Determination of the Current–Phase Relation in Josephson Junctions by Means of an Asymmetric Two-Junction SQUID

Ginzburg, L. V.; Batov, I. E.; Bolginov, V. V.; Чичков, В. И.; Shchegolev, A. E.; Klenov, N. V.; Soloviev, I. I.; Bakurskiy, S. V.; Kupriyanov, M. Yu.

doi:10.1134/s0021364018010058

Cited by 9 publications

(9 citation statements)

References 45 publications

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“…The Josephson junction [ 54 ] is a nonlinear oscillator consisting of two weakly coupled superconductors separated by a thin nonconducting layer for the passage of electrons. Solitary waves exist as the propagation of electromagnetic waves between two superconductors.…”

Section: Applications Of Solitonsmentioning

confidence: 99%

Soliton: A dispersion-less solution with existence and its types

Arora

Rani

Emadifar

2022

Heliyon

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Section: Applications Of Solitonsmentioning

confidence: 99%

Soliton: A dispersion-less solution with existence and its types

Arora

Rani

Emadifar

2022

Heliyon

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“…The dependence of the phase difference on the phase sum, ϕ − (ϕ + ), can be obtained 23,24 from (8b) with corresponding function…”

Section: B Artificial Synapsementioning

confidence: 99%

Adiabatic superconducting artificial neural network: Basic cells

Soloviev

Schegolev

Klenov

et al. 2018

Journal of Applied Physics

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We consider adiabatic superconducting cells operating as an artificial neuron and synapse of a multilayer perceptron (MLP). Their compact circuits contain just one and two Josephson junctions, respectively. While the signal is represented as magnetic flux, the proposed cells are inherently nonlinear and close-to-linear magnetic flux transformers. The neuron is capable of providing a one-shot calculation of sigmoid and hyperbolic tangent activation functions most commonly used in MLP. The synapse features by both positive and negative signal transfer coefficients in the range ∼ (−0.5, 0.5). We briefly discuss implementation issues and further steps toward multilayer adiabatic superconducting artificial neural network which promises to be a compact and the most energy-efficient implementation of MLP.

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“…Unfortunately, direct measurement of the above features is a technically difficult task 12,26 . Thus, to date, experimental determination of the CPR shape has been carried out only for solitary SFS junctions [27][28][29] .…”

Section: Introductionmentioning

confidence: 99%

Density of states and current-voltage characteristics in SIsFS junctions

Bakurskiy,

Neilo,

Klenov

et al. 2020

Preprint

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We study the density of states (DOS) inside superconducting Josephson SIsFS junctions with complex interlayer consisting of a thin superconducting spacer 's' between insulator I and a ferromagnetic metal F. The consideration is focused on the local density of states in the vicinity of a tunnel barrier, and it permits to estimate the current-voltage characteristics in the resistive state of such junctions. We study the influence of the proximity effect and Zeeman splitting on the properties of the system, and we find significant sub-gap regions with non-vanishing DOS. We also find manifestations of the 0-π transition in the behavior of DOS in a thin slayer. These properties lead to appearance of new characteristic features on I-V curves which provide additional information about electronic states inside the junction.

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Determination of the Current–Phase Relation in Josephson Junctions by Means of an Asymmetric Two-Junction SQUID

Cited by 9 publications

References 45 publications

Soliton: A dispersion-less solution with existence and its types

Soliton: A dispersion-less solution with existence and its types

Adiabatic superconducting artificial neural network: Basic cells

Density of states and current-voltage characteristics in SIsFS junctions

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