Optimisation Challenge for a Superconducting Adiabatic Neural Network That Implements XOR and OR Boolean Functions.

In this article, we consider designs of simple analog artificial neural networks based on adiabatic Josephson cells with a sigmoid activation function. A new approach based on the gradient descent method is developed to adjust the circuit parameters, allowing efficient signal transmission between the network layers. The proposed solution is demonstrated on the example of a system that implements XOR and OR logical operations.

Spin-Valve-Controlled Triggering of Superconductivity.

We have studied the proximity effect in an SF1S1F2s superconducting spin valve consisting of a massive superconducting electrode (S) and a multilayer structure formed by thin ferromagnetic (F1,2) and superconducting (S1, s) layers. Within the framework of the Usadel equations, we have shown that changing the mutual orientation of the magnetization vectors of the F1,2 layers from parallel to antiparallel serves to trigger superconductivity in the outer thin s-film. We studied the changes in the pair potential in the outer s-film and found the regions of parameters with a significant spin-valve effect. The strongest effect occurs in the region of parameters where the pair-potential sign is changed in the parallel state. This feature reveals new ways to design devices with highly tunable inductance and critical current.

A bifunctional superconducting cell as flux qubit and neuron.

Josephson digital or analog ancillary circuits are an essential part of a large number of modern quantum processors. The natural candidate for the basis of tuning, coupling, and neromorphic co-processing elements for processors based on flux qubits is the adiabatic (reversible) superconducting logic cell. Using the simplest implementation of such a cell as an example, we have investigated the conditions under which it can optionally operate as an auxiliary qubit while maintaining its "classical" neural functionality. The performance and temperature regime estimates obtained confirm the possibility of practical use of a single-contact inductively shunted interferometer in a quantum mode in adjustment circuits for q-processors.

Bio-Inspired Design of Superconducting Spiking Neuron and Synapse.

The imitative modelling of processes in the brain of living beings is an ambitious task. However, advances in the complexity of existing hardware brain models are limited by their low speed and high energy consumption. A superconducting circuit with Josephson junctions closely mimics the neuronal membrane with channels involved in the operation of the sodium-potassium pump. The dynamic processes in such a system are characterised by a duration of picoseconds and an energy level of attojoules. In this work, two superconducting models of a biological neuron are studied. New modes of their operation are identified, including the so-called bursting mode, which plays an important role in biological neural networks. The possibility of switching between different modes in situ is shown, providing the possibility of dynamic control of the system. A synaptic connection that mimics the short-term potentiation of a biological synapse is developed and demonstrated. Finally, the simplest two-neuron chain comprising the proposed bio-inspired components is simulated, and the prospects of superconducting hardware biosimilars are briefly discussed.

Tunnel Josephson Junction with Spin-Orbit/Ferromagnetic Valve.

We have theoretically studied the transport properties of the SIsNSOF structure consisting of thick (S) and thin (s) films of superconductor, an insulator layer (I), a thin film of normal metal with spin-orbit interaction (SOI) (NSO), and a monodomain ferromagnetic layer (F). The interplay between superconductivity, ferromagnetism, and spin-orbit interaction allows the critical current of this Josephson junction to be smoothly varied over a wide range by rotating the magnetization direction in the single F-layer. We have studied the amplitude of the spin valve effect and found the optimal ranges of parameters.

Contribution of Processes in SN Electrodes to the Transport Properties of SN-N-NS Josephson Junctions.

In this paper, we present a theoretical study of electronic transport in planar Josephson Superconductor-Normal Metal-Superconductor (SN-N-NS) bridges with arbitrary transparency of the SN interfaces. We formulate and solve the two-dimensional problem of finding the spatial distribution of the supercurrent in the SN electrodes. This allows us to determine the scale of the weak coupling region in the SN-N-NS bridges, i.e., to describe this structure as a serial connection between the Josephson contact and the linear inductance of the current-carrying electrodes. We show that the presence of a two-dimensional spatial current distribution in the SN electrodes leads to a modification of the current-phase relation and the critical current magnitude of the bridges. In particular, the critical current decreases as the overlap area of the SN parts of the electrodes decreases. We show that this is accompanied by a transformation of the SN-N-NS structure from an SNS-type weak link to a double-barrier SINIS contact. In addition, we find the range of interface transparency in order to optimise device performance. The features we have discovered should have a significant impact on the operation of small-scale superconducting electronic devices, and should be taken into account in their design.

Superconducting Valve Exploiting Interplay between Spin-Orbit and Exchange Interactions.

We theoretically investigated the proximity effect in SNSOF and SF'F structures consisting of a superconductor (S), a normal metal (NSO), and ferromagnetic (F',F) thin films with spin-orbit interaction (SOI) in the NSO layer. We show that a normal layer with spin-orbit interaction effectively suppresses triplet correlations generated in a ferromagnetic layer. Due to this effect, the critical temperature of the superconducting layer in the SNSOF multilayer turns out to be higher than in a similar multilayer without spin-orbit interaction in the N layer. Moreover, in the presence of a mixed type of spin-orbit interaction involving the Rashba and Dresselhaus components, the SNSOF structure is a spin valve, whose critical temperature is determined by the direction of the magnetization vector in the F layer. We calculated the control characteristics of the SNSOF spin valve and compared them with those available in traditional SF'F devices with two ferromagnetic layers. We concluded that SNSOF structures with one controlled F layer provide solid advantages over the broadly considered SF'F spin valves, paving the way for high-performance storage components for superconducting electronics.

A superconducting adiabatic neuron in a quantum regime.

We explore the dynamics of an adiabatic neural cell of a perceptron artificial neural network in a quantum regime. This mode of cell operation is assumed for a hybrid system of a classical neural network whose configuration is dynamically adjusted by a quantum co-processor. Analytical and numerical studies take into account non-adiabatic processes as well as dissipation, which leads to smoothing of quantum coherent oscillations. The obtained results indicate the conditions under which the neuron possesses the required sigmoid activation function.

Effective Exchange Energy in a Thin, Spatially Inhomogeneous CuNi Layer Proximized by Nb.

Thin films of diluted magnetic alloys are widely used in superconducting spintronics devices. Most studies rely on transport measurements and assume homogeneous magnetic layers. Here we examine on a local scale the electronic properties of the well-known two-layer superconductor/ferromagnet structure Nb/CuNi. Scanning tunneling spectroscopy experiments demonstrated significant spatial variations of the tunneling conductance on nanoscale, with characteristic gapped, nongapped, and strongly zero-bias peaked spectra. The microscopic theory successfully reproduced the observed spectra and relied them to spatial variations of CuNi film thickness and composition, leading to strong variations of the effective exchange energy. The observed inhomogeneities put constraints on the use of diluted magnetic alloys in nanoscale devices.

Revealing Josephson Vortex Dynamics in Proximity Junctions below Critical Current.

Made of a thin non-superconducting metal (N) sandwiched by two superconductors (S), SNS Josephson junctions enable novel quantum functionalities by mixing up the intrinsic electronic properties of N with the superconducting correlations induced from S by proximity. Electronic properties of these devices are governed by Andreev quasiparticles (Andreev, A. Sov. Phys. JETP 1965, 20, 1490) which are absent in conventional SIS junctions whose insulating barrier (I) between the two S electrodes owns no electronic states. Here we focus on the Josephson vortex (JV) motion inside Nb-Cu-Nb proximity junctions subject to electric currents and magnetic fields. The results of local (magnetic force microscopy) and global (transport) experiments provided simultaneously are compared with our numerical model, revealing the existence of several distinct dynamic regimes of the JV motion. One of them, identified as a fast hysteretic entry/escape below the critical value of Josephson current, is analyzed and suggested for low-dissipative logic and memory elements.

Tunable superconducting neurons for networks based on radial basis functions.

The hardware implementation of signal microprocessors based on superconducting technologies seems relevant for a number of niche tasks where performance and energy efficiency are critically important. In this paper, we consider the basic elements for superconducting neural networks on radial basis functions. We examine the static and dynamic activation functions of the proposed neuron. Special attention is paid to tuning the activation functions to a Gaussian form with relatively large amplitude. For the practical implementation of the required tunability, we proposed and investigated heterostructures designed for the implementation of adjustable inductors that consist of superconducting, ferromagnetic, and normal layers.

Superconducting Bio-Inspired Au-Nanowire-Based Neurons.

High-performance modeling of neurophysiological processes is an urgent task that requires new approaches to information processing. In this context, two- and three-junction superconducting quantum interferometers with Josephson weak links based on gold nanowires are fabricated and investigated experimentally. The studied cells are proposed for the implementation of bio-inspired neurons-high-performance, energy-efficient, and compact elements of neuromorphic processor. The operation modes of an advanced artificial neuron capable of generating the burst firing activation patterns are explored theoretically. A comparison with the Izhikevich mathematical model of biological neurons is carried out.

Controlling the proximity effect in a Co/Nb multilayer: the properties of electronic transport.

We present both theoretical and experimental investigations of the proximity effect in a stack-like superconductor/ferromagnetic (S/F) superlattice, where ferromagnetic layers with different thicknesses and coercive fields are made of Co. Calculations based on the Usadel equations allow us to find the conditions at which switching from the parallel to the antiparallel alignment of the neighboring F-layers leads to a significant change of the superconducting order parameter in superconductive thin films. We experimentally study the transport properties of a lithographically patterned Nb/Co multilayer. We observe that the resistive transition of the multilayer structure has multiple steps, which we attribute to the transition of individual superconductive layers with the critical temperature, T c, depending on the local magnetization orientation of the neighboring F-layers. We argue that such superlattices can be used as tunable kinetic inductors designed for artificial neural networks representing the information in a "current domain".

Unipolar magnetic field pulses as an advantageous tool for ultrafast operations in superconducting Josephson "atoms".

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

Periodic Co/Nb pseudo spin valve for cryogenic memory.

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.

Beyond Moore's technologies: operation principles of a superconductor alternative.

The predictions of Moore's law are considered by experts to be valid until 2020 giving rise to "post-Moore's" technologies afterwards. Energy efficiency is one of the major challenges in high-performance computing that should be answered. Superconductor digital technology is a promising post-Moore's alternative for the development of supercomputers. In this paper, we consider operation principles of an energy-efficient superconductor logic and memory circuits with a short retrospective review of their evolution. We analyze their shortcomings in respect to computer circuits design. Possible ways of further research are outlined.

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

We propose the concept of using superconducting quantum interferometers for the implementation of neural network algorithms with extremely low power dissipation. These adiabatic elements are Josephson cells with sigmoid- and Gaussian-like activation functions. We optimize their parameters for application in three-layer perceptron and radial basis function networks.

Magnetic reversal dynamics of a quantum system on a picosecond timescale.

We present our approach for a consistent, fully quantum mechanical description of the magnetization reversal process in natural and artificial atomic systems by means of short magnetic pulses. In terms of the simplest model of a two-level system with a magnetic moment, we analyze the possibility of a fast magnetization reversal on the picosecond timescale induced by oscillating or short unipolar magnetic pulses. We demonstrate the possibility of selective magnetization reversal of a superconducting flux qubit using a single flux quantum-based pulse and suggest a promising, rapid Λ-scheme for resonant implementation of this process. In addition, the magnetization reversal treatment is fulfilled within the framework of the macroscopic theory of the magnetic moment, which allows for the comparison and explanation of the quantum and classical behavior.

A highly pH-sensitive nanowire field-effect transistor based on silicon on insulator.

BACKGROUND: An experimental and theoretical study of a silicon-nanowire field-effect transistor made of silicon on insulator by CMOS-compatible methods is presented. RESULTS: A maximum Nernstian sensitivity to pH change of 59 mV/pH was obtained experimentally. The maximum charge sensitivity of the sensor was estimated to be on the order of a thousandth of the electron charge in subthreshold mode. CONCLUSION: The sensitivity obtained for our sensor built in the CMOS-compatible top-down approach does not yield to the one of sensors built in bottom-up approaches. This provides a good background for the development of CMOS-compatible probes with primary signal processing on-chip.