所有自旋逻辑装置作为一个紧凑的人工神经元

A. Sarkar, B. Behin-Aein, S. Srinivasan, S. Datta
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引用次数: 1

摘要

在我们最近的工作中,我们提出了使用通过自旋电流相互作用的磁体来实现用于信息处理的全自旋逻辑(ASL)器件的可能性,这与标准的基于电荷的架构有本质的不同。信息存储在磁体的磁化状态下,并通过纯自旋电流在磁体之间进行通信。用我们的实验基准模型[2]对这些多磁体网络的模拟表明,这种自旋磁体电路可以模拟许多标准基于电荷的电路的属性,如逆变器、通用NAND/NOR门、环形振荡器等。然而,这些电路并没有充分利用自旋电流和磁体的天然混合模拟/数字特性,我们在本文中讨论了这种可能性。事实上,我们在本文中的贡献是双重的:我们展示了一个简单的ASL设备模型,映射到众所周知的神经元动力学的“漏积分和火”方程,突出了磁铁与神经元的类比。本文首次引入了LLGz,并将其与我们的全严格模型联系起来。我们还表明,LLGz捕获了由完整模型预测的磁体的稳态行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
All Spin Logic device as a compact artificial neuron
In our recent work we have proposed the possibility of using magnets interacting via spin currents to implement all-spin logic (ASL) devices for information processing, fundamentally different from the standard charge-based architecture. Information is stored in the state of magnetization of the magnets and is communicated between magnets through pure spin currents. Simulations of these multi-magnet networks with our experimentally benchmarked model [2] indicate that such spin-magnet circuits can mimic many of the attributes of standard charge-based circuits such as inverters, universal NAND/NOR gates, ring oscillators etc .. However, these circuits do not take full advantage of the natural hybrid analog/digital character of spin currents and magnets, the possibility of which we discuss in this paper. Indeed, our contribution in this paper is twofold: We show that a simple model of an ASL device, maps on to the well-known 'leaky integrate and fire' equation of neuron dynamics, highlighting the analogy of the magnet to a neuron. We introduce LLGz for the first time in this paper and relate it to our full rigorous model. We also show that LLGz captures the steady state behavior of magnets predicted by the full model.
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