Leakage function in magnetic domain wall based artificial neuron using stray field

Wai Lum William Mah,Jian Peng Chan, K. R. Ganesh, V. B. Naik,S. N. Piramanayagam

APPLIED PHYSICS LETTERS(2023)

引用 0|浏览0
暂无评分
摘要
Recently, brain-inspired neuromorphic computing (NC) has been gaining traction as it is expected to be more power efficient and a more suitable platform for artificial intelligence. Artificial neurons and synapses are the main components of the NC architecture, and there have been many studies on artificial synapses. Experimental studies on artificial neurons that should exhibit the leaky integrate-and-fire properties are lacking due to the challenges in fabricating such a device. In this work, we have fabricated domain wall based devices consisting of (Co/Pt)n free and hard layers without interlayer exchange coupling, whereby the stray field from the hard layer triggers the automatic leakage function in the free layer. In addition, devices of smaller width were able to fully reset, showing the potential to scale down to smaller sizes. This experimental proof of concept provided evidence that the proposed neuron design has potential applications in NC. Further studies were performed via micromagnetic simulations to understand the role of the width of the device, thickness, and saturation magnetization of the hard layer.
更多
查看译文
关键词
magnetic domain wall,artificial neuron
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要