We study the collective dynamics of swarmalators subjected to periodic (sinusoidal) forcing. Although previous research focused on the simplified case of motion in a one-dimensional (1D) periodic domain, we extend this analysis to the more realistic scenario of motion in two and three spatial dimensions with periodic boundary conditions. In doing so, we identify analogues of the 1D states and characterize their dynamics and stability boundaries analytically. Additionally, we investigate the forced swarmalators model with power-law interaction kernels, finding that the analytically tractable model with periodic boundary conditions can reproduce the observed dynamic behaviors of this more complex model.

In the framework of the one- and two-dimensional (1D and 2D) ${\varphi }^4$ equations, we elaborate a possibility to control the modulational instability (MI) of extended states by means of spatially periodic potentials, built in terms of the Jacobian elliptic functions. We demonstrate that both the 1D (longitudinal) and 2D (transverse) MIs of exact periodic snoidal states, found in the form of the elliptic sine, can be enhanced or completely suppressed by the snoidal squared potential, depending on the sign of the coefficient in front if it. The enhanced MI can support the generation of rogue waves, while the suppression of MI can open a way to create stable crystal structures (in particular, in ferroelectrics). The consideration is based on the calculation of the spectrum for small perturbations added to the stationary states, and confirmed by direct simulations of the perturbed evolution. In particular, a threshold (minimum) amplitude of the periodic potential, which provides the stabilization, is identified as a function of other parameters. In the 2D setting, the stabilization threshold is higher for the longitudinal MI than for its transverse counterpart.

We analyze the critical time series of the order parameter generated with active to inactive phase transitions of spreading dynamics running on the top of heterogeneous networks. Different activation mechanisms that govern the dynamics near the critical point were investigated. The time series were analyzed using the visibility graph (VG) method where a disassortative degree correlation of the VG is a signature of criticality. In contrast, assortative correlation is associated with off-critical dynamics. The signature of criticality given by the VG is confirmed for collective activation phenomena, as in the case of homogeneous networks. Similarly, for a localized activation driven by a densely connected set of hubs, identified by a maximum $k$-core decomposition, critical times series were also successfully identified by the VG method. However, in the case of activation driven by sparsely distributed hubs, the time series criticality is blurred, being observable only for very large systems. In the case of strong structural localization induced by the presence of rare regions, an assortative VG degree correlation, typical of off-critical series, is observed. We conclude that while macroscopic times series remain good proxies for the analysis of criticality for collective or maximum $k$-core activation, systems under spatial localization can postpone the signatures of or, in case of extreme localization, lead to false negatives for criticality of the time series.

We develop a Koopman reduced-order model (ROM) to analyze the instability mechanism and predict the hydrodynamic behavior for the flag flapping in the wake of a cylinder. The Koopman ROM is constructed using a kernel dynamic mode decomposition method and enhanced through a residual dynamical mode decomposition algorithm, which improves accuracy by identifying and eliminating spurious modes. Our analysis reveals a flow transition from the “2S” mode in the periodic phase to the “2P” mode in the quasiperiodic phase, with the main Koopman mode ${\mathrm{M}}_1$ providing insights into the instability mechanism. In the case of chaotic flapping at a Reynolds number of $\mathrm{Re}=1200$, the Koopman ROM demonstrates high accuracy in predicting the chaotic fluid-structure interaction flow when comparing the fractal dimension $d_c$ and the maximum Lyapunov exponent ${\lambda }_{max}$ of the true and reconstructed flow. Additionally, we observe similar flag flapping and vortex shedding characteristics in the near-structure region throughout the investigated Reynolds number range $\mathrm{Re}\in [500,1200]$, leading to similar vorticity patterns for ${\mathrm{M}}_1$. The flag flapping has a local minimum displacement at position $x_0\approx 3.0$ in the flag's displacement envelope. Notably, this position closely matches the critical position $x_c$ obtained from global linear instability analysis at low Reynolds numbers. This conclusion aligns with the performance of the Koopman ROM using sparse measurement probes attached to the flag. The position of the probes influences the accuracy of the ROM, where higher accuracy corresponds to a larger displacement of the eigenfunction.

The interaction between a droplet and superhydrophobic particles has a duration that significantly deviates from the inertia-capillary timescale. Both the rapid and delayed rebounds of the droplet are observed on the superhydrophobic particles with various particle sizes and impact velocities. Typically, the former occurs with little attachment of the particles to the rebounding droplet, while the latter emerges with the signature of a liquid marble formation. We propose a simplified model to predict the contact time of the droplet on the superhydrophobic particles by considering the additional surface deformation underneath the droplet and the possible formation of a liquid marble induced by the particles. This proposed model not only supplies the upper and lower bounds of the contact time that covers all the experimentally measured data, but also provides a way to estimate the effective viscosity in the liquid-particle mixture, which collapses the maximum spreading factor of all tested impact cases to one curve.

In this paper, we present the first direct experimental evidence supported by numerical modeling of a turbulent plasma column formed during a gas-puff $z$-pinch implosion generated by the cobra current. Utilizing an imaging refractometer, we showed a significant decrease in spatial autocorrelation of the laser field and the appearance of a laser speckle pattern shortly before stagnation. The intensity distribution of the speckles measured during different shot campaigns while employing long and short cobra pulses follows the speckle statistics satisfactorily. The imaging refractometer signal is proportional to the integral over the electron density gradients; hence, the measured phase randomization of the individual plane waves composing the laser field implies a random density distribution. To validate this, the beam propagation method code simulates the laser beam propagation through different artificial density distributions with various average fluctuation scales and generates synthetic imaging refractometer data. The results reproduce similar trends in the experimental data, such as the increasing vertical width for the decreasing average spatial scale of the fluctuations and the decreasing spatial correlation length of the laser field. Therefore, during the gas-puff $z$-pinch implosion process, it is likely that the plasma flow is almost always turbulent with the average spatial scale of the turbulent density fluctuations decreasing towards stagnation.

The long-term development of the transitional regime of drift-wave turbulence is studied in a magnetized plasma column by means of the conditional-average technique. In the transitional regime, small changes in the magnetic-field strength as control parameter lead to large changes in the correlation times, indicating the existence of a critical point of an underlying nonequilibrium continuous phase transition. This and the spatiotemporal dynamics shows similarities to puff splitting, slug-gap splitting, and puff jamming.

The rheological properties of nonpolar ferrofluids have been often studied under the action of an external magnetic or electric field. In this paper, we approach the problem conversely, and we aim to answer whether the ferrofluid shear flow affects the dielectric response. The ferrofluids are based on transformer oil and iron oxide nanoparticles stabilized with oleic acid. Basic physical characterization of the ferrofluids with three different nanoparticle concentrations is followed by experimental investigation of flow curves. Newtonian behavior of the ferrofluids is confirmed. The key experiment of this study consists of complex dielectric permittivity measurements in the frequency range from 20 Hz to 100 kHz at three different temperatures. In these measurements, the ferrofluids are sandwiched between two disk electrodes of a modular rheometer under the shear rates of 0, 10, 100, 500, and $1000{\mathrm{s}}^{-1}$. It is found that the low-frequency dielectric spectra of the ferrofluids exhibit a remarkable conductivity contribution leading to electrode polarization. Additional measurements of electrical conductivity and qualitative analysis of charge mobility in the ferrofluids are provided to understand the low-frequency dielectric relaxation. The results reveal that the slow dielectric relaxation is shear rate independent. The low-frequency dielectric spectra measured under the various shear rates exhibit constant behavior. The electric charge migrates across the shear flow velocity in the shear rate direction and the given rheological conditions do not affect its behavior. It is concluded that the electrical forces dominate the charge motion in the ferrofluids over the shear forces. The finding of the stable dielectric response of ferrofluids under the shear flow conditions supports the application of ferrofluids as dielectric media in electrical equipment with the presence of forced or natural convection.

A number of geometric and topological properties of samples of crack-template-based conductive films are examined to assess the degree to which Voronoi diagrams can successfully model structure and conductivity in such networks. Our analysis suggests that although Poisson-Voronoi diagrams are only partially successful in modeling structural features of real-world crack patterns formed in films undergoing desiccation, such diagrams can nevertheless be useful in situations where topological characteristics are more important than geometric ones. A phenomenological model is proposed that is more accurate at capturing features of the real-world crack patterns.

Persistent motion of microswimmers near boundaries is known to result in surface accumulation. A way to control surface accumulation is by reducing the contact surface area between swimmers and surface by modifying its topography, typically through the application of microscale structures. In this work, we introduce a three-dimensional (3D) phenomenological model of a microswimmer navigating a volume bounded by a top and bottom surface. We describe the swimmer-surface interaction with an effective near-surface alignment force, and study numerically the effect of surface textures, modeled by convex obstacles, on the surface accumulation of chiral and nonchiral microswimmers. We find that, depending on the angular velocity of the swimmer, and the alignment force, convex obstacles can either hinder or enhance surface accumulation. We discuss potential applications to sorting of microswimmers by their angular velocity.

We investigate the effect of heavy impurities on the mechanical properties and plasticity of a modeled amorphous solid by introducing a small fraction of these impurities into the material which resembles real experimental systems. The impurities being mobile, the total degrees of freedom and the potential energy landscape of the pure system are preserved in our model. The mechanical failure and the shear band formation in the amorphous solid in the presence of impurities are studied at the microscopic level by employing the finite shear deformation protocol at nonzero temperature. A significant enhancement in the yield stress is observed as a function of the heaviness of the impurity particles. Via the analysis of the nonaffine displacement field and the microscopic strain fluctuations and the nature of their spatial correlations we find that the shear band formation in the plastic regime is gradually suppressed with increasing impurity mass. Eventually, a crossover mass of the impurity particles is identified above which the plastic events become completely localized. This is marked by a transition from a power law to an exponential decay in the spatial correlations nonaffine displacement field. Likewise, a similar change is observed in the strain correlation function, transitioning from a slower $1/r$ decay to a more rapid $1/r^3$ decay. Finally, the effect shear rate on the plastic events in the presence of impurities is explored.

We consider two different fractional generalizations of the heterogeneous telegrapher's process with and without stochastic resetting. Both governing fractional heterogeneous telegrapher's equations can be obtained from the corresponding standard heterogeneous telegrapher's equations by using the subordination approach. The first-passage time problems are solved analytically for both models by finding the survival probabilities, the first-passage time densities, and the mean first-passage times. We showed that for both cases there are optimal resetting rates for which the mean first-passage times are minimal. The present work carries implications toward our understanding of anomalous diffusion and random search in heterogeneous media.

Estimating entropy production from real observation data can be difficult due to finite resolution in both space and time and finite measurement statistics. We characterize the statistical error introduced by finite sample size and compare the performance of three different entropy estimators under these limitations for two different paradigmatic systems, a four-state Markov network and an augmented Michaelis-Menten reaction scheme. We consider the thermodynamic uncertainty relation, a waiting-time-based estimator for resolved transitions and a waiting-time-based estimator for blurred transitions in imperfect observation scenarios. For perfect measurement statistics and finite temporal resolution, the estimator based on resolved transitions performs best in all considered scenarios. The thermodynamic uncertainty relation gives a better estimate than the estimator based on blurred transitions at low driving affinities, whereas the latter performs better at high driving affinities. Furthermore, we find that a higher temporal and spatial resolution leads to slower convergence of measurement statistics, implying that for short measurement times, a lower resolution may be beneficial. Additionally, we identify a self-averaging effect for the waiting-time-based entropy estimators that can reduce their variance for observations with finite statistics.

Heterogeneous nucleation plays a pivotal role in the ice nucleation process. Within the classical nucleation theory (CNT) framework, the heterogeneous nucleation rate is proportional to the substrate surface area, typically assuming infinite substrate surfaces. However, when the substrate size approaches the nanoscale, the nucleation rate deviates significantly from CNT predictions. This study presents a novel theoretical model that distinguishes the nanoscale substrate into central and edge regions, attributing different contributions to ice nucleation. We hypothesize that the edge width equals the critical size of the nucleus ($r_c$) and validate this hypothesis using molecular dynamics (MD) simulations with the coarse-grained water model (mW model) on circular and rectangular substrates of varying sizes. Our results demonstrate that the edge region impedes heterogeneous ice nucleation, with the MD calculated nucleation rates aligning well with our model. Furthermore, the statistical edge width matches the critical nucleus size $r_c$. By incorporating this refined model, our findings reconcile the nucleation rates with CNT predictions, offering new insights into heterogeneous ice nucleation at the nanoscale.

It is well established that the long-range component of the thermal van der Waals interaction between two semi-infinite dielectrics becomes short-range when an electrolyte is present between them, this is the well known phenomenon of screening. G. Du et al. [Phys. Rev. Lett. 133, 238002 (2024)]. showed that for a binary symmetric electrolyte, an electric field parallel to the dielectric boundaries disrupts screening and a long-range thermal repulsive interaction appears. At large applied fields this long-range repulsive interaction can be explained by the fact that the cations and anions have differing average drifts moving in opposite directions, leading to the correlation of charge density fluctuations between the two species to decouple. Here we extend these results to binary electrolytes which are asymmetric as well as electrolytes with more than two ionic species.

Neurons represent the fundamental units of the nervous system, and modeling their dynamics as slow-fast systems is becoming increasingly ubiquitous in the neurodynamics literature. We look into slow-fast denatured Morris-Lecar neurons, both single and coupled systems, aimed at capturing their bursting patterns. We employ a range of tools from nonlinear dynamics to analyze the single and coupled systems, for example, fixed point analysis and bifurcation analysis. We perform numerical simulations exhibiting a route consisting of hyperchaos, chaos, quasiperiodicity, mixed-mode oscillations, irregular bursting, and decay oscillations. Chaos is studied via numerical computations of Lyapunov exponents and also employing the 0-1 test. Furthermore, the complexity of the time series arising from the coupled system is quantified via sample entropy. Finally, the synchronization between the neurons in the coupled system is studied using the cross-correlation coefficient and whether it contributes to the complexity of our model is identified numerically. We observe in-phase and antiphase synchrony between the two neurons in the coupled system and notice that antiphase synchrony contributes towards more complexity within the system.

In recent times, bound soliton states have often been referred to as soliton molecules in the nonlinear optics literature. The striking analogies between photonic bound states and matter molecular structures in chemistry and physics have intensified studies on optical soliton molecules in both conservative and dissipative systems. In this paper, we demonstrate the existence of vector soliton molecules and their related isomer structures in a conservative optical fiber system by considering the integrable Manakov equation. We show their existence by applying the velocity resonance condition and appropriate choice of temporal separations to the degenerate $N=(\overline{N}+\overline{M})$-soliton solution. Then, we classify the obtained molecular states as either dissociated or synthesized molecular states based on the temporal locations of the constituent solitons. Furthermore, we analyze the collision properties of vector soliton molecules in the present conservative system. The collision scenarios reveal that the soliton molecules undergo intriguing energy-sharing collisions through energy redistribution among the modes. To characterize these collisions, we have carried out an appropriate asymptotic analysis and found that elastic collisions arise as a special case of energy-sharing collisions under specific choices of polarization constants. Finally, we numerically verify the robustness of vector soliton molecules. We believe that the results presented in this paper show potential for soliton molecule-based applications such as optical computation and multilevel encoding for communications.

We demonstrate that the model of a spatially nonuniform two-component Bose-Einstein condensates (BEC) featuring the helicoidal spin-orbit coupling (SOC), gives rise to dark-bright soliton complexes characterized by spatiotemporal periodic oscillations in each component. These solitons are formed by the superposition of dark and bright ones, and exhibit a beating state over time and a striped state across space, earning them the designation of beating stripe solitons. Our analysis demonstrates that helicoidal SOC significantly affects the formation and dynamical properties of these solitons, also serving as the primary driver for spin oscillations. Through the nonlinear superposition of the beating stripe solitons, a range of intricate scenarios of the interaction between multiple solitons emerges, including head-on collisions, bound states, and parallel states.

During epidemic outbreaks, information dissemination plays a pivotal role in shaping individual perceptions, which in turn influence contact behavior and resource acquisition, collectively determining infection risk. To capture this intricate interplay, we propose a comprehensive coevolutionary dynamics model that integrates information, awareness, activity, resources, and epidemic within a multiplex network framework. Through the development of a theoretical analysis coupled with extensive numerical verifications, we uncover the nonmonotonic effects of information dissemination on epidemic dynamics. Paradoxically, excessive information flow can intensify resource competition among individuals, leading to inefficient allocation and ultimately exacerbating the epidemic. Our findings highlight the importance of optimized resource allocation, showing that moderately prioritizing aware individuals with resources can effectively reduce infection rates, especially as information dissemination increases. Additionally, we explore the optimal balance between information dissemination and resource allocation, emphasizing its strong dependence on resource availability, while activity frequency experts a comparatively minor impact. This study advances the modeling of epidemic dynamics, providing valuable insights and practical strategies for effective epidemic management and control.