混合CMOS/STO电路的计算

M. Kabir, M. Stan
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引用次数: 7

摘要

近年来对自旋力矩纳米振荡器(STNO)的研究开辟了利用电子自旋产生持续微波振荡的可能性。此外,实验验证了STNOs的同步性,可以实现与纳米级振荡器的通信和计算。在本文中,我们提出了一种混合MOSFET/STNO阵列,可用于模式识别应用。首先,我们证明了一组电耦合STNOs服从Kuramoto弱耦合振荡器的动力学[1]。这种行为允许我们使用STNO阵列来实现由hoppenstead等人[2]提出的振荡神经计算机。接下来,我们考虑可用于并行连接阵列的实用STNO器件几何形状。我们建议使用双势垒磁隧道结(DMTJ)在没有外部磁场的情况下产生强谐波振荡信号。最后,我们对混合MOSFET/STNO阵列进行HSPICE模拟,以展示如何将其用于模式识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computing with hybrid CMOS/STO circuits
Recent research in spin torque nano-oscillators (STNO) have opened the possibility of using electron spin to generate sustained microwave oscillations. Furthermore, the experimental verification of synchronization of STNOs could allow communication and computation with nanoscaled oscillators. In this paper, we propose a hybrid MOSFET/STNO array which can be used for pattern recognition applications. First, we show that an array of electrically coupled STNOs obey the dynamics of Kuramoto's weakly coupled oscillators [1]. This behavior allows us to use the STNO array to implement the oscillatory neurocomputer proposed by Hoppensteadt et. al. [2]. We next consider practical STNO device geometries which can be used in a parallel-connected array. We propose using a dual barrier magnetic tunnel junction (DMTJ) to produce strong, harmonic oscillation signals in the absence on an external magnetic field. Finally, we perform HSPICE simulations of a hybrid MOSFET/STNO array to show how it can be used for pattern recognition.
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