Magnetic Josephson Junctions With Superconducting Interlayer for Cryogenic Memory

Vernik, Igor V.; Bolginov, V. V.; Bakurskiy, S. V.; Golubov, A. A.; Kupriyanov, Mikhail Yu.; Ryazanov, V. V.; Mukhanov, Oleg A.

doi:10.1109/tasc.2012.2233270

Cited by 143 publications

(110 citation statements)

References 42 publications

(61 reference statements)

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“…It may be possible to implement synapses in the electronic domain by making use of superconducting circuit elements or magnetic elements such as magnetic tunnel junctions or magnetic Josephson junctions [24]. Such an approach to memory will be investigated in future work.…”

Section: Learning Reconfiguration and Plasticitymentioning

confidence: 99%

Superconducting Optoelectronic Circuits for Neuromorphic Computing

et al. 2017

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Neural networks have proven effective for solving many difficult computational problems. Implementing complex neural networks in software is very computationally expensive. To explore the limits of information processing, it will be necessary to implement new hardware platforms with large numbers of neurons, each with a large number of connections to other neurons. Here we propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights of connection can be implemented using several approaches. The use of light as a signaling mechanism overcomes fanout and parasitic constraints on electrical signals while simultaneously introducing physical degrees of freedom which can be employed for computation. The use of supercurrents achieves the low power density necessary to scale to systems with enormous entropy. The proposed processing units can operate at speeds of at least 20 MHz with fully asynchronous activity, light-speed-limited latency, and power densities on the order of 1 mW/cm 2 for neurons with 700 connections operating at full speed at 2 K. The processing units achieve an energy efficiency of ≈ 20 aJ per synapse event. By leveraging multilayer photonics with deposited waveguides and superconductors with feature sizes > 100 nm, this approach could scale to systems with massive interconnectivity and complexity for advanced computing as well as explorations of information processing capacity in systems with an enormous number of information-bearing microstates.

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Section: Learning Reconfiguration and Plasticitymentioning

confidence: 99%

Superconducting Optoelectronic Circuits for Neuromorphic Computing

et al. 2017

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“…Also, by virtue of recent developments in fabrication technology with a multi-layered structure [13], [14] and some energy-efficient circuit technology [15]- [19], several research projects on SFQ microprocessors have been undertaken [20], [21], and an 8-bit microprocessor composed of more than 10,000 Josephson junctions successfully operates at 50 GHz [7]. In addition, inventions of several novel superconductor devices based on new physical phenomena have made the SFQ logic technology much more attractive, e.g., superconductor junctions with one or more ferromagnet layers show different electrical characteristics depending on the magnetic states, by which we can obtain high-density, low-power, cryogenic memory compatible with SFQ circuits [22], [23]. A thermally-assisted nano-structured device called a nanocryotron (nTron) showed the capability of voltage output in the sub-volt range [24], by which we can build very large-scale cryogenic memory by hybridizing Josephson and CMOS integrated circuits [25].…”

Section: Sfq Circuitsmentioning

confidence: 99%

Towards Ultra-High-Speed Cryogenic Single-Flux-Quantum Computing

Ishida

Tanaka

Ono

et al. 2018

IEICE Trans. Electron.

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SUMMARYCMOS microprocessors are limited in their capacity for clock speed improvement because of increasing computing power, i.e., they face a power-wall problem. Single-flux-quantum (SFQ) circuits offer a solution with their ultra-fast-speed and ultra-low-power natures. This paper introduces our contributions towards ultra-high-speed cryogenic SFQ computing. The first step is to design SFQ microprocessors. From qualitatively and quantitatively evaluating past-designed SFQ microprocessors, we have found that revisiting the architecture of SFQ microprocessors and on-chip caches is the first critical challenge. On the basis of cross-layer discussions and analysis, we came to the conclusion that a bit-parallel gate-level pipeline architecture is the best solution for SFQ designs. This paper summarizes our current research results targeting SFQ microprocessors and onchip cache architectures.

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“…1(a) and 1(b) were reported previously in Refs. [4] and [6], respectively, and are normalized with respect to the maximum I c . For convenience, we refer further to the experimental result shown in Fig.…”

Section: Reconstruction Of Critical Current Of Mjj (Verification mentioning

confidence: 99%

“…Very recently, superconductor/ferromagnet hybrid structures based on weak ferromagnetic layers with low coercivity have regained strong practical interest due to their integration in various superconductor-ferromagnet-superconductor (SFS) Josephson spintronic elements [1][2][3][4][5][6][7][8][9][10][11][12] and superconducting ultrafast electronic devices [13,14].…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, Pd-Fe alloy thin films with small Fe content exhibit in-plane magnetization and small coercive field making them perfect candidates for application in novel ultrafast Josephson cryogenic magnetic memory [4][5][6][7]. The value of the critical current of the MJJ memory element is defined * Corresponding author: ryazanov@issp.ac.ru by in-plane magnetic flux including magnetization of the F layer and, therefore, is governed by magnetic history of the ferromagnetic layer.…”

Section: Introductionmentioning

confidence: 99%

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Micromagnetic modeling of critical current oscillations in magnetic Josephson junctions

et al. 2016

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In this work we propose and explore an effective numerical approach for investigation of critical current dependence on applied magnetic field for magnetic Josephson junctions with in-plane magnetization orientation. This approach is based on micromagnetic simulation of the magnetization reversal process in the ferromagnetic layer with introduced internal magnetic stiffness and subsequent reconstruction of the critical current value using total flux or reconstructed actual phase difference distribution. The approach is flexible and shows good agreement with experimental data obtained on Josephson junctions with ferromagnetic barriers. Based on this approach we have obtained a critical current dependence on applied magnetic field for rectangular magnetic Josephson junctions with high size aspect ratio. We have shown that the rectangular magnetic Josephson junctions can be considered for application as an effective Josephson magnetic memory element with the value of critical current defined by the orientation of magnetic moment at zero magnetic field. An impact of shape magnetic anisotropy on critical current is revealed and discussed. Finally, we have considered a curling magnetic state in the ferromagnetic layer and demonstrated its impact on critical current.

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Magnetic Josephson Junctions With Superconducting Interlayer for Cryogenic Memory

Cited by 143 publications

References 42 publications

Superconducting Optoelectronic Circuits for Neuromorphic Computing

Superconducting Optoelectronic Circuits for Neuromorphic Computing

Towards Ultra-High-Speed Cryogenic Single-Flux-Quantum Computing

Micromagnetic modeling of critical current oscillations in magnetic Josephson junctions

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