The small-sized, low-voltage, and low-inductive KING generator (190–230 kA, 40 kV, 200–240 ns) was specially designed to work with X-pinches; however, it was unstable in its original design. In the present work, it is experimentally shown that an increase in the inductance of the output node of the generator led to the stable formation of not only bright but also hot spots. This is the first time the plasma parameters of hot and bright spots generated in hybrid X-pinches on a low-inductive low-voltage generator have been experimentally determined using x-ray spectroscopy with spatial resolution. The parameters of the radiation sources of both hot and bright spots are sufficient for their use in point-projection radiography of plasma, biological, and solid-state objects with a spatial resolution of 3 to 10 µm and a temporal resolution of about 1 ns.

Recent studies have established correlations between nonaffine motion and macroscopic stress fluctuations in sheared granular media. However, a comprehensive examination of the relationship between nonaffine motion, macroscopic stress fluctuations, and interparticle forces remains lacking. We investigated this interplay in simulations of two-dimensional granular media during stick-slip events under plane shear. We found that, during most large slip events, particles with the greatest nonaffine motion, as quantified by $D_{min}^2$, initially coalesce into one or two dominant connected clusters. These clusters coincide with the region exhibiting the greatest instantaneous reduction in interparticle forces, indicating a significant correlation between interparticle force fluctuations and particle rearrangements. Furthermore, the magnitude of the greatest nonaffine motion within these clusters correlates strongly with the magnitude of macroscopic stress fluctuations during slip events. This correlation increased when the nonaffine motion of particles in a neighborhood around the point of greatest nonaffine motion was included in the analysis, suggesting that plastic events are best understood as regional rather than pointlike occurrences. Our results held for various interparticle friction coefficients. Our findings suggest that elastoplastic models should consider plastic events as regional rather than pointlike and highlight the importance of studying the propagation of particle rearrangements.

For low-velocity impacts into granular materials, most of the impact energy is absorbed by the soil and not transferred into the ejected material. That raises the question of how large the volume of material is that is actually affected by the impact, that is, by subsurface material displacement or compaction. Here we use diffusing wave spectroscopy to detect the changes in local soil packing structure before, during, and after an impact has occurred. We clearly identify a (half)-spherical volume where particles are rearranged, with a radius substantially larger than the diameter of the impact crater. We also show that the size of the rearrangement zone follows similar scaling laws as the crater size.

The ferroelectric nematic ($N_f$) liquid crystal phase is a highly polar fluid, with spontaneous polarization ($P_S$) values of the order of $\mu \mathrm{C}\mathrm{c}{\mathrm{m}}^{-2}$ and viscosities of around 10 Pas. The combination of high polarity and fluidity makes these materials unique polar dielectrics. We consider the free energy of the ferroelectric nematic phase and derive its thermodynamic potentials. This allows us to predict that the spontaneous polarization will saturate as a function of applied voltage, rather than field. Further, we determine that the inclusion of an alignment layer, which is usual in liquid crystal devices, could provide a significantly enhanced energy barrier to switching. Indeed, an insulating alignment layer introduces a polar anchoring energy in addition to the orientational anchoring energy usually considered in liquid crystal devices. We confirm experimentally that measurements of the spontaneous polarization depend very slightly on the thickness of the $N_f$ layer and more dramatically on the polar interactions of the phase with the confining surfaces. In relatively thin devices ($\sim 10\mu \mathrm{m}$) with an alignment layer present, we demonstrate that this effect can be so pronounced that polarization switching is completely suppressed. We also explore the influence of the preparation conditions of a thin film of ferroelectric nematic material on the stability and lifetime of the sample.

We set up and study the hydrodynamic theory for inversion-symmetric active fluid and tethered membranes. For some choices of the activity parameter, such membranes are stable and described by linear hydrodynamic equations, which are exact in the asymptotic long wavelength limit, giving stable flat phases with translational quasi-long-range orders. For other choices of the activity parameter, the system is linearly unstable in the long wavelength limit, implying crumpling, or has intermediate wave-vector instabilities, suggesting patterns. We argue that in such an active membrane thermal noises dominate over any active noises, and use those to calculate the correlation functions of membrane conformation fluctuations in the stable case, and the associated correlation functions of the embedding bulk flow velocities. Our work identifies a hitherto unknown activity-induced route, distinct from the well-known thermal crumpling of equilibrium fluid membranes, to destabilize a membrane.

We have explored and analyzed the outcome data from several simulated superstatistical time series including an $E^{\mu -1}$ density of states. Among the three main classes of superstatistics (SS), we have chosen the one that imposes a gamma distribution $g\left(\beta \right)$ for the fluctuating intensive parameter $\beta$. In our analysis, we have generated a set of synthetic time series through a simple algorithm, which provided us different dynamical scenarios by setting some relevant superstatistical parameters. In each emerging scenario, multifractal detrended fluctuation analysis (MFDFA) was applied to evaluate the corresponding singularity spectrum width $\mathrm{\Delta }\alpha$. With this information we have characterized the complexity' degree of each superstatistical time series. The results show that the complexity is strongly dependent on the shape parameter $\nu$ of $g\left(\beta \right)$ and that, in any of these cases, the parameter $\mu$ associated with the density of states smoothly increases said complexity. A multiple regression model shows that although $\mu$ and $\nu$ do not interact significantly, they do act complementary to describe the system's complexity as measured by $\mathrm{\Delta }\alpha$. This analysis confirms that the simulated data could represent the behavior of some complex systems whose complexity can be effectively described by the regression model through $\mu$ and $\nu$. This conclusion is further supported by the assessment of eight SYM-H magnitude datasets, taken during periods of maximum and minimum solar activity, where predicted $\mathrm{\Delta }\alpha$ values are reasonably close to the corresponding values obtained through the MFDFA.

We explore the impact of global resetting on Kuramoto-type models of coupled limit-cycle oscillators with distributed frequencies both in absence and presence of noise. The dynamics comprises repeated interruption of the bare dynamics at random times with simultaneous resetting of phases of all the oscillators to a predefined state. To characterize the stationary-state behavior, we develop an analytical framework that spans across different generalizations of the Kuramoto model involving either quenched or annealed disorder or both, and for any choice of the natural frequency distribution. The framework applies to the dynamics both in absence and presence of resetting, and is employed to obtain, in particular, the stationary-state synchronization order parameter of the system, which is a measure of spontaneous ordering among the oscillator phases. A key finding is the pivotal role of correlations in shaping the ordering dynamics under resetting.

In recent years, numerous mathematical models of opinion formation have been developed, incorporating diverse interaction mechanisms such as imitation and majority rule. However, limited attention has been given to models grounded in persuasive arguments theory (PAT), which describes how individuals may alter their opinions through the exchange of arguments during discussions. Moreover, analytical investigations of PAT-based models remain sparse. In this study, we propose an analytical model rooted in PAT, demonstrating that a group of agents can exhibit two distinct collective dynamics: quasiconsensus and bipolarization. Specifically, we explore various scenarios characterized by the number of arguments and the degree of homophily, revealing that bipolarization arises within this framework only in the presence of homophily.

We study continuous time random walks on a network. We find that the steady state of the random walk on a given node is independent of the nature of the distribution of waiting times $\psi \left(\tau \right)$ and depends only on the local neighborhood of the node. The relaxation toward the steady state is, however, dependent on $\psi \left(\tau \right)$. For $\psi \left(\tau \right)\stackrel{\text{large}\tau }{\sim }{\tau }^{-1-\alpha },0<\alpha <1$, the relaxation behavior depends on $\alpha$. For $\alpha >1,\psi \left(\tau \right)$ possesses a finite mean and the relaxation exhibits a scaling behavior independent of the specific details of $\psi \left(\tau \right)$. We find that the distribution of recurrence times for a given node possesses the same qualitative form as $\psi \left(\tau \right)$. Starting from a node $i$, we study the mean number of distinct nodes visited by the random walk $\langle S_i\left(t\right)\rangle$, and find that analogous to the relaxation behavior, its properties are dependent on the exponent $\alpha$. Interestingly, $\langle S_i\left(t\right)\rangle$ grows algebraically with time; that is, $\langle S_i\left(t\right)\rangle \sim t^{\alpha }$ for $\alpha <1$. On the other hand, for $\alpha >1,\langle S_i\left(t\right)\rangle \sim Nf(t/N\langle \tau \rangle )$, with the scaling function $f$ depending only on the structural details of the network of size $N$. In addition, for exponentially distributed waiting times, $\langle S_i\left(t\right)\rangle$ grows linearly with $t$ at small times for homogeneous networks.

Subdiffusion is argued to be forbidden in a classical homogenous Hamiltonian system due to finiteness of the Poincaré recurrence time. Recently, long-range-interaction-induced subdiffusion has been revealed, which questions the above argument. In this Letter, we study a one-dimensional ${\phi }^4$ lattice and present convincing evidence in various aspects that in strong nonlinearity regimes energy transport can be subdiffusive in such a system with neither disorder nor long-range interaction. The calculation of energy diffusivity and conductivity both indicate subdiffusive energy transport and they are in quantitatively consistent with each other. The normal-to-subdiffusive conversion can be understood by match and mismatch between the power spectra and the phonon band of the lattice.

A Schrödinger bridge is the most probable time-dependent probability distribution that connects an initial probability distribution $w_i$ to a final one $w_f$. The problem has been solved and widely used for the case of simple Brownian evolution (noninteracting particles). It is closely related to the problem of entropy-regularized Wasserstein optimal transport. In this article, we generalize the problem to systems of interacting particles. We derive some equations for the forward and backward single-particle “wave functions,” which allows computation of the most probable evolution of the single-particle probability between the initial and final distributions.

This study presents a comparative analysis of three quantum thermal engines utilizing a two-qubit Heisenberg XXZ chain as the working substance. A novel generalized quantum Otto cycle (GQOC) is introduced, featuring two distinct coupling configurations to thermal reservoirs. The GQOC exhibits the potential for 100% efficiency, surpassing the efficiency of the conventional quantum Otto cycle. Essential conditions for positive work extraction and achieving maximum unity efficiency are derived. An experimental implementation using quantum electrodynamic circuits and Transmon qudit is proposed. This work contributes to the advancement of quantum heat engines, highlighting the benefits of nonequilibrium processes and asymmetric coupling for enhanced work extraction and efficiency.

We introduce an exactly solvable model of a randomly decorated two-leg spin-ladder that incorporates the topology and main magnetic interactions in CuO ladders found in several cuprate superconducting ceramics. Copper ions at the nodal sites have $S=1/2$. Oxygen ions at the bonds have a random fraction of $S=1/2$ spins due to hole doping. Annealed disorder is assumed to result from the thermal equilibrium with the hole reservoir. Using the transfer matrix technique, we derive the exact thermodynamic behavior and explore its main features. After raising the exact ground-state diagram as a function of the chemical potential and exchange ratio, we explore the thermodynamic signatures of the influence of the model parameters on the entropy and specific heat curves, unveiling competing spin correlations. Finally, we show that distinct hole concentrations in the ladder's legs and rungs are developed, especially when the strength of the Cu-O exchange coupling is larger than the Cu-Cu coupling, as in superconducting cuprate ceramics. We show that for weak Cu-O couplings, thermal fluctuations promote a bias toward a larger hole concentration in the ladder's rungs. For strong Cu-O couplings, magnetic frustration leads to distinct hole concentrations even at zero temperature, with a bias toward the rungs for low doping fractions and the reversed trend toward the ladder's legs at high doping levels.

The development of synchronization and chimera states plays an extremely important role in the collective activity of systems of interacting neurons. For this reason, it is crucial from both fundamental and applied perspectives to investigate empirically relevant (in a biological sense) configuration models that support analytical studies of the development of partial synchronization states. Herein we consider a system of superdiffusively coupled neurons from the limiting case perspective of the linear stability of two-component reaction-superdiffusion equations. It is found that extended linear analysis in the parameter space of the fractional Laplace operator exponents is able to characterize the configuration features of networks of superdiffusively coupled neurons supporting both the development of full and partial synchronization, as well as states of full incoherence. The possibility of not only numerical but also analytical study in a continuous perspective of superdiffusion neural networks opens new opportunities for problems of chimera state control, as well as providing extended possibilities to design functional zones on the basis of these systems.

Magnetized fusion has been used in various inertial confinement fusion concepts to relax ignition requirements. Strong magnetic fields would induce burning asymmetry, which may be usually harmful to the central ignition schemes. However, it could be utilized in some intrinsically asymmetric ignition schemes, such as the traditional fast ignition (FI) scheme and the double-cone ignition (DCI) scheme, in which the hot spots are located at the edge of the compressed fuel. In this paper, an analytical model and a three-dimensional MHD code are developed to study the asymmetric burning propagation and related effects in magnetic fields. It is found that the magnetic field can guide a directional and faster burning propagation along the parallel direction to the B-field by the anisotropic $\alpha$-particle transport, providing a method to control the burning behavior. The B-field also leads to a faster increase in the hot spot temperature. Simulation shows that 10 kT B-fields, corresponding to the $\alpha$-particle Hall parameter of $H_{\alpha }\sim 0.5,$ would increase the hot spot temperature by 38% and the burning propagation speed by 44% in FI and DCI conditions, leading to an 87% increase of the fusion output energy and an 18% increase of hot spot mass. This study could also provide a direct reference for assessing the burning asymmetry in the magnetized ICF schemes.

In this work, the conformational dynamics of the von Willebrand Factor (vWF) are investigated as it encounters localized regions of high shear and extensional forces in a converging/diverging channel. Using direct numerical simulations that employ two-way coupling between a lattice Boltzmann fluid solver and a Langevin dynamics-based bead-spring model for vWF, we study how flow-induced forces influence the spatiotemporal evolution of molecular unfolding. Unlike studies that rely on statistical models or averaged behavior, our approach captures transient and configuration-specific unfolding events that arise from the interplay between molecular conformation and flow-field structure. In the simulations, the vWF passes through a straight section of pipe with subcritical shear rates before entering a converging/diverging section where shear and extension rates exceed the known critical threshold for vWF unfolding. Streamwise extension and conformational states are analyzed over time. Results show that while vWF may unfurl in the converging/diverging sections, the likelihood of such events is significantly influenced by the vWF's initial conformation upon entering these regions. Notably, increasing the flow rate to elevate shear and extension rates does not necessarily enhance unfolding likelihood in the converging/diverging section due to its greatly reduced residence time.

We consider the effects of temperature anisotropy in a quiescent, hard sphere gas, as a model system for flowing granular matter. Utilising kinetic theory we obtain expressions for the streaming pressure, collisional pressure and the rate of transfer of kinetic energy between the different translational degrees of freedom, assuming a Maxwell-Boltzmann velocity distribution and an isotropic pair correlation function at contact. A theory for the collisional pressure with an anisotropic pair correlation function is also presented. Event driven simulations are carried out for frictionless, elastic, hard spheres, using a thermostat that maintains a different temperature in one of the coordinate directions. The pair correlation function, the velocity distribution function, streaming and collisional pressures, and the rate of energy transfer are computed in the simulations for different temperature anisotropy values. The pair correlation function becomes significantly anisotropic with increasing temperature anisotropy and solid fraction. The streaming pressure and the energy transfer rate are well described by the theory based on the isotropic pair correlation function. The predictions of this theory for the collisional pressure match well with the results of the simulations for a solid fraction of 0.1, but increasing deviations are obtained for higher solid fractions. The theory incorporating the anisotropy in the pair correlation function gives good predictions of the collisional pressure for all the solid fractions considered. The work shows the importance of incorporating the anisotropy in the pair correlation function in kinetic theories for systems with temperature anisotropy.

A quantum eigenstate of a classically chaotic system is referred to as scarred by an unstable periodic orbit if its probability density is concentrated in the vicinity of that orbit. Recently, a new class of scarring - variational scarring - was discovered in numerical studies of disordered quantum dots, arising from near-degeneracies in the quantum spectrum associated with classical resonances of the unperturbed system. Despite the increasing body of theoretical evidence on variational scarring, its experimental observation has remained out of reach. Motivated by this dearth, we argue and demonstrate that variational scarring can occur in an elliptical quantum dot fabricated on monolayer graphene, and locally perturbed by a nanotip. Then, we further show that the fingerprint of these variational scars can potentially be detected via scanning tunneling microscopy, thus offering an attractive experimental pathway for the first validation of this puzzling quantum-chaotic phenomenon.

Bursting oscillations, characterized by alternating patterns of rapid oscillations and quiescence, is a prototypical form of complex dynamics that can emerge in both in low-dimensional systems and networks of coupled dynamical systems. Such bursting patterns are frequently observed in a wide range of systems, including neuronal models, electronic circuits, and laser models. However, the mechanisms governing the conditions under which bursting is initiated remain challenging from the nonlinear dynamics viewpoint. In this work, we investigate the emergence of bursting in the Chialvo model, a map-based neuron model, focusing on a critical parameter region near a crisis bifurcation where the deterministic system rests at a stable equilibrium. In the deterministic setting, we demonstrate that (i) chaotic bursting arises suddenly due to the bifurcation structure, (ii) interburst intervals follow a power-law distribution, and (iii) long chaotic transients may precede convergence to the stable state. Under stochastic influences, we uncover a range of nontrivial phenomena, including noise-induced bursting, coherence resonance, and transitions from regular to chaotic activity. By employing stochastic sensitivity analysis and confidence ellipses, we predict noise-induced transition thresholds and confirm them via numerical simulations. These findings provide new insights into how stochastic fluctuations interact with underlying bifurcation structures to generate rich and complex bursting patterns in low-dimensional systems, shedding light on mechanisms that may also be relevant for neuronal networks.