CyberSec Research

The recent discovery of compressed superconductivity at 80~K in La$_3$Ni$_2$O$_7$-$\delta$ has brought nickelates into the family of unconventional high-temperature superconductors. However, due to the challenges of directly probing the superconducting pairing mechanism under high pressure, the pairing symmetry and gap structures of nickelate superconductors remain under intense debate. In this work, we successfully determine the microscopic information on the superconducting gap structure of La$_3$Ni$_2$O$_7$-$\delta$ samples subjected to pressures exceeding 20~GPa, by constructing different conductance junctions within diamond anvil cells. By analyzing the temperature-dependent differential conductance spectra within the Blonder--Tinkham--Klapwijk (BTK) model, we have determined the superconducting energy gap at high pressure. The differential conductance curves reveal a two-gap structure with $\Delta_{1} = 23~\mathrm{meV}$ and $\Delta_{2} = 6~\mathrm{meV}$, while the BTK fitting is consistent with an $s$-like, two-gap spectrum. The gap ratio $2\Delta_{s1}(0) / k_{\mathrm{B}}T_{c}$ is found to be 7.61, belonging to a family of strongly coupled superconductors. Our findings provide valuable insights into the superconducting gap structures of the pressure-induced superconducting nickelates.

We review, critique, and extend results related to the problem of closed loop shape equilibria of a string shooter, a type of catenary consisting of steady, axially moving configurations of an inertial, inextensible, perfectly flexible string in the presence of gravity and drag forces. We highlight recurring misconceptions, and relate to similar problems, including the lariat (no gravity), chain fountain (not closed), and heavy \emph{elastica} (bending stiffness). We focus on the difficulty inherent to continuing a catenary through a vertical orientation, necessary to close a loop, which difficulty changes in nature as the system undergoes bifurcations with increasing drag. We construct solutions by implementing available analytical results, and numerically generate additional solutions with added bending stiffness. We briefly discuss global balances of linear, angular, and pseudo- momentum for this system.

Neural mass models describe the mean-field dynamics of populations of neurons. In this work we illustrate how fundamental ideas of physics, such as energy and conserved quantities, can be explored for such models. We show that time-rescaling renders recent next-generation neural mass models Hamiltonian in the limit of a homogeneous population or strong coupling. The corresponding energy-like quantity provides considerable insight into the model dynamics even in the case of heterogeneity, and explain for example why orbits are near-ellipsoidal and predict spike amplitude during bursting dynamics. We illustrate how these energy considerations provide a possible link between neuronal population behavior and energy landscape theory, which has been used to analyze data from brain recordings. Our introduction of near-Hamiltonian descriptions of neuronal activity could permit the application of highly developed physics theory to get insight into brain behavior.

A theory of a new magnetodynamic effect describing the energy exchange between the degrees of freedom of a conducting cylinder moving in a helical magnetic field has been developed. The possibility of effectively converting the translational motion of the cylinder into its angular rotation around the system axis (translational-rotational conversion, TRC) has been demonstrated. A connection between this effect and the formation of helical trajectories of electrons in undulators in free electron lasers (FELs) and the inverse Faraday effect (IFE) has been revealed. In TRC, unlike many known effects associated with the interaction of a moving conductor with a magnetic field, the conductor has no electrical contact with any external circuit, which makes it especially attractive for various applications. The TRC is also possible in a magnetohydrodynamic flow moving along the axis of a helical magnetic field. The theory is formulated in the limit of large magnetic Reynolds numbers, which corresponds to a sufficiently fast motion of well-conducting objects. In this scenario, the dynamics of the system is described by a nonlinear pendulum equation or a nonlinear pendulum equation with a nonzero right-hand side. In the latter case, a system dynamic mode corresponding to phase lock can be implemented.

We investigate the tension distribution in systems of mass-less ropes under different loading conditions. For a two-rope system, we demonstrate how the breaking scenario depends on the applied force dynamics: rapid pulling causes the lower rope to break, while gradual pulling leads to upper rope failure. Extending to a three-rope Y-shaped configuration, we identify a critical angle theta_C=60{\deg} that determines which rope breaks first. When the angle between the upper ropes exceeds this critical value, the upper ropes fail before the lower one. We further analyze how an attached mass at the junction point modifies this critical angle and establish maximum mass limits for valid solutions. Our results provide practical insights for introductory physics students understanding static forces and system stabilities.

The crucial role played by Wet Cooling Towers (WCT) in many electricity production plants (e.g. nuclear power plants) make them a key parameter in the industrial design of such facilities. Their impact over the cooling water consumption and surrounding atmosphere through the formation and dispersion of a humid air plume has pushed the need to obtain proper models and simulations in order to anticipate those effects. In this work, we tackle this issue through a dedicated modelling in the CFD solver code_saturne. Specific modeling includes heat and mass transfer (convection and evaporation) between the injected water and the air flow that are validated against experimental results obtained in a reduced scale WCT experimental loop. Satisfying agreement is obtained for several parameters such as air and water exit temperatures, evaporation mass flow rate and total exchanged thermal power. This constitutes an important first step for detailed CFD predictions of WCT water consumption and humid air plume atmospheric dispersion.

Electroactive polymers are smart materials that can be used as actuators, sensors, or energy harvesters. We focus on a pseudo trilayer based on PEDOT, a semiconductor polymer: the central part consists of two interpenetrating polymers and PEDOT is polymerized on each side; the whole blade is saturated with an ionic liquid. A pseudo trilayer is obtained, the two outer layers acting as electrodes. When an electric field is applied, the cations move towards the negative electrode, making it swell, while the volume decreases on the opposite side; this results in the bending of the strip. Conversely, the film deflection generates an electric potential difference between the electrodes. We model this system and establish its constitutive relations using the thermodynamics of irreversible processes; we obtain a Kelvin--Voigt stress--strain relation and generalized Fourier's and Darcy's laws. We validate our model in the static case: we apply the latter to a cantilever blade subject to a continuous potential electric difference at the constant temperature. We draw the profiles of the different quantities and evaluate the tip displacement and the blocking force. Our results agree with the experimental data published in the literature.

A framework is introduced for expressing electromagnetic (EM) potentials and fields of single atomic or molecular emitters modeled as oscillating dipoles, which follows a recently proposed method for solving inhomogeneous wave equations for arbitrary, time-dependent distributions of charge. This framework is first used to evaluate the physical implications of simplifying assumptions made in the standard approach to quantization of the EM fields and the impact of such assumptions on the results of energy and momentum quantization. Then, the exact expressions for the EM potentials and fields, in relation to the oscillating (transition) dipoles properties, afforded by the present framework are used to quantize electromagnetic fields from single emitters and restore the agreement with the well-known classical dipole radiation pattern, while maintaining the quantum mechanical description of electromagnetic radiation in terms of the probability distribution of quantum modes. Contributions of the present analysis to the understanding of photon emission from excited atoms or molecules stimulated by light or vacuum field fluctuations are highlighted, and possible experimental tests and practical applications are proposed.

Non-destructive evaluation (NDE) of rail tracks is crucial to ensure the safety and reliability of rail transportation systems. In this work, we present a quantitative study using various signal processing methods to identify defects in rail structures. A diffuse field configuration was employed at few dozens of kiloHertz, where the emitter and receiver were remotely located, and wave energy propagated via multiple reflections within the medium. A reference database is first constructed by acquiring measurements at different rail positions and different torque levels (up to 50 N.m). The defect is then identified by comparing its signature to those stacked in the database. First, the destretching technique, based on Coda Wave Interferometry (CWI), is applied to correct for temperature-induced velocity variations. Then, the identification is performed using the Mean Square Error (MSE) metric and Orthogonal Matching Pursuit (OMP) technique. A comparative analysis of the both methods is conducted, focusing on their robustness and performance.

The enormous energy demand of artificial intelligence is driving the development of alternative hardware for deep learning. Physical neural networks try to exploit physical systems to perform machine learning more efficiently. In particular, optical systems can calculate with light using negligible energy. While their computational capabilities were long limited by the linearity of optical materials, nonlinear computations have recently been demonstrated through modified input encoding. Despite this breakthrough, our inability to determine if physical neural networks can learn arbitrary relationships between data -- a key requirement for deep learning known as universality -- hinders further progress. Here we present a fundamental theorem that establishes a universality condition for physical neural networks. It provides a powerful mathematical criterion that imposes device constraints, detailing how inputs should be encoded in the tunable parameters of the physical system. Based on this result, we propose a scalable architecture using free-space optics that is provably universal and achieves high accuracy on image classification tasks. Further, by combining the theorem with temporal multiplexing, we present a route to potentially huge effective system sizes in highly practical but poorly scalable on-chip photonic devices. Our theorem and scaling methods apply beyond optical systems and inform the design of a wide class of universal, energy-efficient physical neural networks, justifying further efforts in their development.

The intricate complex eigenvalues of non-Hermitian Hamiltonians manifest as Riemann surfaces in control parameter spaces. At the exceptional points (EPs), the degeneracy of both eigenvalues and eigenvectors introduces noteworthy topological features, particularly during the encirclement of the EPs. Traditional methods for probing the state information on the Riemann surfaces involve static measurements; however, realizing continuous encircling remains a formidable challenge due to non-adiabatic transitions that disrupt the transport paths. Here we propose an approach leveraging the phase-locked loop (PLL) technique to facilitate smooth, dynamic encircling of EPs while maintaining resonance. Our methodology strategically ties the excitation frequencies of steady states to their response phases, enabling controlled traversal along the Riemann surfaces of real eigenvalues. This study advances the concept of phase-tracked dynamical encircling and explores its practical implementation within a fully electrically controlled non-Hermitian microelectromechanical system, highlighting robust in-situ tunability and providing methods for exploring non-Hermitian topologies.

We prove finite-time blowup of classical solutions for the compressible Upper Convective Maxwell (UCM) viscoelastic fluid system. By establishing a key energy identity and adapting Sideris' method for compressible flows, we derive a Riccati-type inequality for a momentum functional. For initial data with compactly supported perturbations satisfying a sufficiently large condition, all classical solutions lose regularity in finite time. This constitutes the first rigorous blowup result for multidimensional compressible viscoelastic fluids.

The present study investigates the dynamics of nonlocal beams by establishing a consistent stress-driven integral elastic using the Physics-Informed Neural Network (PINN) approach. Specifically, a PINN is developed to compute the first eigenfunction and eigenvalue arising from the underlying sixth-order ordinary differential equation. The PINN is based on a feedforward neural network, with a loss function composed of terms from the differential equation, the normalization condition, and both boundary and constitutive boundary conditions. Relevant eigenvalues are treated as separate trainable variables. The results demonstrate that the proposed method is a powerful and robust tool for addressing the complexity of the problem. Once trained, the neural network is less computationally intensive than analytical methods. The obtained results are compared with benchmark analytical solutions and show strong agreement.

This paper examines the intuitive meaning of the Saint--Venant compatibility equation known from the linear theory of deformations. The linearized theory is typically obtained from the relations of finite deformation theory by neglecting higher-order terms. We show how to formulate the compatibility conditions for finite deformations and how the well-known equation for small deformations follows from this formulation.

In physics geometrical connections are the mean to create models with local symmetries (gauge connections), as well as general diffeomorphisms invariance (affine connections). Here we study the irreducible tensor decomposition of connections on the tangent bundle of an affine manifold as used in the polynomial affine model of gravity. This connection is the most general linear connection, which allows us to build metric independent, diffeomorphism invariant models. This set up includes parts of the connection that are associated with conformal and projective transformations.

Because of a difference between his and our results for the Coulomb-gauge vector potential, Onoochin (arXiv:2507.08042) suspected that we might have used some (so far unidentified) mathematically illegal operations in our paper (arXiv:2507.02104). In this note, we present four methods to prove the validity of our results in dispute. Onoochin's method for calculating his Coulomb-gauge vector potential is among our four methods used in the proofs.

In Maxwell's equations, the electric field can be expressed as the sum of the Coulombic field associated with the electric charge and the induced field associated with the time variation of the magnetic field from Faraday's law. The same holds true for the displacement current densities, which are the time-derivatives of the respective electric fields. In the case of an AC current of constant amplitude, the amplitude of the displacement current density associated with the Coulombic field is independent of the frequency. In contrast, the displacement current density associated with the induced field is very small at low frequencies, increasing initially as the square of the frequency, and ultimately becomes of the same order of magnitude as that of the Coulombic field.

We study one-dimensional elastic collisions of three point masses on a line under vacuum, with no triple collisions. We express momentum conservation in matrix form and analyze the composite map $D=D_{BC}D_{AB}$ and its powers $D^k$, which yield the velocities after any prescribed number of collisions for arbitrary mass ratios and initial data. After that, using vector $u$ on a plane $s^\perp$, the total number of collisions is \[ n\;=\;1+\Big\lfloor\tfrac{\Omega-\phi_{BC}}{\theta}\Big\rfloor+\Big\lceil\tfrac{\Omega-\phi_{BC}}{\theta}\Big\rceil, \] Through this concept, $D$ is recognised as giving $u$ a rotation with angle $\theta$ which is determined by only mass ratios. And, we calculated energy transfer through collisions. With the work, we find that the change of energy is proportional to total momentum of two particles and average velocity of particles based on initial average velocity of A and B before collision.