Walkers (i.e., bouncing droplets coupled to a local Faraday wave) are sent on an orthogonal standing wave. The trajectories of successive walkers form a straight-propagating beam toward the wave that splits into three distinct paths during the interaction with the wave. At the end of the interaction, walkers' trajectories split again and are deviated into three main directions. The walkers' trajectories show sensitivity to parameters and initial conditions but remain predictable in some regions of the parameter space. The dependence of the statistical distribution of deviations on the wave amplitude markedly differs from the prediction of quantum mechanics for a particle interacting with a standing electromagnetic wave.

Plasma discharge devices have recently emerged as compact and versatile tools for particle beam manipulation. Building upon the active plasma lens (APL) and its curved extension, the active plasma bending, this work introduces the concept of the plasma discharge undulator (PDU). In a PDU, a high-current discharge within a capillary generates an azimuthal magnetic field providing strong linear focusing $\left[O\right(\text{kT/m}\left)\right]$, while a controlled and periodical spatial modulation of the discharge axis acts as a geometric driving term. The resulting beam dynamics can be modeled as a forced harmonic oscillator, yielding a well-defined oscillation at wavelength ${\lambda }_{\mathrm{PDU}}$, distinct from the natural betatron wavelength ${\lambda }_{\beta }$ related to APL focusing. Proper injection conditions result in the suppression of collective betatron oscillations, significantly reducing the intrinsic undulator strength spread typical of conventional plasma undulators while allowing for matched beam transport thanks to strong APL focusing. Analytical models for particle trajectories and radiation emission are developed, and the one-dimensional requirements for free-electron laser (FEL) emission are evaluated, providing scaling relations and feasibility criteria for FEL operation in the proposed scheme. Theoretical estimates are validated through multiparticle simulations of beam dynamics and radiation emission, confirming that the PDU can operate in the short-period regime (${\lambda }_{\mathrm{PDU}}$ of millimeters to centimeters) with tunable undulator strength $K_{\mathrm{PDU}}$, supporting narrow-band radiation emission. Numerical studies further demonstrate that the PDU is capable of sustaining seeded longitudinal microbunching analogous to that occurring in conventional magnetic undulators. The PDU thus provides a pathway toward miniaturized, tunable, fully plasma based light sources with enhanced control over focusing and spectral properties.

We report the combined results of both experiments and molecular dynamics simulations, carried out to investigate superheating phenomena in vertically vibrated granular matter. Specifically, we consider a system of cubic particles, densely packed in a squared-lattice array and subjected to different acceleration shaking strengths $\mathrm{\Gamma }$. Below a critical value ${\mathrm{\Gamma }}_c\sim 3.2$, the excited crystalline array remains stable indefinitely, whereas for a fixed $\mathrm{\Gamma }>{\mathrm{\Gamma }}_c$, the system stays first in a metastable solid phase and then it transitions progressively into a liquid phase, during a $\mathrm{\Gamma }$-dependent timescale ${\tau }_m$. The value of ${\mathrm{\Gamma }}_c$ required to observe metastable superheated states for cubic particles is considerably larger than the value previously reported for spherical beads (${\mathrm{\Gamma }}_c^{\text{sph}}\sim 1.4)$, which is attributed to a more efficient energy dissipation process due to interparticle friction, that also lengthens substantially the lifetime of the superheated crystal. Notably, however, the exponents of the power scaling laws for ${\tau }_m\left(\mathrm{\Gamma }\right)$ are very similar for both geometries, suggesting universality in this transition. Our findings also show that the transition from the superheated-solid to the liquid state of the vibrated system is well captured by a Kolmogorov-Johnson-Mehl-Avrami equation, routinely employed to describe phase transformations in thermal systems.

It is common to model ion-irradiated amorphous thin films as if they were highly viscous fluids. In such models, one is frequently concerned with the ion-enhanced fluidity, a measure of the ability of the free interface to relax surface energy. Motivated by usual fluid dynamics problems, the ion-enhanced fluidity is near universally treated as a constant throughout the amorphous layer. However, for an irradiated thin film, the fluidity is ultimately caused by radiation-induced defect kinetics within the film, leading to regions with greater or lesser fluidity, and sensitive dependence on ion energy, species, flux, irradiation angle, temperature, and other experimental parameters. Here we develop and analyze a model of radiation-induced defect kinetics coupled to the continuum equations of a viscous thin film where sputtering-induced surface destabilization is neglected. Using realistic parameter values, we show that defect kinetics can meaningfully alter theoretical predictions of surface relaxation and ion-enhanced fluidity. Implications for aligning theoretical and experimental work, especially for surface nanopatterning of silicon induced by low-energy argon irradiation, are discussed.

In this letter, by an approach that employs Weyl symbols for operators, a semiclassical theory is developed for the off-diagonal function in the eigenstate thermalization hypothesis, which is for off-diagonal elements $\langle E_i\left|O\right|E_j\rangle$ of an observable $O$ on the energy basis. It is shown analytically that the matrix of $O$ has a banded structure, possessing a bandwidth $w_b$ that scales linearly with $\hslash$, a phase-space gradient of the classical Hamiltonian $\langle \left|\mathbf{\nabla }{H}_{\mathrm{cl}}\right|\rangle$ and an $O$-dependent property. This predicts that the thermalization timescale of a quantum system may be inversely proportional to the phase-space gradient of the Hamiltonian, aligning with intuitions in classical thermalization. This approach also elucidates the origin of a ${\rho }_{\mathrm{dos}}^{-1/2}$ scaling of the off-diagonal function. The analytical predictions are checked numerically in the Lipkin-Meshkov-Glick model.

The fast ion (FI) on turbulent transport is one of the key topics of magnetic confinement fusion. This work focus on the impact of FI pressure gradients on turbulence in a high-β plasma scenario using gyrokinetic simulations. Linear analyses reveal that FIs strongly stabilize ion temperature gradient (ITG) modes via the thermal-ion dilution, while their influence on trapped electron modes (TEMs) is minimal. At elevated FI pressure gradients, a transition to a FI-driven BAE (FI-BAE) regime occurs, as evidenced by mode structure and frequency alignment within the Alfvénic gap. Electron β scans further demonstrate the emergence of kinetic ballooning modes at higher β, whereas an ITG-TEM hybrid turbulence dominates near experimental β values. Nonlinear simulations show that moderate FI pressure suppresses transport via zonal flow (ZF) shear, whereas strong FI drive weakens ZFs and enhances transport by destabilizing FI-BAEs. These results highlight the dual role of FIs in regulating turbulence and offer insight into multiscale transport physics relevant for high-performance plasmas.

Using particle-based simulations, we study the rheology of dense, frictional, non-Brownian suspensions containing active particles. We find that the viscosity and the shear jamming point of the suspension can be tuned by varying the activity strength of the active particles. Microscopically, variations in the number of frictional contacts and the formation of a more isotropic force-chain network due to the presence of active particles underlie the viscosity changes. We introduce an effective temperature, defined through the control parameters of the active particles, that uniquely governs the viscosity of the suspensions. We also find that while activity drives the system away from jamming by hindering force-chain formation, unjamming an already jammed state by breaking existing force chains requires higher activity strength.

Molecular communication is a model of information transmission where the signal is transmitted by information-carrying molecules through their physical transport from a transmitter to a receiver through a communication channel. Prior efforts have identified suitable “information molecules” whose efficacy for signal transmission has been studied extensively in diffusive channels (DC). Although easy to implement, DCs are inefficient for distances longer than tens of nanometers. In contrast, molecular motor-driven nonequilibrium or active transport can drastically increase the range of communication and may permit efficient communication up to tens of micrometers. In this paper, we investigate how active transport influences the efficacy of molecular communication, quantified by the mutual information between transmitted and received signals. We consider two specific scenarios: (a) active transport through relays and (b) active transport through a mixture of active and diffusing particles. In each case, we discuss the efficacy of the communication channel and discuss their potential pitfalls.

We present an extension of the functional renormalization group (FRG) framework developed to compute critical probability distributions of the order parameter to momentum‐dependent observables. Focusing on the constraint effective action at fixed magnetization for the Ising universality class, we derive its exact flow equations and solve them at the second order of the derivative expansion (DE2). We solve these flow equations numerically for two‐ and three‐dimensional systems, extract universal rate functions and momentum‐dependent correlation functions, and benchmark them against Monte Carlo simulations. In three dimensions, we recover the rate function and accurately reproduce the first few Fourier modes of the constrained correlation function and demonstrate the convergence of the method. In two dimensions, the lowest-order approximations such as local potential approximation fail, and it is required to consider at least the DE2 to describe the critical point. Our results are in qualitative agreement with the numerics. We confirm the robustness of the FRG approach for calculating both zero‐ and finite‐momentum critical observables at fixed magnetization.

In this paper, we develop a variational foundation for stochastic thermodynamics of finite-dimensional, continuous-time systems. Requiring the second law (non-negative average total entropy production) systematically yields a consistent thermodynamic structure from which novel generalized fluctuation-dissipation relations emerge naturally, ensuring local detailed balance. This principle extends key results of stochastic thermodynamics including an individual trajectory level description of both configurational and thermal variables and fluctuation theorems in an extended thermodynamic phase space. It applies to both closed and open systems, while accommodating state-dependent parameters, nonlinear couplings between configurational and thermal degrees of freedom, and cross-correlated noise consistent with Onsager symmetry. This is achieved by establishing a unified geometric framework in which stochastic thermodynamics emerges from a generalized Lagrange-d'Alembert principle, building on the variational structure introduced by Gay-Balmaz and Yoshimura [Philos Trans. R. Soc. A 381, 2256 (2023)]. Irreversible and stochastic forces are incorporated through nonlinear nonholonomic constraints, with entropy treated as an independent dynamical variable. This work provides an approach for thermodynamically consistent modeling of stochastic systems and paves the way to applications in continuum systems such as active and complex fluids.

This study examines the domain-growth dynamics of $q$-state active Potts models ($q=3–8$) under the cyclically symmetric conditions using Monte Carlo simulations on square and hexagonal lattices. By imposing active cyclic flipping of states, finite-length waves emerge in the long-term limit. This study focuses on coarsening dynamics from an initially random mixture of states to these moving-domain states. The correlation length and mean cluster size grow, following the Lifshitz-Allen-Cahn (LAC) law ($\propto t^{1/2}$) in the intermediate time range, and in the late range, saturation is observed at the characteristic wavelengths. It is found that the growth rate is raised prior to saturation, leading to a transient increase in the coarsening exponent. The coarsening dynamics to disordered waves exhibit greater transient increases than those to spiral waves. Moreover, the transient increase is greater at higher $q$. In factorized symmetry modes at $q=6$, domains composed of two or three states similarly follow the LAC law. Finally, this study confirms that the choice of lattice type (square or hexagonal) and update scheme (Metropolis or Glauber) does not alter the dynamic behavior.

We investigate the efficiency of different quantum Monte Carlo simulations of a pair of antiferromagnetically coupled qubits in an Ohmic dissipative environment. Using a Trotter-Suzuki decomposition and integrating out the degrees of freedom of the thermal bath, the model maps onto a frustrated long-range double-chain Ising lattice. We prove that: (i) due to frustration, the conventional Swendsen-Wang approach to cluster dynamics turns out to suffer from a severe inefficiency, stemming from the mismatch between spin correlations and cluster connectivity; (ii) the Kandel-Domany approach is extremely effective in the study of dissipative quantum qubits. We partition the double-chain into different types of plaquettes and minimize the weight of graphs containing antiferromagnetic bonds by using both analytic and numerical approaches. Monte Carlo simulation results, based on the analysis of the autocorrelation time, show that “long-range” plaquette decompositions are more efficient than the “local” ones, especially for high levels of dissipation.

Phase transitions and thermodynamic properties of an Ising antiferromagnetic bilayer honeycomb lattice with competing interlayer interactions were investigated. By applying a cluster mean-field method, we study the role of exchange interactions on the interplay between thermal fluctuations and quantum effects introduced by a transverse magnetic field. The presence of competing interactions can lead to the onset of first-order phase transitions, but our findings reveal that the nature of these phase transitions can be changed by the transverse magnetic field, introducing continuous phase transitions at low temperatures. Our results also support that this change in the nature of phase transitions, called quantum annealed criticality, is associated with a large accumulation of entropy and an enhanced magnetocaloric effect at low temperatures. Therefore, magnetically anisotropic bilayer honeycomb systems provide a promising platform for the implementation of cooling and heating technologies based on enhanced magnetocaloric effect near quantum criticality.

We explore the synchronization dynamics of Kuramoto oscillators in three 2-simplicial ring networks—node-coupled, edge-coupled, and ring-star—covering both identical and nonidentical systems. Notably, the 2-simplicial ring networks support much richer antiphase fully synchronized states than those in traditional simplicial complex models, with cluster sizes following a universal, finite-size-effect-free Gaussian distribution. Regarding in-phase fully synchronized states, we verify via the cellular dynamics method that they are linearly stable yet practically unreachable from random initial conditions due to their extremely small attraction basins. Under frequency heterogeneity, partial synchronization emerges, where oscillator frequencies cluster into two distinct groups. Among these networks, the ring-star 2-simplicial ring network exhibits the narrowest range of coupling strengths supporting partial synchronization states, while displaying the most significant disparity in cluster sizes. This research highlights the pivotal role of simplicial coupling and ring topology in regulating synchronization, offering new insights into higher-order complex networks.

We investigate elastic, inelastic, and coalescent collisions between two-dimensional flat-top solitons supported by the cubic-quintic nonlinear Schrödinger equation. Numerical simulations reveal distinct collision regimes ranging from nearly elastic scattering to strongly inelastic interactions leading to long-lived merged states. We demonstrate that the transition between these regimes is primarily controlled by the relative phase of the solitons at the collision point, with out-of-phase collisions suppressing overlap and in-phase collisions promoting strong interaction. Kinetic-energy diagnostics are introduced to quantitatively characterize collision outcomes and to identify phase- and separation-dependent windows of elasticity. To interpret the observed dynamics, we extract effective phase-dependent interaction potentials from collision trajectories, providing a mechanical picture of attraction and repulsion between flat-top solitons. The stability of merged states formed after strongly inelastic collisions is explained by their lower energetic cost, arising from interfacial energetics, where a balance between internal pressure and edge tension plays a central role. A variational analysis based on direct energy minimization supports this picture by revealing robust energetic minima associated with stationary two-dimensional flat-top solitons.

This work presents a numerical investigation of interacting chiral oscillators (COs), characterized by an intrinsic rotational handedness. The coupling of positional and orientational degrees of freedom drives a mutual influence between synchronization and spatial dynamics. The control parameter, Δ (anisotropy or detuning), represents the frequency difference between two COs (for the two-body case) or between two families of COs (for the many-body case) with opposite handedness. For two COs with opposite handedness, interaction forces generate a helical excitable dipole (HED), where excitability is a spatiotemporal act characterized by a helical trajectory. For many COs moving in two dimensions, the model displays a locking-to-unlocking transition of the Kuramoto kind driven by Δ, leading the system from ordered states to irregular spatiotemporal dynamics. Within the locking region, many “superexcitable” states emerge, sustained by a global saddle-node bifurcation, detected by the collective period behavior versus Δ. These coherent, topological states are characterized by dissipationless phase-momentum locking, which I quantified using appropriate global metrics, including the Kuramoto order parameter and parameter S, capable of detecting the phase-momentum locking. These states exhibit a wide variety of topologically protected vortex complexes, whose complexity increases with system size. The model provides a unified framework for diverse biophysical applications—from molecular ratchets to cardiac looping—identifying the symmetry breaking of motile excitable units as a fundamental process for large-scale, robust collective transport.

Associative memory models such as the Hopfield network and its dense generalizations with higher-order interactions exhibit a “blackout catastrophe”—a discontinuous transition where stable memory states abruptly vanish when the number of stored patterns exceeds a critical capacity. This transition is often interpreted as rendering networks unusable beyond capacity limits. We argue that this interpretation is largely an artifact of the equilibrium perspective. We derive dynamical mean-field equations for graded-activity dense associative memory models, with the Hopfield model as a special case, using a bipartite cavity approach. We solve the resulting self-consistent equations using an iterative numerical scheme. We show that patterns can be transiently retrieved with high accuracy above capacity despite the absence of stable attractors. This occurs because slow regions persist in the above-capacity energy landscape near stored patterns as lingering traces of the stable basins that existed below capacity. The same transient-retrieval effect occurs in below-capacity networks initialized outside basins of attraction. “Transient-recovery curves” provide a concise visual summary of these effects, revealing graceful, noncatastrophic changes in retrieval behavior above capacity and allowing us to compare the behavior across interaction orders. This dynamical perspective reveals energy landscape structure obscured by equilibrium analysis, including slow regions near stored patterns that persist above capacity, and suggests biological neural circuits may exploit transient dynamics for memory retrieval. Furthermore, our approach suggests ways of understanding computational properties of neural circuits without reference to fixed points and yields new theoretical results on generalizations of the Hopfield model.

Biological systems rely on asynchronous and temporally overlapping dynamics, allowing for the concurrent activation of multiple processes. This principle is particularly evident in brain function, where cognitive tasks engage distributed, interacting regions rather than sequentially isolated ones. To investigate the mechanisms enabling such coordination, we study a modular spiking neural network composed of leaky integrate-and-fire neurons and governed by spike-timing-dependent plasticity. Our model stores modular spatiotemporal patterns both at the mesoscopic level (sequences of modules) and at the microscopic level (precise spike timings) and includes a parameter, $\eta$, which regulates the degree of temporal overlap between modules' activations. By tuning $\eta$, the network transitions from sequential to overlapping regimes, ranging from synfire chainlike dynamics to fully co-activated modules. We investigate how the temporal structure influences the network's capacity to encode and selectively retrieve multiple dynamical patterns while considering biological constraints such as the cost of long-range connectivity. Our results offer insight into how spatiotemporal coding and network organization support robust, large-scale memory storage and replay.

Recent advances in microscopy techniques has uncovered unique aspects of flagella-driven motility in bacteria. A remarkable example is the discovery of flagellar wrapping, a phenomenon whereby a bacterium wraps its flagellum (or flagellar bundle) around its cell body and propels itself like a corkscrew, enabling locomotion in highly viscous or confined environments. For certain bacterial species, this flagellar-wrapping mode is crucial for establishing selective symbiotic relationships with their hosts. The transformation of a flagellum from an extended to a folded (wrapped) state is triggered by a buckling instability driven by the motor-generated torque that unwinds the helical filament. This study investigated this biologically inspired, novel buckling mechanism through a combination of macroscale physical experiments, numerical simulations, and scaling theory to reveal its underlying physical principles. Excellent quantitative agreement between experiments and numerical results showed that long-range hydrodynamic interactions are essential for accurate quantitative descriptions of the geometrically nonlinear deformation of the helical filament during wrapping. By systematically analyzing extensive experimental and numerical data, we constructed a stability diagram that rationalized the stability boundary through an elastohydrodynamic scaling analysis. Leveraging the scaling nature of this study, we compared our physical results with available biological data and propose that bacteria exploit motor-induced buckling instability to initiate their flagellar wrapping. Our findings indicate that this mechanically driven process is essential to bacterial-wrapping motility and, consequently, plays a critical role in symbiosis and infection.

Micronanorobotic swimmers have promising potential for future biomedical tasks such as targeted drug delivery and minimally invasive diagnosis. An efficient method for controlled actuation of such nanoswimmers is applying a rotating external magnetic field, resulting in helical corkscrewlike locomotion. In previous joint work, we presented fabrication and actuation of a simple magnetic nanoswimmer composed of two nanorods connected by a short elastic hinge. Experiments under different actuation frequencies result in different motion regimes: at low frequencies, in-plane tumbling; at higher frequencies, moving forward in a spatial helical path in synchrony with the rotating magnetic field; in further frequency increase, asynchronous swimming is obtained. In this work, we present mathematical analysis of this nanoswimmer motion. We consider a simple two-link model and explicitly formulate and analyze its nonlinear dynamic equations, and reduce them to a simpler time-invariant system. We obtain explicit analytic solutions of synchronous motion under simplifying assumptions, for both solutions of in-plane tumbling and spatial helical swimming. We conduct stability analysis of the solutions, presenting stability transitions and bifurcations for the different solution branches. Furthermore, we present analysis of the influence of additional effects, as well as parametric optimization of the swimmer's speed. The results of our theoretical study are essential for understanding the nonlinear dynamics of experimental magnetic nanoswimmers for biomedical applications, and for conducting practical optimization of their performance.