Physical review. E最新文献

Experiments using a rotational rheometer have demonstrated that the apparent viscosity becomes negative under the electric-field-induced turbulent state of conductive nematic liquid crystals [Orihara et al., Phys. Rev. E 99, 012701 (2019)10.1103/PhysRevE.99.012701; F. Kobayashi et al., Phys. Rev. E 101, 022702 (2020)10.1103/PhysRevE.101.022702]. When the upper rotating plate of the rheometer is left free, spontaneous rotation-that is, spontaneous shear flow-has also been observed. In this study, we reproduce these phenomena through three-dimensional simulations based on continuum theory. The simulations reveal characteristic velocity, director, and stress fields in the negative-viscosity state. Furthermore, they clarify the interplay between topological defects (disclinations) and space charges which drive the turbulence.

A variety of bacterial species are able to spontaneously assemble into an aerotactic band, a local accumulation at a fixed distance from the air-water interface. Although the phenomenon is long known, its modeling so far is limited to mesoscopic, one-dimensional or numerical descriptions. We investigate band properties at the microscopic scale using exact solutions to the Fokker-Planck equation. First, we show that the interplay between oxygen consumption and tumbling modulation is governed by a third-order nonlinear differential equation relating the oxygen concentration to the aerotactic response. For two model aerotactic behaviors, we present analytical solutions and discuss the resulting band structure. Second, we investigate how an aerotactic band of magnetotactic bacteria in a magnetic field induces a fluid flow, as observed in experiments [Marmol et al., Phys. Rev. Lett. (2025), doi: 10.1103/qrgn-m91t]. In the low-field limit, we determine the bacterial distribution and the active stress tensor. Using the Green function of the hydrodynamic problem, we obtain a prediction for the fluid flow that is both simple and consistent with observations. Altogether, our results provide a model system of aerotactic band and solid ground for analyzing aerotaxis-driven self-organization.

The generation of 200 MeV class protons by irradiating a 25 J laser pulse onto a water target using three-dimensional particle-in-cell simulation is shown. Two types of targets-foil and disk-are evaluated and compared. Disks, which are mass-limited targets, produce ions with higher energy than those produced by foils. This enhancement is attributed to laser focusing equivalent effects in mass-limited targets during the acceleration process. In addition, the disk diameter that generates the maximum energy protons is theoretically derived, which shows good agreement with the simulation result.

Noether's theorem is traditionally applied to Lagrangian systems to identify conserved quantities. In this work, we apply Noether's theorem instead to a broad class of non-Lagrangian gradient flow partial differential equations (PDEs) arising in physics, showing how continuous symmetries constrain the evolution of such systems and, in certain special cases, still give rise to conserved quantities. We demonstrate symmetry-induced evolutionary constraints numerically on the thin-film equation with capillary and van der Waals forces, and also theoretically derive a conserved quantity for a singular fast-diffusion equation. These results not only provide a tool to analyze gradient flow PDEs; they also demonstrate the utility of Noether's theorem beyond Lagrangians.

Perfluorohexane is a biocompatible material that serves as a liquid core for acoustically responsive agents in biomedical applications. Despite its relatively widespread usage, there is a lack of experimental data determining its thermodynamic properties. This challenges numerical simulations to predict the acoustic response of agents developed using this material. In this study, we employ the well-established method of shock compression of materials at relatively high pressures (100-400 MPa) to estimate a kinematic equation of state for perfluorohexane. We use multi-objective optimization to obtain the Noble-Abel stiffened-gas equation of state, which is suitable for hydrodynamic numerical simulations. We then apply the extrapolated equation of state to simulate shock-wave propagation within a perfluorohexane droplet showing excellent agreement with equivalent experiments. This promotes the use of numerical simulations as a valuable tool for understanding the complex acoustic interactions involved in these biomedical agents, ultimately facilitating their translation for clinical purposes.

Extensive optical measurements of canonical turbulent pipe flows have revealed the existence of structural boundary states (SBSs)-near-wall low-speed streaks strongly correlated with pairs of counter-rotating quasistreamwise vortices. In this study, we investigate the number fluctuations of these structures within the framework of statistical mechanics. Specifically, we introduce reduced degrees of freedom to model the low-speed streaks as a dilute lattice gas of hard-core particles. The Metropolis stochastic evolution provides, furthermore, a simple yet effective two-parameter model for describing SBS transitions. The lattice gas approach enables us to derive both the probability of SBS occurrence and the peculiar self-similar correlations that these structures exhibit along the streamwise direction. Our findings give additional support to the idea that the statistically stationary regimes of wall-bounded turbulent flows can be understood as Markov chains of coherent dynamical states in reduced-dimensional phase spaces.

A century after Ising introduced the Ising measure to study equilibrium systems, its relevance has expanded well beyond equilibrium contexts, notably appearing in nonequilibrium frameworks such as the Katz-Lebowitz-Spohn (KLS) model. In this work, we investigate a class of generalized asymmetric simple exclusion processes (ASEPs) for which the Ising measure serves as the stationary state. We show that the average stationary current in these models can display current reversal and other unconventional behaviors, offering insights into transport phenomena in nonequilibrium systems. Moreover, although long-range interaction rates often give rise to long-range interactions in the potential function, our model provides a counterexample: Even with long-range interactions in the dynamics, the resulting potential remains short ranged. Finally, our framework encompasses several well-known models as special cases, including ASEPs, the KLS model, the facilitated exclusion process, the cooperative exclusion process, and the assisted exchange model.

Biomolecular condensates are essential for cellular organization and result from phase separation in systems far from thermodynamic equilibrium. Among various models, chemically active droplets play a significant role, and consist of proteins that switch between attractive and repulsive states via nonequilibrium chemical reactions. While field-based simulations have provided insights into their behavior, these coarse-grained approaches fail to capture molecular-scale effects, particularly in crowded cellular environments. Macromolecular crowding, a key feature of intracellular organization, strongly influences molecular transport within condensates, yet its quantitative impact remains underexplored. This study investigates the interplay between chemically active droplets and crowders by using particle-based models, that provide molecular insight, and a field-based model, that complements this picture. Surprisingly, crowding reduces droplet size while expanding the overall dense phase volume, challenging equilibrium-based expectations. This effect arises from the interplay between depletion interactions, diffusion hindrance, and nonequilibrium particle fluxes. Our findings provide a step towards a more comprehensive understanding of chemically active droplets in complex, realistic cellular environments.

We explore competitive dynamics in multiagent active matter systems using reinforcement learning. In our study, two active Brownian particles (referred to as predators) were trained using either simultaneous or sequential protocols to capture ten passive Brownian particles (preys). The training results depend on the agent, and generally one agent tends to overperform the other. To assess the effectiveness of the two protocols, we examined two policies: (i) a natural policy, where updates to the reinforcement learning parameters of both predators were stopped at a fixed time, even if one agent performed suboptimally; and (ii) a hybrid policy, where we combined the reinforcement learning parameters recorded when each agent achieved its optimal performance. If limited to natural training, simultaneous training appears to be the better option. However, when hybrid training is also allowed, sequential training becomes the preferred choice.

Tensor networks are employed to characterize the current fluctuations in one-dimensional diffusion-reaction systems. The representative system under study is a semiconducting material where holes and electrons constitute two types of charge carriers. These holes and electrons diffuse in the system with the reactions of pair-generation and -recombination occurring between them. The system is driven by imbalanced conditions imposed at two boundaries. The large deviation function encoding the full counting statistics of electric current is numerically calculated using the density matrix renormalization group. The fluctuation theorem is shown to hold for the current. Moreover, by comparing the cases where the reactions are turned on or off, it is revealed that the reactions have a damping effect on current fluctuations. This indicates an interesting inequality, suggesting that current fluctuations are upper bounded.