaky integrate-and-fire behavior of neurons and the spike-timing-dependent plasticity of synapses. Our proposal opens the possibility for an all-spin neuromorphic platform based on antiferromagnetic insulators.
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