Adiabatic superconducting cells for ultra-low-power artificial neural networks

Schegolev, Andrey E.; Klenov, N. V.; Soloviev, I. I.; Терешонок, М. В.

doi:10.3762/bjnano.7.130

Cited by 44 publications

(31 citation statements)

References 30 publications

(27 reference statements)

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“…Superconductor digital devices have attracted growing attention due to their unique energy efficiency and performance [1], and also due to compatibility with a number of quantum and neuromorphic computers under development [2–4]. However the lack of cryogenic memory elements (including synapses) with sufficiently fast switching between stable states and sufficiently small energy dissipation is still the main obstacle in the field.…”

Section: Resultsmentioning

confidence: 99%

Periodic Co/Nb pseudo spin valve for cryogenic memory

Klenov¹,

Khaydukov²,

Bakurskiy³

et al. 2019

Beilstein J. Nanotechnol.

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We present a study of magnetic structures with controllable effective exchange energy for Josephson switches and memory applications. As a basis for a weak link we propose to use a periodic structure composed of ferromagnetic (F) layers spaced by thin superconductors (s). Our calculations based on the Usadel equations show that switching from parallel (P) to antiparallel (AP) alignment of neighboring F layers can lead to a significant enhancement of the critical current through the junction. To control the magnetic alignment we propose to use a periodic system whose unit cell is a pseudo spin valve of structure F1/s/F2/s where F1 and F2 are two magnetic layers having different coercive fields. In order to check the feasibility of controllable switching between AP and P states through the whole periodic structure, we prepared a superlattice [Co(1.5 nm)/Nb(8 nm)/Co(2.5 nm)/Nb(8 nm)]6 between two superconducting layers of Nb(25 nm). Neutron scattering and magnetometry data showed that parallel and antiparallel alignment can be controlled with a magnetic field of only several tens of Oersted.

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Section: Resultsmentioning

confidence: 99%

Periodic Co/Nb pseudo spin valve for cryogenic memory

Klenov¹,

Khaydukov²,

Bakurskiy³

et al. 2019

Beilstein J. Nanotechnol.

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“…While ASL circuits are distinguished by their ultimate energy efficiency, the shape of the magnetic signal transferred by ASL transmission line can be easily tuned in-situ. In comparison with Josephson transmission line, here Josephson junctions are substituted by superconducting adiabatic logic cells [33][34][35][36]. This allows you to transfer data not in the form of the presence or absence of quantum, but in the direction of the currents circulating in the superconducting circuits (excluding in the limit the energy dissipation due to the transition in the resistive state).…”

Section: Issues Of the Experimental Realization Of The Theoretically mentioning

confidence: 99%

Unipolar magnetic field pulses as an advantageous tool for ultrafast spin-flip in superconducting Josephson “atoms”

Popolitova¹,

Klenov²,

Soloviev³

et al. 2019

Preprint

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The theoretical approach to the consistent fully quantum description of the ultrafast population transfer and magnetization reversal in superconducting meta-atoms induced by picosecond unipolar pulses of the magnetic field is developed. A promising scheme based on the regime of stimulated Raman Λ-type transitions between qubit spin states via upper-lying levels is suggested in order to provide an ultrafast spin-flip on the picosecond time scale. The experimental realization of the ultrafast control of circuit -on -chip is presented.

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“…In addition, the theoretical basis of artificial neurons with sigmoid function has not been fully discussed. 12 Hence in this paper, we present the physical basis of the sigmoid function acting as an activation function in neurons which are the building blocks of ANNs based on a typical two-state stochastic transition model. The model will then be used to analyze simplified SQUIDbased artificial neurons.…”

Section: Introductionmentioning

confidence: 99%

Theoretical basis of SQUID-based artificial neurons

Katayama

Fujii

Hatakenaka

2018

Journal of Applied Physics

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The physical basis of an artificial neuron is studied using a model that is based on the stochastic transition between two states in a double well potential. It is shown that the stochastic transition model generates an energy-defined sigmoid function acting as an activation (or transfer) function in neurons. The model is also applied to circuit neurons using superconducting quantum interference devices (SQUIDs) in artificial neural networks.

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Adiabatic superconducting cells for ultra-low-power artificial neural networks

Cited by 44 publications

References 30 publications

Periodic Co/Nb pseudo spin valve for cryogenic memory

Periodic Co/Nb pseudo spin valve for cryogenic memory

Unipolar magnetic field pulses as an advantageous tool for ultrafast spin-flip in superconducting Josephson “atoms”

Theoretical basis of SQUID-based artificial neurons

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