We developed a machine learning algorithm designed to predict the spatial distribution of the pairing potential in a quasi-one-dimensional superconductor based on a given disorder profile. This approach uses the ability of neural networks to learn mappings between disorder configurations and the corresponding superconducting pairing potential, bypassing the need for iterative numerical solutions of the Bogoliubov-de Gennes equations.

In this paper we review recent progress in the theoretical understanding of the peculiarities of photogalvanic phenomena, photon drag, and the inverse Faraday effects in superconductors and hybrid superconducting structures. Our study is based on the time-dependent Ginzburg-Landau theory with a complex-valued relaxation constant, which provides the simplest description of the mechanisms of the second-order nonlinear effects in the electrodynamic response and related mechanisms for the generation of dc photocurrents and magnetic moment, as well as switching between different current states under the influence of electromagnetic radiation of various polarizations.

The paper presents an overview of the magnetic resistive memory varieties, discusses their design features, weaknesses and benefits, and provides a comparative characteristic. A review of a combined mathematical model that jointly describes the change of spins and coordinates of atoms (spin-lattice dynamics) is given. In general, the model can use any form of interatomic force potential and describes various contributions to the magnetic Hamiltonian. In this work, a simplified form of the magnetic Hamiltonian, taking into account only the Zeeman and exchange interactions, was considered to investigate magnetic interactions. The described model is implemented in the SPIN software package in the freely distributed LAMMPS complex. In this work, computational experiments were performed using the MEAM potential.

We recently demonstrated that the dielectric permittivity of a single-layer SrTiO₃ thin film decreases with increasing thickness, and that incorporation of intermediate AlFeO₃ layers into an SrTiO₃ /AlFeO₃ heterostructure mitigates this suppression of dielectric properties. We proposed two temperature-dependent mechanisms that could contribute to this effect: thermal strain and the formation of polar nanoregions (PNRs). In this study, we used Raman spectroscopy to assess the possibility of PNR formation in single-layer SrTiO₃ films (50 and 250 nm thick) and in a multilayer heterostructure 5×[50 nm SrTiO₃ + 50 nm AlFeO₃ . Our results show that the spectra of SrTiO₃-containing structures exhibit telltale signs of PNR formation: the presence of symmetry-forbidden first-order modes and an asymmetric shape of the TO₂ mode.

We provide an overview of the methodology and fundamental principles associated with newly developed experimental technique -- scanning quantum-vortex microscopy. This approach appears promising for experimental studies of vortex pinning phenomena in superconducting films and nanodevices. In particular, we studied the magnetic properties of magnetron-sputtered niobium (Nb) films by low-temperature magnetic force microscopy. As the temperature approaches the superconducting critical temperature, the pinning potential caused by structural defects weakens; consequently, the attractive interaction between the magnetic tip of the cantilever and a single-quantum vortex begins to dominate. In this scenario the magnetic probe is capable of trapping a vortex during the scanning process. Because the dragged vortex continues interacting with structural defects, it serves as an efficient nano-probe to explore pinning potentials and visualize grain boundaries in granular Nb films, achieving resolutions (30 nm) comparable to the superconducting coherence length.

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.

It is well-known that the cornerstone of the proximity effect in superconductor/ferromagnet heterostructures is a generation of triplet Cooper pairs from singlet Cooper pairs inherent in a conventional superconductor. This proximity effect brought a lot of new exciting physics and gave a powerful impulse to development of superconducting spintronics. Nowadays a new direction of spintronics is actively developing, which is based on antiferromagnets and their heterostructures. It is called antiferromagnetic spintronics. By analogy with an important role played by triplet Cooper pairs in conventional superconducting spintronics based on ferromagnets the question arises: does the triplet proximity effect exist in superconductor/antiferromagnet heterostructures and, if so, what are the properties of the induced triplet correlations and the prospects for use in superconducting spintronics? Recent theoretical findings predict that despite the absence of a net magnetization, the Néel magnetic order of the antiferromagnet does give rise to specific spin-triplet correlations at superconductor/antiferromagnet interfaces. They were called Néel triplet correlations. The goal of this review is to discuss the current understanding of the fundamental physics of these Néel triplet correlations and their physical manifestations.

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.

Terahertz time-domain spectroscopy is used to perform the first detailed studies of the electrodynamic properties of MoRe (60\( \% \)/40\( \% \)) films with thicknesses ranging from 10 to 100 nm. Films are prepared by magnetron sputtering technique on silicon substrates. The critical temperatures vary from \( 6.5\, \textrm{K} \) (for 10 nm film) to \( 9.5\, \textrm{K} \) (for 100 nm film). Spectra of complex permittivity, conductivity, refraction index, surface impedance and reflection coefficient for the films are acquired at frequencies \( 0.15 - 2.4\, \textrm{THz} \) (wavenumbers \( 5 – 80\, \textrm{cm}^{-1} \)) and in the temperature interval \( T=5\,–\, 300\,\textrm{K} \). For all films, temperature dependencies of the superconducting energy gap, penetration depth, superconducting condensate plasma frequency, and normalised superfluid density are obtained on a quantitative level. It is shown that the reduction of film thickness leads to a strong decrease of the critical temperature and magnitude of the energy gap. The observed suppression of superconductivity is assigned to reduction of the superconducting order parameter due to the contribution to the free energy of the electronic energy states at the surface of superconductor. The MoRe films with the obtained characteristics can be used in designing advanced superconducting electronic devices.

A Journal Facilitating Open Science Across the Intersect of Mesoscopic Physics and Nanotechnology