Based on extensive parallel-tempering Monte Carlo simulations, we investigate the relationship between cluster percolation and equilibrium ordering phenomena in the three-dimensional $\pm J$ random-bond Ising model for different fractions of antiferromagnetic bonds. We consider a range of cluster definitions, most of which are constructed in the space of overlaps between two independent replicas of the system. In the pure ferromagnet that is contained as a limiting case in the class of problems considered, the relevant percolation point coincides with the thermodynamic ordering transition. For the disordered ferromagnet encountered first on introducing antiferromagnetic bonds and the adjacent spin-glass phase of strong disorder, this connection is altered, and one finds a percolation transition above the thermodynamic ordering point that is accompanied by the appearance of two percolating clusters of equal density. Only at the lower (disordered) ferromagnetic or spin-glass transition points the densities of these two clusters start to diverge, thus providing a percolation signature of these thermodynamic transitions. We compare the scaling behavior at this secondary percolation transition with the thermodynamic behavior at the corresponding ferromagnetic and spin-glass phase transitions.

The causal relationships between the physical fields that intervene in the description of heat transport in rigid heat-conducting solids are analyzed in the light of the transfer of information. The analysis runs through three heat transport models, namely, the Fourier (F), the Maxwell-Cattaneo-Vernotte (MCV), and the Jeffreys-Guyer-Krumhansl (J-GK) models. It is argued that the MCV model can be obtained (to first order) by introducing a delay time into the F model, and, similarly, the GK model can be obtained from the MCV model. This implicit causality allows to identify two sets of causal physical fields. The causal relationship of each of the pairs is then characterized by the transfer of information measured with the so-called transfer entropy. Validation experiments are used to interpret the results, which leads to our main conclusion: information flows from spatial inhomogeneities to heat flow and temporal temperature variation, thus clarifying causal relationships in the system. Such causality vanishes for long timescales.

The nature of the ordered phases and the character of the phase transitions of the Ising chain model with intrachain interaction $j$, coupled by interchain direct $j_2$, indirect $j_1$, and four-spin $k$ interactions, are studied using a hybrid method—a combination of the transfer matrix (TM) and molecular field approximation (MFA). Indirect coupling is achieved through redundant spins that can be rigorously traced out in the partition function, which leads to a temperature-dependent resultant (effective) interchain interaction. In this approach, an exactly solvable one-dimensional model is placed in the molecular field originating from adjacent chains. The temperature dependences of the magnetization, specific heat, and correlation functions in the ordered phases are found. The phase diagram in the plane (transition temperature $t_c, k$) with three ordered phases— $FM$ ferromagnetic, $AF$ antiferromagnetic, $M$ with alternating ferro- and antiferromagnetic chains—and a re-entrant paramagnetic phase has been determined. It has been shown that the four-spin interaction $k$ can change the phase transition kind from continuous to discontinuous and lead to a gigantic specific heat at a temperature above $t_c$.

This paper investigates a coupled two-qubits heat engine fueled by generalized measurements of the spin components and using a single heat reservoir as sink. Our model extends the proposal of Yi, Talkner, and Kim [Phys. Rev. E 96, 022108 (2017)], where the role of a hot reservoir in a four-stroke cycle was replaced by a quantum measurement apparatus, the other steps being two quantum adiabatic strokes and thermalization with a cold reservoir. We propose a five-stroke cycle, where an ergotropy extracting stroke is introduced following the measurement stroke, and study the effect of measurements of different spin components on the performance of the machine. For measurements along z-z directions, we find two possible occupation distributions that yield an active state and the ergotropic stroke improves the performance of the engine over the four-stroke cycle. Further, the three-stroke engine (without the adiabatic strokes) yields the same performance as the five-stroke engine. For arbitrary working medium and nonselective measurements, we prove that the total work output of a five-stroke engine is equal to the sum of the work outputs of the corresponding four-stroke and three-stroke engines. For measurement directions other than z-z, there may be many possible orderings of the postmeasurement probabilities that yield an active state. However, as we illustrate, for specific cases (e.g., x-x), a definite ordering may be obtained with the projective measurements. Thus we find that the five-stroke engine exploiting ergotropy outperforms both its four-stroke as well as three-stroke counterparts.

Organisms have evolved various mechanisms to cope with stochastic environmental fluctuations, and the survival strategies of being generalists and specialists are particularly crucial in this context. Generalists prioritize long-term population survival, providing equal benefits in both favorable and unfavorable environments. In contrast, specialists focus on short-term rapid growth, with benefits that differ significantly in different environmental conditions. In this paper we investigate the invading process of mutants in a finite wild-type population under fluctuating environmental conditions, aiming to elucidate the potential survival strategies that mutants can adopt to maximize their fixation probability. To this end, we construct and analyze a dynamic model in which the population dynamics is governed by a birth–death process, and the fluctuating environment is modeled by a Markov chain. We explore scenarios in which the mutant population adopts alternating strategies between specialist and generalist according to either responsive or stochastic switching schemes. Interestingly, we find that mutant populations adopting stochastic switching strategies achieve higher fixation probabilities than those using just pure strategies. This counterintuitive result is reminiscent of Parrondo's paradox in complex systems, where an unexpected victory arises from two individually losing strategies, provided that they are utilized in a particular or random manner. Our work reveals that in stochastic environments, survival in the evolutionary process depends not on the superiority of a specific strategy but on the population's adaptability.

We propose a threshold model of language competition which includes an intermediate bilingual state. The model is based on the Minett-Wang model but through the introduction of thresholds in the language shift rates, it incorporates the effects of memory and learning. The model is piecewise linear, allowing an exact analytical treatment. We study the symmetric case where two competing languages are equivalent in terms of status and social pressure and provide a complete list of the various dynamical regimes. We also study several limiting regimes corresponding to asymmetric systems and characterize the full spectrum of possible asymptotic behaviors. Unlike the Minett-Wang model, which always predicts the extinction of one of the languages, the proposed model exhibits a wide range of possible equilibrium scenarios, including equilibrium states of coexistence. Most commonly, in such coexistence regimes the minority language speakers are either predominantly monolingual or predominantly bilingual.

Framing the glass formation within standard statistical mechanics is an outstanding problem of condensed matter theory. To add insight, we investigate the structural properties of the Lennard-Jones fluid in the very-low temperature regime by using a replicated version of the refined HMSA theory of the liquid state combined with an appropriate split of the pair potential [Bomont and Bretonnet, J. Chem. Phys. 114, 4141 (2001)]. Our scheme allows one to reach an unprecedented low-temperature domain within both the supercooled liquid and the ideal-glass phase. Therein, a density-dependent temperature is identified, whereupon the radial distribution function experiences clear-cut structural changes, insofar as an additional peak develops in between the main and the second peaks. Such a structural feature points to a local structure of the Lennard-Jones ideal glass with an fcc-like short-range order, in the absence of any long-range order.

Understanding the contact between rough surfaces undergoing plastic deformation is crucial in many applications. We study the effect of plastic deformation on the surface separation between two solids with random roughness. Assuming a constant penetration hardness, we propose an iterative smoothing procedure (akin to elastoplastic “shakedown”) within Persson's multiscale contact mechanics theory to obtain the average surface separation by applying the elastic formulation to an effective power spectrum that accounts for plastic smoothing. Deterministic numerical simulations based on the boundary element method are used to validate the procedure and show good agreement with the theoretical predictions. The treatment also provides a route to incorporate plastic stiffening of the roughness as the stress state becomes increasingly hydrostatic at large plastic deformation.

Active Stokesian suspensions are conventionally understood to generate dipolar stresses that destabilize aligned states in the bulk and drive systemwide spatiotemporally chaotic flows. Here, we report dynamics in suspensions of torque-driven spinning chiral particles that exhibit a distinct and previously unrecognized route to collective dynamics. Using a mean-field kinetic theory, stability analysis, and nonlinear simulations, we demonstrate how flows driven by torque monopoles and self-propulsion resulting from microscopic chirality drive chaotic flows in three dimensions. Unlike the well-known alignment instability of dipolar active matter, the present dynamics is intrinsically tied to self-propulsion and relies on the emergent coupling between nematic and polar order. Our results establish a novel route to pattern formation, suggest strategies for designing torque-driven active suspensions, and provide a mechanistic framework to probe the rheology of chiral fluids.

We study two inertial Brownian particles with nonlinear coupling in a symmetric periodic potential and subjected to an unbiased harmonic driving in combination with a constant external force. The study focuses on the key role of the nonlinear interaction in inducing the absolute negative mobility. It is revealed that, due to the phase locking effect, with proper strength of nonlinearity, the system may be pushed much more easily into a stable regular trajectory, in which the phase of the relative motion and that of the temporally periodic driving are bounded to a desired phase difference. The overall mobility can be notably negative. The evident connection between the phase locking and the negative mobility is then observed. Furthermore, the robustness under perturbation of external noise can be partly improved in some cases. The way of tuning the collective mobility of a microscopic system via adjusting its internal interactions is thus broadened.

Learning to detect, identify, or select stimuli is an essential requirement of many behavioral tasks. In real-life situations, relevant and nonrelevant stimuli are often embedded in a continuous sensory stream, presumably represented by different segments of neural activity. Here we introduce a spiking network model that can discover action-relevant stimuli in an unsegmented sensory stream of spike trains. The model uses a biologically plausible plasticity rule and learns from the reinforcement of correct decisions taken at the right time. Learning is fully online and is faster for larger population size; it allows for a wide spectrum of neural-encoding strategies and can segment cortical spike patterns recorded from behaving animals. Based on these results, the proposed model provides a biologically plausible framework for reinforcement learning in the absence of prior information on the identity, relevance, and timing of input stimuli embedded in a continuous spatiotemporal stream.

Guiding active motion is important for targeted delivery, sensing, and search tasks. Many active systems exhibit circular swimming, ubiquitous in chemical, physical, and biological systems, that biases motion and reduces transport efficiency. We show that stochastic position-orientation resetting can overcome these limitations in two-dimensional chiral active Brownian particles by interrupting circular motion, resulting in tunable dynamics. When resets are infrequent compared to chiral rotation, the steady-state mean-squared displacement varies nonmonotonically with rotational diffusion. Steady-state excess kurtosis and orientation autocorrelation yields a spatiotemporal state diagram comprising three states: an activity-dominated chiral state and two resetting-dominated states with and without chiral rotation; in contrast, the achiral (or nonchiral) counterpart supports only the resetting-dominated state without chiral rotation. Chirality thus enriches the dynamical landscape, enabling tunable transitions between transport modes absent in achiral systems. A simple reset protocol can therefore transform chiral active dynamics and offer a practical strategy for optimizing search and transport in circle swimmers.

We study the out-of-equilibrium spinodal-like dynamics of three-dimensional $q$-state Potts systems driven across their thermal first-order transition in the thermodynamic limit, by a relaxational (heat-bath) dynamics. During the evolution, the inverse temperature $\beta$ increases linearly with time, as $\delta \beta \left(t\right)\equiv \beta \left(t\right)-{\beta }_{\mathrm{fo}}\sim t/t_s$, where ${\beta }_{\mathrm{fo}}$ is the inverse temperature at the transition point, $t$ is the time, and $t_s$ is a timescale. The dynamics starts at $t_i<0$ from an ensemble of disordered configurations equilibrated at an inverse temperature $\beta \left(t_i\right)<{\beta }_{\mathrm{fo}}$ and ends at positive values of $t$, corresponding to $\beta \left(t\right)>{\beta }_{\mathrm{fo}}$ in the ordered phase (this is analogous to a standard Kibble-Zurek protocol). The time-dependent energy density shows an out-of-equilibrium scaling behavior in the large-$t_s$ limit, in terms of the scaling variable $\sigma \equiv t{(lnt)}^{\kappa }/t_s$. The exponent $\kappa$ turns out to be consistent with $\kappa =3/2$ (with good accuracy), which is the value obtained by assuming that the initial nucleation of ordered regions is the relevant mechanism providing the largest timescale. This scaling behavior implies a spinodal-like phenomenon close to the transition point: the passage from the disordered to the ordered phase, composed of large ordered regions of different color, occurs at $\delta \beta \left(t\right)=\delta {\beta }_{*}>0$, which decreases as $\delta {\beta }_{*}\sim {(ln{t}_s)}^{-\kappa }$ in the large-$t_s$ limit.

We report on the experimental study of the spectral properties of quantum systems consisting of two quantum billiards (QBs), one with chaotic, the other one with integrable classical dynamics, that are coupled to each other via an opening in a common wall. They are compared to those of a special case of the Rosenzweig-Porter model with random matrices composed of two diagonal blocks modeling the spectral properties of the QBs, which are coupled with a tunable parameter. We demonstrate that this model is suitable for the description of the experimental data and thus may be employed to determine the strength of the coupling. It results from the increasing overlap of eigenmodes in the QBs penetrating through the opening into the other one, leading to a mixing of their eigenstates, and the breaking of the symmetry present in the QB with integrable dynamics. This implicates deviations of the spectral properties from those of typical quantum systems with integrable and chaotic dynamics, respectively, and approaches those of a fully chaotic system for sufficiently large coupling strength. In contrast, in previous studies the transition from integrable to chaotic dynamics was induced by introducing a random potential of increasing strength into such a QB and applicability of a variant of the Rosenzweig-Porter model was tested.

We report a unique regime for generating zeptosecond pulses (ZPs) to break the attosecond timescale barrier through cascaded coherent synchrotron emission driven by ultraintense x-ray laser-pulse-excited wakefields in foil. When an x-ray laser pulse interacts with the near-critical-density but exactly overdense plasma, it excites huge wakefields with huge accelerating gradients, while the displaced electrons are shaped into several electron nanosheets. The primary relativistic electron sheet is accelerated by the wakefields and emits coherent radiation with a long electromagnetic field tail. The subsquent electron sheet is longitudinally accelerated as well as transversely perturbed by the radiation tail and emits another pulse. This cascaded process is repeated several times and finally results in ZP generation. This cascaded coherent wakefield synchrotron emission regime establishes a viable pathway for accessing light-matter interactions in the zeptosecond regime, probing vacuum quantum electrodynamics and subnucleonic scale dynamics.

Using event-driven molecular dynamics simulations, we investigate the crystallization of hard spheres confined within ellipsoidal cavities and find that the curvature anisotropy of the confining boundary governs both nucleation and growth dynamics. Crystallization preferentially initiates at low-curvature regions and propagates inward. In prolate ellipsoids, multiple nuclei emerge along the equatorial plane and grow into several misoriented crystalline domains, whereas in oblate ellipsoids, crystallization starts at the poles and results in a nearly monocrystalline structure. The free energy of nucleation scales linearly with cluster size, reflecting a surface-dominated growth mechanism, and the free-energy penalty per particle follows a universal power-law dependence on the Gaussian curvature. The distribution of lattice defects on the curved surface is consistent with the anisotropic crystallization inside the cavity, revealing that curvature-induced defect localization controls the symmetry breaking of confined crystallization.

We investigate the nonequilibrium dynamics of active matter using a two-dimensional active Brownian particles model. In these systems, self-propelled particles undergo motility-induced phase separation (MIPS), spontaneously segregating into dense and dilute phases. We find that in the high-density phase, local particle mobility exhibits transient caging, with diffusivity remaining unchanged despite variations in the global system density. As global density increases further, the system undergoes a transition to a solidlike state through an intermediate regime with pronounced dynamical arrest. Our findings identify a distinct high-density regime characterized by transient caging and dynamical slowing down in a monodisperse active system, shedding light on the connection between MIPS and nonequilibrium arrest.

The screeching of peeling tape is a familiar albeit annoying sound. However, despite decades of study, its source has remained elusive. Herein we demonstrate that this sound is produced by a discrete train of weak shocks emanating from the fine fractures which travel supersonically with respect to the surrounding air, in the transverse direction within the detaching adhesive. Each sound pulse is generated when a fracture tip reaches the edge of the tape. We verify this using two microphones synchronized with clips from two simultaneous high-speed video cameras, one observing the fracture motions in the adhesive through the transparent substrate, while the other captures schlieren imaging of the shock fronts in the air.

Feedback cooling enables a system to achieve low temperatures through measurement-based control. Determining the thermodynamic cost required to achieve the ideal cooling efficiency within a finite time remains an important problem. In this work, we establish a thermodynamic uncertainty relation (TUR) for feedback cooling in classical underdamped Langevin systems, thereby deriving a trade-off between the cooling efficiency and the entropy reduction rate. The obtained TUR implies that simultaneous achievement of the ideal cooling efficiency and finite entropy reduction rate is asymptotically possible by letting the fluctuation of the reversible local mean velocity diverge. This is shown to be feasible by using a feedback control based on the Kalman filter. Our results clarify the thermodynamic costs of achieving the fundamental cooling limit of feedback control from the perspective of the TUR.