Physical Review E最新文献

Relevant and fundamental concepts of the statistical mechanical theory of classical liquids are ordinarily introduced in the context of the description of thermodynamic equilibrium states. This makes explicit reference to probability distribution functions of equilibrium statistical ensembles (canonical, microcanonical, etc.) in the derivation of general and fundamental relations between interparticle interactions and measurable macroscopic properties of a given system. This includes, for instance, expressing the internal energy and the pressure as functionals of the radial distribution function, or writing transport coefficients (diffusion constant, linear viscosity, etc.) in terms of integral relations involving both static and dynamic autocorrelation functions (density-density, stress-stress, etc.). Most commonly, however, matter is not in thermodynamic equilibrium, and this calls for the extension of these relations to out-of-equilibrium conditions with the aim of understanding, for example, the time-dependent transient states during the process of equilibration, or the aging of glass- and gel-forming liquids during the formation of nonequilibrium amorphous solid states. In this work, we address this issue from both a general perspective and an illustrative concrete application focused on the first-principles description of rheological and viscoelastic properties of glass- and gel-forming liquids.

The linear stability of a lipid membrane under a dc electric field, applied perpendicularly to the interface, is investigated in the electrokinetic framework, taking into account the dynamics of the Debye layers formed near the membrane. The perturbed charge in the Debye layers redistributes and generates destabilizing Maxwell stress on the membrane, which outweighs the stabilizing contribution from the electrical body force, leading to a net destabilizing effect. The instability is suppressed as the difference in the electrolyte concentration of the solutions separated by the membrane increases, due to a weakened base state electric field near the membrane. This result contrasts with the destabilizing effect predicted using the leaky dielectric model in cases of asymmetric conductivity. We attribute this difference to the varying assumptions about the perturbation amplitude relative to the Debye length, which result in different regimes of validity for the linear stability analysis within these two frameworks.

Microswimmer locomotion in heterogeneous media is increasingly relevant in biological physics due to the prevalence of microorganisms in complex environments. A model for such porous media is the Brinkman fluid, which accounts for a sparse matrix of stationary obstacles via a linear resistance term in the momentum equation. We investigate two models for the locomotion and the flow field generated by a swimmer in such a medium. First, we analyze a dumbbell swimmer composed of two spring-connected spheres and driven by a flagellar force and derive its swimming velocity as a function of the Brinkman medium resistance, showing that the swimmer monotonically slows down as the medium drag monotonically increases. In the limit of no resistance the model reduces to the classical Stokes dipole swimmer, while finite resistance introduces hydrodynamic screening that attenuates long-range interactions. Additionally, we derive an analytical expression for the far-field flow generated by a Brinkmanlet force dipole, which can be used for propulsive point-dipole swimmer models. Remarkably, this approximation reproduces the dumbbell swimmer's flow field in the far-field regime with high accuracy. These results provide analytical tools for understanding locomotion in complex fluids and offer foundational insights for future studies on collective behavior in active and passive suspensions within porous or structured environments.

We present a multiscale simulation framework that couples the finite-element method with molecular dynamics. Bypassing traditional equations of state (EOS) by using in-line atomistic simulations, the method offers the advantage of incorporating detailed microscale physics not easily represented with coarse-grained models. Coupling consistency with the continuum code is ensured through the use of lifting and restriction operators, in line with heterogeneous multiscale methods. The concurrent continuum-atomistic framework is validated through comparison with experimental results and conventional EOS models, and demonstrated in a shock-driven hydrodynamic flow simulation under extreme conditions. We further evaluate the framework's usability by comparing it to state-of-the-art EOS models of deuterium. A computational performance study reveals that the atomistic EOS evaluation is a feasible alternative to conventional approaches, and demonstrates a weak scaling of 99% efficiency. These results highlight the framework's potential for large-scale multiscale modeling across a broad range of materials and conditions.

The Stuart-Landau oscillator generalized to D>2 dimensions has SO(D) rotational symmetry. We study the collective dynamics of a system of K such oscillators of dimensions D=3 and 4, with coupling chosen to either preserve or break rotational symmetry. This leads to emergent dynamical phenomena that do not have analogs in the well-studied case of D=2. Further, the larger number of internal parameters allows for the exploration of different forms of heterogeneity among the individual oscillators. When rotational symmetry is preserved there can be various forms of synchronization as well as multistability and partial amplitude death, namely, the quenching of oscillations within a subset of variables that asymptote to the same constant value. The oscillatory dynamics in these cases are characterized by phase locking and phase drift. When the coupling breaks rotational symmetry we observe partial synchronization (when a subset of the variables coincide and oscillate) and partial oscillation death (when a subset of variables asymptote to different stationary values), as well as the coexistence of these different partial quenching phenomena.

Extensive behavioral experiments reveal that conditional cooperation is a prevalent phenomenon. Previous game-theoretical studies have predominantly relied on hard-manner models, where cooperation is triggered only upon reaching a specific threshold. This approach contrasts with the observed flexibility of human behaviors, where individuals adapt their strategies dynamically based on their surroundings. To capture this adaptability, here we introduce a soft form of conditional cooperation by integrating the Q-learning algorithm from reinforcement learning. In this form, players not only reciprocate cooperation but may also defect in highly cooperative environments or cooperate in less-cooperative settings to maximize rewards. To explore the effects of hard and soft conditional cooperators, we examine their interactions in two scenarios: structural mixture (SM) and probabilistic mixture (PM), where the two behavioral modes are fixed and probabilistically adopted, respectively. In SM, hard conditional cooperators enhance cooperation when the threshold is low but hinder it otherwise. Surprisingly, in PM, the cooperation prevalence exhibits two first-order phase transitions as the probability is varied, leading to high, low, and vanishing levels of cooperation. Analysis of Q tables offers insights into the "psychological shifts" of soft conditional cooperators and the overall evolutionary dynamics. Model extensions confirm the robustness of our findings. These results highlight the novel complexities arising from the diversity of conditional cooperators.

Motility is important for bacteria for their survival, adaptation, and pathogenesis, especially in complex environments such as mucus, tissues, and biofilms. Although bacterial motility has been extensively studied based on imaging and tracking bacterial cell bodies, how the behavior and dynamics of the flagellar filaments of bacteria are affected by complex environments remains largely unexplored. To address this knowledge gap, we exploited site-directed mutagenesis and specific fluorescence labeling and directly visualized the flagellar filaments of Escherichia coli (E. coli) bacteria in polyethylene glycol-based hydrogel under fluorescence microscopy. We observed and classified three distinct types of flagellar motions of the E. coli bacteria in hydrogels: swimming (SWIM), trapped (TRAP), and stalled (STALL). Additionally, we quantified and compared the shapes and behaviors of the bacterial flagella of the three types using various shape quantifiers and descriptors. We found that these shape descriptors and quantifiers reliably and consistently reported the behaviors of the bacterial flagellar filaments. We examined the correlation of bacterial motility and flagellar dynamics for the three types, and found that the interactions of the bacterial flagella and hydrogel polymers/mesh reduced such correlation. Last, we inspected the flagellar filaments in more detail and identified their abnormalities due to hydrogel confinement and entanglement of the flagellar filaments with hydrogel polymers. The methods and analyses from this study are expected to support future efforts to develop and optimize hydrogels for more effective trapping of motile bacteria, thereby informing improved contamination-control strategies in hydrogel-related biomedical applications.

The inclusion of the process of multiple ionization of atoms in high-intensity electromagnetic fields into particle-in-cell (PIC) codes applied to the simulation of laser-plasma interactions is a challenging task. In this paper, we first revisit ionization rates as given by the Smirnov-Chibisov and Perelomov-Popov-Terent'yev formulas within the paradigm of sequential tunnel ionization. We analyze the limit of validity and possible inconsistencies of this approach. We show that a strongly limiting factor to a precise description of ionization is the competing contribution of different sequential ionization processes. To solve this an algorithm is proposed that allows one to find the dominant nonsequential path of tunnel ionization and significantly improves the precision in simulations. This procedure is implemented in the PIC code SMILEI, and includes the dependence of the ionization rates on the magnetic quantum number of the level. The sensitivity to variations in the ionization model is studied via full simulations of the ionization of an argon target by an incident high-intensity laser pulse. Finally, we analyze generalizations of the Perelomov-Popov-Terent'yev rate developed to describe the barrier suppression ionization in high fields and discuss the necessity and possibility of including these extensions in PIC simulations.

We study effective mixing behavior of solutes in steady flows through three-dimensional random fracture networks and find that mixing in these systems is characterized by phenomena distinct from continuous porous media. Network-scale heterogeneity leads to the complex spatio-temporal organization of the flow-field that determines a mixing interface between transported solutes. The growth of the mixing interface is characterized by splitting events as it crosses between fracture intersections, which does not occur in a continuous porous medium. We derive an analytical model for growth of the mixing interface, which is a function of network properties. Agreement of the model with high-fidelity simulations of flow and transport indicates a link between network topology and mixing dynamics unique to fractured media. The model also provides asymptotic predictions that are intractable with current numerical simulations. Moreover, we do not observe the chaotic exponential growth of the mixing interface that is commonly observed in porous media. The observations and model development indicate a foundational difference in mixing behavior between fractured and porous media.

We present a class of self-similar solutions describing ultrahigh compression of a uniform-density target by spherically converging, stacked shock waves. Extending the classical Guderley model, we derive a scaling law for the final density of the form ρ_{r}/ρ_{0}∝P[over ̂]^{β(N-1)}, where N is the number of shocks, P[over ̂] the stage pressure ratio, and β a numerical exponent determined by the adiabatic index γ. One-dimensional hydrodynamic simulations confirm the validity of this scaling across a broad parameter range. Notably, the relation remains accurate even in the strongly nonlinear regime up to P[over ̂]∼70, well beyond the perturbative limit, highlighting the robustness and practical relevance of the model. Owing to its volumetric geometry, this compression scheme inherently avoids the Rayleigh-Taylor instability, which typically compromises shell-based implosions, and thereby establishes a theoretical benchmark for instability-free compression in inertial confinement fusion.