Soloviev, Igor Igorevich

Maksimovskaya A.A., Ruzhickiy V.I., Klenov N.V., Schegolev A.E., Bakurskiy S.V., Soloviev I.I., Yakovlev D.S.

Sergeev M., Bastrakova M., Vozhakov V., Soloviev I., Klenov N., Kulandin D., Linyov A.

Nazhestkin I.A., Bakurskiy S.V., Neilo A.A., Tarasova I.E., Ismailov N.G., Gurtovoi V.L., Egorov S.V., Lisitsyn S.A., Stolyarov V.S., Antonov V.N., Ryazanov V.V., Kupriyanov M.Y., Soloviev I.I., Klenov N.V., Yakovlev D.S.

The transport properties of a nanobridge superconducting quantum interference device made of Al/Pt bilayer have been studied. Measurement and approximation of the voltage‐field dependencies allow to estimate the inductance of the structure. It is found that this value significantly exceeds the expected geometric inductance and exhibits an atypical temperature dependence. To explain this effect, a microscopic model of electron transport in SN bilayers is developed, considering the proximity effect, and the available regimes of the current distribution are described. The measured properties may be indicative of the formation of high‐resistance aluminum with high values of kinetic inductance during the fabrication of Al/Pt bilayers.

Schegolev Andrey E., Bastrakova Marina V., Sergeev Michael A., Maksimovskaya Anastasia A., Klenov Nikolay V., Soloviev Igor

The extensive development of the field of spiking neural networks has led to many areas of research that have a direct impact on people’s lives. As the most bio-similar of all neural networks, spiking neural networks not only allow for the solution of recognition and clustering problems (including dynamics), but they also contribute to the growing understanding of the human nervous system. Our analysis has shown that hardware implementation is of great importance, since the specifics of the physical processes in the network cells affect their ability to simulate the neural activity of living neural tissue, the efficiency of certain stages of information processing, storage and transmission. This survey reviews existing hardware neuromorphic implementations of bio-inspired spiking networks in the ”semiconductor”, ”superconductor”, and ”optical” domains. Special attention is given to the potentials for effective ”hybrids” of different approaches.

Skryabina O.V., Bakurskiy S.V., Ruzhickiy V.I., Shishkin A., Klenov N.V., Soloviev I.I., Kupriyanov M.Y., Stolyarov V.S.

Abstract We study the effect of electrode width on superconducting current transport in Nb–Au–Nb Josephson bridges. The critical current as well as the normal bridge resistance drop with decreasing electrode width on scales of a few μ m , which are orders of magnitude larger than the estimated coherence length of the Au strip. We consider several physical reasons for such an anomalous influence of the width W of the superconducting electrode on the critical current I c (AIWIc) and provide model fits for the resistive and superconducting properties of the bridges. The smooth dependence of the Nb–Au–Nb bridge parameters on the electrode width can be used to optimize the design of superconducting devices for specific applications.

Neilo A., Bakurskiy S., Klenov N., Soloviev I., Stolyarov V., Kupriyanov M.

The supercurrent in a Josephson SF1S1F2sIS spin valve (“S” is for superconductor, “F” is for ferromagnet, and “I” is for insulator) is studied theoretically. It is found that by rotating the magnetization of one of the ferromagnetic layers, a smooth switching of the system between two states with different critical currents is possible. The operating range of the device can be adjusted by varying the thickness of the intermediate s-layer. The proposed structure is a promising scalable control element for the use in superconducting electronics.

Bakurskiy Sergey, Ruzhickiy Vsevolod, Neilo Alexey, Klenov Nikolay, Soloviev Igor, Elistratova Anna, Shishkin Andrey, Stolyarov Vasily, Kupriyanov Mikhail

We have studied the Thouless energy in Josephson superconductor – normal metal – superconductor (SN-N-NS) bridges analytically and numerically, considering the influence of the sub-electrode regions. We have discovered a significant suppression of the Thouless energy with increasing interfacial resistance, consistent with experimental results. The analysis of the temperature dependence of the critical current in Josephson junctions in comparison with the expressions for the Thouless energy may allow the determination of the interface parameters of S and N-layers.

Zakharov R.V., Tikhonova O.V., Klenov N.V., Soloviev I.I., Antonov V.N., Yakovlev D.S.

AbstractA basic element of a quantum network based on two single‐mode waveguides is proposed with different frequencies connected by a solid‐state qubit. Using a simple example of a possible superconducting implementation, the usefulness of the simplifications used in the general theoretical consideration has been justified. The non‐classical field in a single‐mode with a frequency of is fed to the input of a qubit controller and transformed into a non‐classical field in an output single‐mode with a frequency of . The interface can establish a quantum connection between solid‐state and photonic flying qubits with adjustable pulse shapes and carrier frequencies. This allows quantum information to be transferred to other superconducting or atomic‐based quantum registers or chips. The peculiarities of the wave‐qubit interactions are described, showing how they help to control the quantum state of the non‐classical field. On this basis, the operating principles of solid‐state and flying qubits for the future quantum information platforms are considered.

Pashin D.S., Bastrakova M.V., Rybin D.A., Soloviev I.I., Klenov N.V., Schegolev A.E.

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.

Kalashnikov D.S., Ruzhitskiy V.I., Shishkin A.G., Golovchanskiy I.A., Kupriyanov M.Y., Soloviev I.I., Roditchev D., Stolyarov V.S.

AbstractThe ongoing progress of superconducting logic systems with Josephson junctions as base elements requires the development of compatible cryogenic memory. Long enough junctions subject to magnetic field host quantum phase 2π-singularities—Josephson vortices. Here, we report the realization of the superconducting memory cell whose state is encoded by the number of present Josephson vortices. By integrating the junction into a coplanar resonator and by applying a microwave excitation well below the critical current, we are able to control the state of the system in an energy-efficient and non-destructive manner. The memory effect arises due to the presence of the natural edge barrier for Josephson vortices. The performance of the device is evaluated, and the routes for creating scalable cryogenic memories directly compatible with superconducting microwave technologies are discussed.

Neilo A., Bakurskiy S., Klenov N., Soloviev I., Kupriyanov M.

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.

Pashin D.S., Pikunov P.V., Bastrakova M.V., Schegolev A.E., Klenov N.V., Soloviev I.I.

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.

Khismatullin G.S., Klenov N.V., Soloviev I.I.

Adiabatic superconducting logic circuits can ensure the practical implementation of operations with the energy dissipation below the Landauer limit. However, applications of the existing solutions are limited because of two contradictory requirements of a high energy efficiency and a sufficiently fast response of devices. Josephson junctions with a negative critical current (π junctions) allow one to obtain a certain form of the potential energy of superconducting circuits and, as a result, a practically required degree of control of dynamic processes in the proposed reversible logic cells. The features of the current transport and balance of Josephson phases in circuits with π junctions make it possible to improve the coupling between the parts of a reversible computer by a factor more than 2. At the same time, the continuous evolution of the state is ensured at higher critical currents and higher characteristic voltages of the main Josephson junctions of adiabatic superconducting logic cells, which allows an increase in the response rate.

Schegolev A.E., Klenov N.V., Gubochkin G.I., Kupriyanov M.Y., Soloviev I.I.

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.

Neilo A., Bakurskiy S., Klenov N., Soloviev I., Kupriyanov M.

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.

Golden E.B., Semenov V.K., Tolpygo S.K.

Ucpinar B.Z., Karamuftuoglu M.A., Razmkhah S., Kamal M., Pedram M.

Ahmad H.G., Ferraiuolo R., Serpico G., Satariano R., Levochkina A., Vettoliere A., Granata C., Montemurro D., Esposito M., Ausanio G., Parlato L., Pepe G.P., Bruno A., Tafuri F., Massarotti D.

Yang H., Liu L., Shu Z., Zhang W., Huang C., Zhu Y., Li S., Wang W., Li G., Zhang Q., Liu Q., Jiang G.

Maksimovskaya A.A., Ruzhickiy V.I., Klenov N.V., Schegolev A.E., Bakurskiy S.V., Soloviev I.I., Yakovlev D.S.

Yanilkin I.V., Gumarov A.I., Gabbasov B.F., Yusupov R.V., Tagirov L.R.

Zhao M., Wang Y., Gao X., Yuan P., Wang S., Niu M., You L., Ren J., Li L.

Abstract We present a non-return-to-zero (NRZ) superconductive voltage driver (SVD) for interfacing single flux quantum (SFQ) circuits with semiconductor circuits. The NRZ SVD design consists an encoding module, splitter networks, sixteen RS flip-flops (RSFFs), and a sixteen-stage DC SQUID array (DSA). By employing an asymmetric SQUID structure, the SVD achieved a simulated output swing of 4.3 mV. The impedance and quality factor formulas of the DSA were provided. We solved the issue of slower fall time caused by the asymmetric SQUID by inserting a termination resistor into the DSA to reduce its quality factor. By using this damped asymmetric DSA, the NRZ SVD can reach up to 30 Gbps in simulation. The test chip of the NRZ SVD was fabricated using the SIMIT’s Nb03P process (JC = 6 kA cm−2) and measured in a liquid helium dewar. The SVD achieved a measured output swing of up to 6.8 mV, which is relatively high compared to the published reports. Eye diagrams at 5 Gbps and 10 Gbps were clearly opened, demonstrating a very low bit error rate. The test circuit for the NRZ SVD can support up to 15 Gbps with a 2 9 − 1 pseudo-random bit sequence (PRBS-9) input and 20 Gbps with a sinusoidal input.

Asaka K., Yoshikawa N., Yamanashi Y.

Abstract tochastic computing (SC) is a form of probabilistic computation that encodes information in the probability of a ``1’’ appearing within a finite-length binary sequence. SC has been investigated for applications in various fields that do not require deterministic and precise computation. A superconducting single-flux-quantum (SFQ) circuit is considered a promising candidate for implementing SC hardware due to its high-speed operation and probabilistic behavior. In this study, we propose a novel large fan-out signal splitter to enable large-scale SFQ-based stochastic arithmetic circuits, addressing the issue of computation accuracy degradation caused by correlations between binary sequences. The proposed signal splitter generates uncorrelated output binary sequences by utilizing superconductor random number generators frequency-synchronized to the input binary sequence. Moreover, the fan-out can be easily increased by simply adding more superconductor random number generators. We implemented a four-output stochastic number signal splitter using the 10 kA/cm^2 Nb four-layer superconducting circuit fabrication process. Its operation was successfully demonstrated by measuring the average voltage at the input and outputs under continuous high-speed binary sequence input. Correct operation was confirmed at the input frequency of up to 32.4 GHz. The proposed signal splitter uniquely leverages the properties of superconducting circuits, where flux quanta determined by fundamental physical constants serve as the information carrier. We believe this development will significantly advance the realization of practical SFQ-based SC systems.

Norouzi M., Hosseiny S.M., Seyed-Yazdi J.

Schneider M.L., Jué E.M., Pufall M.R., Segall K., Anderson C.W.

Abstract Neuromorphic computing takes biological inspiration to the device level aiming to improve computational efficiency and capabilities. One of the major issues that arises is the training of neuromorphic hardware systems. Typically training algorithms require global information and are thus inefficient to implement directly in hardware. In this paper we describe a set of reinforcement learning based, local weight update rules and their implementation in superconducting hardware. Using SPICE circuit simulations, we implement a small-scale neural network with a learning time of order one nanosecond per update. This network can be trained to learn new functions simply by changing the target output for a given set of inputs, without the need for any external adjustments to the network. Further, this architecture does not require programing explicit weight values in the network, alleviating a critical challenge with analog hardware implementations of neural networks.

Hovhannisyan R.A., Grebenchuk S.Y., Larionov S.A., Shishkin A.G., Grebenko A.K., Kupchinskaya N.E., Dobrovolskaya E.A., Skryabina O.V., Aladyshkin A.Y., Dremov V.V., Golovchanskiy I.A., Samokhvalov A.V., Mel’nikov A.S., Roditchev D., Stolyarov V.S.

Pikunov P.V., Pashin D.S., Bastrakova M.V.

Sergeev M., Bastrakova M., Vozhakov V., Soloviev I., Klenov N., Kulandin D., Linyov A.

Wanta G.C., Kurniawan C., Wibowo N.A.

Abstract Spintronic device development relies on an understanding of magnetization dynamics in permalloy thin films, as it reveals the material's properties and magnetization reversal mechanism through the propagation of the domain wall controlled by the external magnetic field pulse. This study explores the impact of Gaussian magnetic pulse width and height on magnetization rate in permalloy thin films using micromagnetic simulations based on the Landau-Lifshitz-Gilbert (LLG) equation. The examined Gaussian magnetic pulse heights were 200 mT and 500 mT, respectively, and the corresponding pulse width varied from 200 to 2000 ps. The size of the permalloy thin film also varied. After exposure to a Gaussian magnetic pulse, the magnetic moments become magnetized and oscillate. Oscillation or ringing can result from the interaction between the magnetic pulse and spin and is impacted by a low damping value. The magnetization reversal rate will reach a constant value at each critical pulse width. The amplitude of the magnetic field and thin film sizes influence the critical pulse width. The primary component influencing the permalloy thin film magnetic energy during the magnetization reversal is demagnetization energy, which leads to the onset of a single domain. The study suggests that spintronic devices can modify read-write data on the permalloy thin film using either a high-intensity magnetic field with a short pulse duration or a low-intensity magnetic field with a longer pulse duration. Nonetheless, it is essential to take into account the size of the thin layer to enhance the efficiency of spintronic devices.

Khomitsky D.V., Bastrakova M.V., Pashin D.S.

Yakovlev D.S., Frolov A.V., Nazhestkin I.A., Temiryazev A.G., Orlov A.P., Shvartzberg J., Dizhur S.E., Gurtovoi V.L., Hovhannisyan R., Stolyarov V.S.

AbstractTopological insulator nanostructures became an essential platform for studying novel fundamental effects emerging at the nanoscale. However, conventional nanopatterning techniques, based on electron beam lithography and reactive ion etching of films, have inherent limitations of edge precision, resolution, and modification of surface properties, all of which are critical factors for topological insulator materials. In this study, an alternative approach for the fabrication of ultrathin Bi2Se3 nanoribbons is introduced by utilizing a diamond tip of an atomic force microscope (AFM) to cut atomically thin exfoliated films. This study includes an investigation of the magnetotransport properties of ultrathin Bi2Se3 topological insulator nanoribbons with controlled cross‐sections at ultra‐low 14 mK) temperatures. Current‐dependent magnetoresistance oscillations are observed with the weak antilocalization effect, confirming the coherent propagation of 2D electrons around the nanoribbon surface's perimeter and the robustness of topologically protected surface states. In contrast to conventional lithography methods, this approach does not require a highly controlled clean room environment and can be executed under ambient conditions. Importantly, this method facilitates the precise patterning and can be applied to a wide range of 2D materials.

Hyyppä E., Vepsäläinen A., Papič M., Chan C.F., Inel S., Landra A., Liu W., Luus J., Marxer F., Ockeloen-Korppi C., Orbell S., Tarasinski B., Heinsoo J.

Improving the speed and fidelity of quantum logic gates is essential to reach quantum advantage with future quantum computers. However, fast logic gates lead to increased leakage errors in superconducting quantum processors based on qubits with low anharmonicity, such as transmons. To reduce leakage errors, we propose and experimentally demonstrate two new analytical methods, Fourier ansatz spectrum tuning derivative removal by adiabatic gate (FAST DRAG) and higher-derivative (HD) DRAG, both of which enable shaping single-qubit control pulses in the frequency domain to achieve stronger suppression of leakage transitions compared to previously demonstrated pulse shapes. Using the new methods to suppress the ef transition of a transmon qubit with an anharmonicity of −212 MHz, we implement RX(π/2) gates achieving a leakage error below 3.0×10−5 down to a gate duration of 6.25 ns without the need for iterative closed-loop optimization. The obtained leakage error represents a 20-fold reduction in leakage compared to a conventional cosine DRAG pulse. Employing the FAST DRAG method, we further achieve an error per gate of (1.56±0.07)×10−4 at a 7.9-ns gate duration, outperforming conventional pulse shapes both in terms of error and gate speed. Furthermore, we study error-amplifying measurements for the characterization of temporal microwave control-pulse distortions, and demonstrate that non-Markovian coherent errors caused by such distortions may be a significant source of error for sub-10-ns single-qubit gates unless corrected using predistortion. Published by the American Physical Society 2024

Bafia D., Murthy A., Grassellino A., Romanenko A.

Zakharov R.V., Tikhonova O.V., Klenov N.V., Soloviev I.I., Antonov V.N., Yakovlev D.S.

AbstractA basic element of a quantum network based on two single‐mode waveguides is proposed with different frequencies connected by a solid‐state qubit. Using a simple example of a possible superconducting implementation, the usefulness of the simplifications used in the general theoretical consideration has been justified. The non‐classical field in a single‐mode with a frequency of is fed to the input of a qubit controller and transformed into a non‐classical field in an output single‐mode with a frequency of . The interface can establish a quantum connection between solid‐state and photonic flying qubits with adjustable pulse shapes and carrier frequencies. This allows quantum information to be transferred to other superconducting or atomic‐based quantum registers or chips. The peculiarities of the wave‐qubit interactions are described, showing how they help to control the quantum state of the non‐classical field. On this basis, the operating principles of solid‐state and flying qubits for the future quantum information platforms are considered.

Kozlov S., Lesueur J., Roditchev D., Feuillet-Palma C.

AbstractThe electron transport in current-biased superconducting nano-bridges is determined by the motion of the quantum vortex confined in the internal disorder landscape. Here we consider theoretically a simple case of a single or two neighbouring linear defects crossing a nano-bridge. The strong anharmonicity of the vortex motion along the defect leads, upon radio frequency (RF) excitation, to fractional Shapiro steps. In the case of two defects, the vortex motion becomes correlated, characterised by metastable states that can be locked to the RF-drive. The lock-unlock process causes sudden voltage jumps and drops in the voltage-current characteristics that can be observed in experiments. We analyse the parameters that promote these metastable dynamic states and discuss their possible experimental realisations.

Uludağ R.B., Çağdaş S., İşler Y.S., Şengör N.S., Akturk I.

Abstract Neuromorphic systems are designed to emulate the principles of biological information processing, with the goals of improving computational efficiency and reducing energy usage. A critical aspect of these systems is the fidelity of neuron models and neural networks to their biological counterparts. In this study, we implemented the Izhikevich neuron model on Intel's Loihi 2 neuromorphic processor. The Izhikevich neuron model offers a more biologically accurate alternative to the simpler Leaky-Integrate and Fire (LIF) model, which is natively supported by Loihi 2. We compared these two models within a basic two-layer network, examining their energy consumption, processing speeds, and memory usage. Furthermore, to demonstrate Loihi 2's ability to realize complex neural structures, we implemented a basal ganglia circuit to perform a Go/No-Go decision-making task. Our findings demonstrate the practicality of customizing neuron models on Loihi 2, thereby paving the way for constructing Spiking Neural Networks (SNNs) that better replicate biological neural networks and have the potential to simulate complex cognitive processes.

Hovhannisyan R.A., Golod T., Krasnov V.M.

The utilization of Josephson vortices as information carriers in superconducting digital electronics is hindered by the lack of reliable displacement and localization mechanisms. In this Letter, we experimentally investigate planar Nb junctions with an intrinsic phase shift and nonreciprocity induced by trapped Abrikosov vortices. We demonstrate that the entrance of a single Josephson vortex into such junctions triggers the switching between metastable ±π semifluxon states. We showcase controllable manipulation between these states using short current pulses and achieve a nondestructive readout by a nearby junction. Our observations pave the way toward ultrafast and energy-efficient digital Josephson electronics. Published by the American Physical Society 2024

Abramson J., Adler J., Dunger J., Evans R., Green T., Pritzel A., Ronneberger O., Willmore L., Ballard A.J., Bambrick J., Bodenstein S.W., Evans D.A., Hung C., O’Neill M., Reiman D., et. al.

AbstractThe introduction of AlphaFold 21 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design2–6. Here we describe our AlphaFold 3 model with a substantially updated diffusion-based architecture that is capable of predicting the joint structure of complexes including proteins, nucleic acids, small molecules, ions and modified residues. The new AlphaFold model demonstrates substantially improved accuracy over many previous specialized tools: far greater accuracy for protein–ligand interactions compared with state-of-the-art docking tools, much higher accuracy for protein–nucleic acid interactions compared with nucleic-acid-specific predictors and substantially higher antibody–antigen prediction accuracy compared with AlphaFold-Multimer v.2.37,8. Together, these results show that high-accuracy modelling across biomolecular space is possible within a single unified deep-learning framework.

Tolpygo S.K., Rastogi R., Weir T., Golden E.B., Bolkhovsky V.

Ucpinar B.Z., Karamuftuoglu M.A., Razmkhah S., Pedram M.

Feldhoff F., Toepfer H.

Bal M., Murthy A.A., Zhu S., Crisa F., You X., Huang Z., Roy T., Lee J., Zanten D.V., Pilipenko R., Nekrashevich I., Lunin A., Bafia D., Krasnikova Y., Kopas C.J., et. al.

AbstractWe present a transmon qubit fabrication technique that yields systematic improvements in T1 relaxation times. We encapsulate the surface of niobium and prevent the formation of its lossy surface oxide. By maintaining the same superconducting metal and only varying the surface, this comparative investigation examining different capping materials, such as tantalum, aluminum, titanium nitride, and gold, as well as substrates across different qubit foundries demonstrates the detrimental impact that niobium oxides have on coherence times of superconducting qubits, compared to native oxides of tantalum, aluminum or titanium nitride. Our surface-encapsulated niobium qubit devices exhibit T1 relaxation times 2–5 times longer than baseline qubit devices with native niobium oxides. When capping niobium with tantalum, we obtain median qubit lifetimes above 300 μs, with maximum values up to 600 μs. Our comparative structural and chemical analysis provides insight into why amorphous niobium oxides may induce higher losses compared to other amorphous oxides.

Shrestha S.B., Timcheck J., Frady P., Campos-Macias L., Davies M.

Karimov T., Ostrovskii V., Rybin V., Druzhina O., Kolev G., Butusov D.

Josephson junctions (JJs) are superconductor-based devices used to build highly sensitive magnetic flux sensors called superconducting quantum interference devices (SQUIDs). These sensors may vary in design, being the radio frequency (RF) SQUID, direct current (DC) SQUID, and hybrid, such as D-SQUID. In addition, recently many of JJ’s applications were found in spiking models of neurons exhibiting nearly biological behavior. In this study, we propose and investigate a new circuit model of a sensory neuron based on DC SQUID as part of the circuit. The dependence of the dynamics of the designed model on the external magnetic flux is demonstrated. The design of the circuit and derivation of the corresponding differential equations that describe the dynamics of the system are given. Numerical simulation is used for experimental evaluation. The experimental results confirm the applicability and good performance of the proposed magnetic-flux-sensitive neuron concept: the considered device can encode the magnetic flux in the form of neuronal dynamics with the linear section. Furthermore, some complex behavior was discovered in the model, namely the intermittent chaotic spiking and plateau bursting. The proposed design can be efficiently applied to developing the interfaces between circuitry and spiking neural networks. However, it should be noted that the proposed neuron design shares the main limitation of all the superconductor-based technologies, i.e., the need for a cryogenic and shielding system.

Birge N.O., Satchell N.

The past two decades have seen an explosion of work on Josephson junctions containing ferromagnetic materials. Such junctions are under consideration for applications in digital superconducting logic and memory. In the presence of the exchange field, spin–singlet Cooper pairs from conventional superconductors undergo rapid phase oscillations as they propagate through a ferromagnetic material. As a result, the ground-state phase difference across a ferromagnetic Josephson junction oscillates between 0 and π as a function of the thickness of the ferromagnetic material. π-junctions have been proposed as circuit elements in superconducting digital logic and in certain qubit designs for quantum computing. If a junction contains two or more ferromagnetic layers whose relative magnetization directions can be controlled by a small applied magnetic field, then the junction can serve as the foundation for a memory cell. Success in all of those applications requires careful choices of ferromagnetic materials. Often, materials that optimize magnetic properties do not optimize supercurrent propagation, and vice versa. In this review, we discuss the significant progress that has been made in identifying and testing a wide range of ferromagnetic materials in Josephson junctions over the past two decades. The review concentrates on ferromagnetic metals, partly because eventual industrial applications of ferromagnetic Josephson junctions will most likely start with metallic ferromagnets (either in all metal junctions or junctions containing an insulating layer). We will briefly mention work on non-metallic barriers, including ferromagnetic insulators, and some of the exciting work on spin–triplet supercurrent in junctions containing non-collinear magnetic inhomogeneity.