超导绝热Sigma神经元的数字控制

IF 1.3 4区物理与天体物理 Q3 PHYSICS, MULTIDISCIPLINARY

JETP Letters Pub Date : 2025-06-25 DOI:10.1134/S0021364025605779

M. V. Bastrakova, D. S. Pashin, G. I. Gubochkin, A. E. Schegolev, S. V. Bakurskiy, I. I. Soloviev, N. V. Klenov

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引用次数: 0

摘要

基于量子参数子的超导绝热神经元可以在一个周期内以模拟的方式“计算”s型激活函数及其导数，并具有创纪录的能量效率。然而，对于此类系统的应用，有必要确定允许与约瑟夫森数字电路集成的操作制度，其中信息以皮秒单极电压脉冲序列的形式呈现。在这项工作中，从理论上确定了允许绝热sigma神经元脉冲控制的条件。所获得的结果使我们能够开发模拟-数字约瑟夫森神经网络硬件实现的基本单元设计。

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Digital Control of a Superconducting Adiabatic Sigma Neuron

Superconducting adiabatic neurons based on quantum parametrons make it possible to “calculate” sigmoid activation functions and their derivatives in an analog manner in one cycle with record energy efficiency. However, for the application of such systems, it is necessary to determine operation regimes that allow integration with Josephson digital circuits, where information is presented in the form of sequences of picosecond unipolar voltage pulses. The conditions allowing the pulse control of an adiabatic sigma neuron have been theoretically determined in this work. The obtained results allowed us to develop the design of the basic unit for the hardware implementation of analog–digital Josephson neural networks.

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来源期刊

JETP Letters 物理-物理：综合

CiteScore

2.40

自引率

30.80%

发文量

164

审稿时长

3-6 weeks

期刊介绍： All topics of experimental and theoretical physics including gravitation, field theory, elementary particles and nuclei, plasma, nonlinear phenomena, condensed matter, superconductivity, superfluidity, lasers, and surfaces.