随机单通量量子神经形态计算利用磁可调谐约瑟夫森结

S. Russek, C. Donnelly, M. Schneider, B. Baek, M. Pufall, W. Rippard, P. Hopkins, P. Dresselhaus, S. Benz
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引用次数: 23

摘要

单通量量子电路(SFQ)形成了一种天然的神经形态技术,SFQ脉冲和超导传输线分别模拟动作电位和轴突。在这里,我们提出了一种新的组件,磁性约瑟夫森结,具有可调性和可重构性,这是以前的SFQ神经形态电路所缺乏的。纳米级的磁性结构作为可调谐的突触成分,可以改变结的临界电流。这些电路可以在接近热极限的情况下工作,在这种情况下,神经元的随机放电是该技术的重要组成部分。该技术能够创建每秒超过1021次神经发射的复杂神经系统,耗散约为1w。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic single flux quantum neuromorphic computing using magnetically tunable Josephson junctions
Single flux quantum (SFQ) circuits form a natural neuromorphic technology with SFQ pulses and superconducting transmission lines simulating action potentials and axons, respectively. Here we present a new component, magnetic Josephson junctions, that have a tunablility and re-configurability that was lacking from previous SFQ neuromorphic circuits. The nanoscale magnetic structure acts as a tunable synaptic constituent that modifies the junction critical current. These circuits can operate near the thermal limit where stochastic firing of the neurons is an essential component of the technology. This technology has the ability to create complex neural systems with greater than 1021 neural firings per second with approximately 1 W dissipation.
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