This work proposes a model to simulate transient flow of a gas mixture at arbitrary rarefaction parameters and molar fractions through a long capillary. The transient model is based on the linear relationship between the thermodynamic fluxes (mass flow rate, diffusion flux, etc.) and the thermodynamic forces (gradients of the pressure, concentration, etc.) of the gas flow in the long capillary. The coefficients between the fluxes and the forces, namely so-called kinetic coefficients, are obtained by solving the binary-species linearized and steady Boltzmann equation using the finite-difference method. The kinetic coefficients at different rarefaction parameters and molar fractions are validated by comparing them with the literature. The Chebyshev polynomial approximation method is introduced to reduce the computational consumption of kinetic coefficients. Then the transient flow through a long capillary can be efficiently and accurately predicted by this model. Based on the proposed model, the possible clogging problem during the filling process of the target gas through the capillary is further investigated. The critical pressure ratio for judging clogging is proposed as a criterion. The influences of molar fraction, rarefaction parameter, and molecular mass ratio on the critical pressure ratio were investigated. The results showed that the critical pressure ratio was positively correlated to the rarefaction parameter and negatively correlated to the molar fraction. Only at relatively low molar fractions, the effect of molecular mass ratio on the critical pressure ratio of the light species is significant.

In the field of inertial confinement fusion and ion beam-driven high-energy-density physics, the energy deposition along the beam trajectory is a critical physical parameter. Beyond particle collisions, the collective effects of plasma can significantly affect ion transport. The development of two-stream instability induced by beam-plasma interaction plays a crucial role, as it simultaneously affects the beam structure and its energy transfer. This paper presents an experimental investigation into the transverse modulation effects with a 100 keV proton beam passing through low-density hydrogen plasma. The results demonstrate that the observed beam defocusing phenomenon can be attributed to the excitation of two-stream instability: the diffusion of returning electrons leads to the formation of a radial electric field, which ultimately induces the transverse divergence of the proton beam. Both the numerical simulations based on analytical theoretical methods and particle-in-cell simulations are quantitatively validated, yielding results consistent with the experimental observations. Furthermore, the particle-in-cell simulation results indicate that wave-particle interactions can lead to additional energy loss, which is more significant than collision term. Experimental investigations of the two-stream instability are essential for revealing its underlying dynamics, validating theoretical descriptions, and improving the reliability of the ion beam transport modeling in plasmas.

Activity and renewability are distinctive features of living matter and constitute a new class of materials that we term renewable active matter. A striking example is the cell cytoskeleton, where myosin filaments bind to the actin meshwork, apply contractile stresses, and undergo continual stress- or strain-dependent turnover, thus acting as both force generators and sensors. As a consequence of nonreciprocity, arising from the independence of action and response, such living matter exhibits unusual mechanical properties like, segregation without attraction, fragility and force chains. Here we show that the interplay between activity and turnover gives rise to mechanical excitability in the form of traveling waves and pulses, and spatiotemporal chaos. We provide a systematic study of the nucleation, movement and shape of the traveling pulse, and present a boundary layer analysis to establish the existence of homoclinic orbits. Our analytical results are supported by detailed numerical analysis of the governing partial differential equations. This study has implications for the observed mechanical excitability in a variety of cellular contexts such as in isolated adherent cells and confluent cells within tissues.

We describe and analyze a generalization of the classic “Four Bugs on a Square” cyclic pursuit problem. Instead of allowing the bugs to spiral towards one another, we constrain $N$ bugs to the perimeter of the unit circle. Depending on their configuration, each bug moves either clockwise or counterclockwise with a constant angular speed, or remains stationary. Unlike the original problem where bugs always coalesce, this generalization produces three possible steady states: all bugs coalescing to a single point, clusters of bugs located at two antipodal points, or bugs entering a stable infinite chase cycle where they never meet. We analyze the stability of these steady states and calculate the probability that randomly initialized bugs reach each state. For $N\le 4$, we derive exact analytical expressions for these probabilities. For larger values, we employ Monte Carlo simulations to estimate the probability that randomly initialized bugs will eventually coalesce, and find that it approximately follows an inverse square-root relationship with the number of bugs. This generalization reveals rich dynamical behaviors that are absent in the classic problem. Our analysis provides insight into how restricting the bugs to the circle's perimeter fundamentally alters the long-term behavior of pursuing agents compared to unrestricted pursuit problems.

Disordered systems can exhibit a dramatic slowdown of their dynamics called aging. Contrary to the established understanding that this phenomenon is destroyed by nonreciprocal interactions, we here show that the outcome crucially depends on the structure of the system. Unlike previous studies, which focused on random nonsymmetric interactions between simple microscopic components, we investigate a scenario where nonreciprocally coupled agents are macroscopic entities with complex internal dynamics, modeled as two identical spin glasses. This framework could be relevant for many biological systems, in which nonreciprocal interactions can arise at a coarse-grained level. Our dynamical mean-field theory calculations reveal a finite temperature transition from a static disordered phase to a non-time-translationally-invariant regime. Below this transition, mediated by a spectral singularity known as exceptional points, we find macroscopic oscillations superimposed on aging behavior. Asymptotically, the system rotates in the plane spanned by the two lowest energy modes of the uncoupled system. We contrast these results to the case of random nonreciprocity, where aging is suppressed at any finite temperature, and propose that the two cases correspond to two broader classes of systems, with “microscopic” versus “macroscopic” nonreciprocity, with aging surviving only in the second case.

Chaos is ubiquitous in high-dimensional neural dynamics. A strong chaotic fluctuation may be harmful to information processing. A traditional way to mitigate this issue is to introduce Hebbian plasticity, which can stabilize the dynamics. Here, we introduce another distinct way without synaptic plasticity. An Onsager reaction term due to the feedback of the neuron itself is added to the vanilla recurrent dynamics, making the driving force a gradient form. The original unstable fixed points supporting the chaotic fluctuation can then be approached by further decreasing the kinetic energy of the dynamics. We show that this freezing effect also holds in more biologically realistic networks, such as those composed of excitatory and inhibitory neurons. The gradient dynamics are also useful for computational tasks such as recalling or predicting external time-dependent stimuli.

The rheology of dense granular shear flows is influenced by friction and particle shape. We investigate numerically the impact of nonspherical particle geometries under shear on packing fraction, stress ratios, velocity fluctuations, force distribution, and dissipation mechanisms, for a wide range of inertial numbers, friction coefficients and aspect ratios. We obtain a regime diagram for the dissipation which shows that lentil-like (oblate) particles exhibit an extended sliding regime compared to ricelike (prolate) particles with the same degree of eccentricity. Additionally, we identify nonmonotonic behavior of slightly aspherical particles at low friction, linking it to their higher fluctuating rotational kinetic energy. We find that angular velocity fluctuations are generally reduced when particles align with the flow, except in highly frictional rolling regimes, where fluctuations collapse onto a power-law distribution and motion becomes less correlated. Moreover, for realistic friction coefficients power dissipation tends to concentrate along the major axis aligned with the flow, where slip events are more frequent. We also show that flat particles develop stronger fabric anisotropy than elongated ones, influencing macroscopic stress transmission. These findings provide new insights into the role of particle shape in granular mechanics, with implications for both industrial and geophysical applications.

In the frequency power spectral density, periodic oscillations appear as a Dirac comb at integer multiples of the frequency of the period. In weakly nonlinear systems or systems close to the primary instability threshold, the periodicity may be perturbed, resulting in deviations from the Dirac comb. We review and discuss a stochastic model of such semiperiodic fluctuations, while also providing several new results which widen the applicability of the model. The fluctuations are described as a superposition of pulses with a fixed shape. Closed form expressions are derived for the frequency power spectral density in the case of periodic pulse arrivals and a random distribution of pulse amplitudes. In general, the spectrum is a Dirac comb located at multiples of the inverse periodicity time and modulated by the pulse spectrum. Deviations from strict periodicity in the arrivals are considered in two ways: either as a random offset to each periodic arrival (jitter) or as independently distributed waiting times between arrivals (renewal). In this contribution, we show that both ways of including deviations from periodicity remove the Dirac comb with remarkable efficiency, leaving mainly the spectrum of the pulse function. Where the jitter process modulates the mass of the higher harmonics, the renewal process leads to spectral broadening. We clarify the effects of random pulse amplitudes on the frequency power spectrum and demonstrate the applicability of normally distributed waiting times to modeling. Contrary to the previous literature, we argue that negative waiting times do not pose problems for the theory, broadening the applicability of the normal approximation. Randomness in the pulse arrival times is investigated by numerical realizations of the process, and the model is used to describe time series of kinetic energy of fluctuating motions in two-dimensional thermal convection.

The out-of-time-order correlator (OTOC) is studied for a bosonic quantum lattice model. We gain its classical analog through the replacement of both commutators appearing in the quantum correlator by a corresponding Poisson bracket. The evaluation of the Poisson bracket is then performed in a complex-valued description of the Hamiltonian dynamics and, for the initial choice of quantum operators to be site-specific annihilators, turns out to be given by the expectation value of the absolute square of a specific element of the complex-valued monodromy matrix. The growth rate of this expectation value is compared to a typical chaos indicator, the mean finite-time Lyapunov exponent (FTLE). In both cases the numerical phase-space average is weighted by a Wigner function corresponding to a multimode coherent state. For a three-well Bose-Hubbard model in the Mott insulator regime, it is found that although, on the level of single trajectories, FTLE and classical OTOC show similar long-time behavior, after averaging, they exhibit a marked difference [which for purely chaotic initial conditions is close to $ln\left(\sqrt{2}\right)$], rooting in the different order the logarithm and the average are taken. This observation is an example of the relevance of the fluctuations of the FTLE to correctly explain the quantitative difference between OTOC growth rate and FTLE in a prototypical many-body system.

The partial information decomposition (PID) framework has emerged as a powerful tool for analyzing high-order interdependencies in complex network systems. However, its application to dynamic processes remains challenging due to the implicit assumption of memorylessness, which often falls in real-world scenarios. In this work, we introduce the framework of partial information rate decomposition (PIRD) that extends PID to random processes with temporal correlations. By leveraging mutual information rate instead of mutual information (MI), our approach decomposes the dynamic information shared by multivariate random processes into unique, redundant, and synergistic contributions obtained aggregating information rate atoms in a principled manner. To concretely implement this idea, we define a pointwise redundancy rate function based on the minimum MI principle applied locally in the frequency-domain representation of the processes. The framework is validated in benchmark simulations of Gaussian systems, demonstrating its advantages over traditional PID in capturing temporal correlations and showing how the spectral representation may reveal scale-specific higher-order interactions that are obscured in the time domain. Furthermore, we apply PIRD to a physiological network comprising cerebrovascular and cardiovascular variables, revealing frequency-dependent redundant information exchange during a protocol of postural stress. Our results highlight the necessity of accounting for the full temporal statistical structure and spectral content of vector random processes to meaningfully perform information decomposition in network systems with dynamic behavior such as those typically encountered in neuroscience and physiology.

This study explores collective learning in living neural networks, focusing on group-to-group Hebbian learning, i.e., strengthening and weakening of links dependent on the precise timing of their activities. While neuronal plasticity is now well understood for single pairs of neurons, recent research has demonstrated that groups of tens of neurons are required to encode information in mammalian brains. Thus, it is critical to understand how mechanisms of plasticity, in particular spike-timing-dependent plasticity, operate at the group scale. We find that neuronal groups can reach significant plasticity after only 45 stimuli when a proper tradeoff between pulse duration and photostimulation effectiveness is chosen. Random contextual stimulation, which enhances the reliability of response for the targeted neuronal groups, is necessary for rapid network-level Hebbian learning. By demonstrating enhanced learning in the presence of random contextual activity, this study underscores the highly cooperative character of neurons and the importance of investigating learning, information flow, and memory formation at the network scale.

Experimental benchmarking of transport coefficients under extreme conditions is required for validation of differing theoretical models. To date, measurement of transport properties of dynamically compressed samples remains a challenge with only a limited number of studies able to quantify transport in high pressure and temperature matter. x-ray photon correlation spectroscopy utilizes coherent x-ray sources to measure time correlations of density fluctuations, thus providing measurements of length and timescale-dependent transport properties. Here, we present a first-of-a-kind experiment to conduct x-ray photon correlation spectroscopy in laser shock compression experiments. We report measurement of the turbulent velocity in the wake of a laser driven supersonic shock and place an upper bound on thermal diffusivity in a solid density plasma on nanosecond timescales.

The shear flow of granular materials is studied in the presence of overburden pressure and gravity using the discrete element method. The system comprises particles confined between parallel walls moving with constant speed in opposite directions and with an overburden pressure applied on the top wall, which is free to move in the wall-normal direction. The overburden pressures are high enough that the stored elastic energy due to compression of the particles is significant. The variation in the average velocity, solid volume fraction, and fluctuation velocity profiles with overburden pressure is shown. For most of the overburden pressures, a coexistence of a sheared region and a pluglike region is observed. As the overburden pressure increases, a flow transition is observed from a plug in the lower region to a plug in the upper region. At intermediate overburden pressures, a wide shear zone and a fluctuating profiles are observed. The transition is found to be continuous with increasing overburden pressure, and a scaling relation for the average midplane velocity variation with pressure is obtained for different wall velocities and particle stiffness values. Analysis of different configurations of the system show that the pluglike region forms near the fluctuating wall, where pressure is applied. The instantaneous velocity profile is found to vary chaotically with time at intermediate pressures. The midline velocity distribution is found to be Gaussian in most of the cases studied with a higher standard deviation at the intermediate pressures and lower wall velocities. The work highlights the nonlinear behavior of granular shear flow as a result of overburden pressure, which includes multiplicity and chaotic velocities.

Collective actuation in active solids, the spontaneous condensation of the dynamics on a few elastic modes, takes place whenever the deformations of the structure reorient the forces exerted by the active units composing, or embedded in, the solid. In a companion paper, we show through a combination of model experiments, numerical simulations, and theoretical analysis that adding an external field that polarizes the active forces strongly affects the dynamical transition to collective actuation. A new oscillatory regime emerges, and a reentrance transition to collective actuation takes place. Depending on the degeneracy of the modes on which the dynamics condensates, and on the orientation of the field with respect to the stiff direction of the solid, several new dynamical regimes can be observed. The purpose of the present paper is to review these dynamical regimes in a comprehensive way, both for the single-particle dynamics and for the coarse-grained one. Whenever possible the dynamical regimes and the transition between them are described analytically, otherwise numerically.

It is frequent for active or living entities to find themselves embedded in a surrounding medium. Resulting composite systems are usually classified as either active fluids or active solids. Yet, in reality, particularly in the biological context, a broad spectrum of viscoelasticity exists in between these two limits. There, both viscous and elastic properties are combined. To bridge the gap between active fluids and active solids, we here systematically derive a unified continuum-theoretical framework. It covers regimes of viscous, viscoelastic, and elastic active behavior. Our continuum equations are obtained by coarse-graining a discrete, agent-based microscopic dynamic description. In our subsequent analysis, we mainly focus on thin active films on supporting substrates. Strength of activity and degree of elasticity are used as control parameters that control the overall behavior. We concentrate on the analysis of transitions between spatially uniform analytical solutions of collective migration. These include isotropic and polar, orientationally ordered states. A stationary polar solution of persistent directed collective motion is observed for rather fluidlike systems. It corresponds to the ubiquitous swarming state observed in various kinds of dry and wet active matter. With increasing elasticity, persistent motion in one direction is prevented by elastic anchoring and restoring forces. As a consequence, rotations of the spatially uniform migration direction and associated flow occur. Our unified description allows us to continuously tune the material behavior from a viscous active fluid, via a range of intermediate viscoelasticity, to dampened elastic active behavior by variation of a single parameter. Therefore, it allows us in the future to investigate the time evolution of complex systems and biomaterials such as biofilms within one framework.

The correspondence between quantum and classical behavior has been essential since the advent of quantum mechanics. This principle serves as a cornerstone for understanding quantum chaos, which has garnered increased attention due to its strong impact in various theoretical and experimental fields. When dissipation is considered, quantum chaos takes concepts from isolated quantum chaos to link classical chaotic motion with spectral correlations of Ginibre ensembles. This correspondence was first identified in periodically kicked systems with damping, but it has been shown to break down in dissipative atom-photon systems [Phys. Rev. Lett. 133, 240404 (2024)]. In this contribution, we revisit the original kicked model and perform a systematic exploration across a broad parameter space, reaching a genuine semiclassical limit. Our results demonstrate that the correspondence principle, as defined through this spectral connection, fails even in this prototypical system. These findings provide conclusive evidence that Ginibre spectral correlations are neither a robust nor a universal diagnostic of dissipative quantum chaos.

The physics of interacting baths is of interest in a variety of contexts, ranging from ultracold atoms to ionized gases. While many features can already be captured in a one-dimensional model, others are specific to the situation of two- or three-dimensional systems. In this paper we focus on three-dimensional features of a model for thermalization between two baths that we have explored in earlier publications. In contrast to the one-dimensional situation we show that, en route to thermalization, deviations from the Maxwell-Boltzmann energy distributions more akin to $\kappa$ distributions are observed. In three dimensions, these can be seen in changes at the peak of the distribution, which is precluded by the expected monotonic behavior of the energy distributions in one dimension. Furthermore, we consider thermalization for anisotropic trapping and explore its role in the onset of anomalous scaling with respect to the particle number. These results may be pertinent to the understanding of the interplay between turbulent behavior and nonlinearities for a variety of many-body classical systems.