Physical Review E最新文献

Near a tipping point, a critical transition occurs when small changes in input conditions lead to abrupt, often irreversible shifts in a dynamical system's state. This phenomenon is observed in various biological and physical systems, including the collapse of species in ecosystems. Several statistical indicators, known as early warning signals (EWSs), have been developed to anticipate such collapses, garnering significant attention for their broad applicability. This paper investigates the stochastic versions of a bistable algae-zooplankton food-chain model under demographic and environmental noise. Our findings show that an increase in the predatory fish population, which consumes zooplankton, triggers a collapse in zooplankton abundance through a saddle-node bifurcation. Basin stability measure reveals that the resilience of the underexploited steady state significantly diminishes as the system approaches the collapse point. We evaluate the efficacy of various generic EWSs in predicting sudden collapses under both types of noise through statistical analysis. The robustness of AR(1) and variance are assessed through a comprehensive sensitivity analysis of processing parameters. We also calculate conditional heteroskedasticity, which minimizes false positive signals in the time series. Our results indicate that the prediction accuracy of variance and conditional heteroskedasticity remains independent of the noise type. However, AR(1) and skewness perform better in the presence of environmental noise.

Clathrin-mediated endocytosis is the main pathway used by eukaryotic cells to take up extracellular material, but the dominant physical mechanisms driving this process are still elusive. Recently, several high-resolution imaging techniques have been used on different cell lines to measure the geometrical properties of clathrin-coated pits over their whole lifetime. Here, we first show that the combination of all datasets with the recently introduced cooperative curvature model defines a consensus pathway, which is characterized by a flat-to-curved transition at finite area, followed by linear growth and subsequent saturation of curvature. We then apply an energetic model for the composite of the plasma membrane and clathrin coat to this consensus pathway to show that the dominant mechanism for invagination could be coat stiffening, which might originate from cooperative interactions between the different clathrin molecules and progressively drives the system toward its intrinsic curvature. Our theory predicts that two length scales determine the invagination pathway, namely the patch size at which the flat-to-curved transition occurs and the final pit radius.

Periodically driven classical many-body systems can host a rich zoo of prethermal dynamical phases. In this work, we extend the paradigm of classical prethermalization to aperiodically driven systems. We establish the existence of a long-lived prethermal regime in spin systems subjected to random multipolar drives. We demonstrate that the thermalization time scales as (1/T)^{2n+2}, where n is the multipolar order and T is the intrinsic time-scale associated with the drive. In the n→∞ limit, the drive becomes quasiperiodic and the thermalization time becomes exponentially long [∼exp(β/T)]. We further establish the robustness of prethermalization by demonstrating that these thermalization time scaling laws hold for a wide range of initial state energy densities. Intriguingly, the thermalization process in these classical systems is parametrically slower than their quantum counterparts, thereby highlighting important differences between classical and quantum prethermalization. Finally, we propose a protocol to harness this classical prethermalization to realize time rondeau crystals.

This paper introduces a method to estimate irreversibility in multivariate time series based on the well-known mapping to a binary classification problem. Our approach utilizes gradient boosting as a binary classifier, thus providing a model-free, nonlinear, and multivariate analysis while requiring minimal calibration of the classifier. An additional functionality of the proposed methodology is to easily dissect the contributions to the irreversibility of subsets of variable interactions, for instance, those operating at different time scales. The pipeline is divided into three phases: trajectory encoding, Markovian order identification, and irreversibility estimation via the classifier; the latter could be refined by hypothesis testing and quantification of variable interactions' contributions to irreversibility. When applied to financial markets, our findings reveal a distinctive shift: During stable periods, irreversibility is mainly related to short-term patterns, whereas in unstable periods, these short-term patterns are disrupted, leaving only contributions from stable, long-term ones.

Controlling and understanding phenomena in coupled systems remains a significant challenge across diverse fields. This study investigates a simple globally coupled chemical system that exhibits a range of rich collective dynamics, from coherence to chimera states, controllable by a system parameter. We explore the effects of altering this control parameter using two different protocols. In protocol-I, a continuous variation of the control parameter leads to memory effects, resulting in two distinct sets of phenomena in the forward and reverse directions. In contrast, protocol-II, which includes a resetting feature, yields an entirely distinct collection of behaviors. Additionally, we capture the evolution of key elements of nonequilibrium thermodynamics associated with these dynamical states under both protocols, revealing distinct signatures for each. This work highlights the complexity and uniqueness of regulating coupled systems via control parameters compared to corresponding single systems, and it carries potential implications for the manipulation and application of collective behaviors.

While renormalization groups are fundamental in physics, renormalization of complex networks remains vague in its conceptual definition and methodology. Here, we propose a novel strategy to renormalize complex networks. Rather than resorting to handling the bare structure of a network, we overlay it with a readily renormalizable physical model, which reflects real-world scenarios with a broad generality. From the renormalization of the overlying system, we extract a rigorous and simple renormalization group transformation of arbitrary networks. In this way, we obtain a transparent, model-dependent physical meaning of the network renormalization, which in our case is a scale transformation preserving the transition dynamics of low-density particles. We define the strength of a node in accordance with the physical model and trace the change of its distribution under our renormalization process. This analysis demonstrates that the strength distributions of scale-free networks remain scale-invariant, whereas those of homogeneous random networks do not.

Percolation processes on random networks have been the subject of intense research activity over the last decades: the overall phenomenology of standard percolation on uncorrelated and unclustered topologies is well known. Still some critical properties of the transition, in particular for heterogeneous substrates, have not been fully elucidated and contradictory results appear in the literature. In this paper we present, by means of a generating functions approach, a thorough and complete investigation of percolation critical properties in uncorrelated locally treelike random networks. We determine all critical exponents, the associated critical amplitude ratios, and the form of the cluster size distribution for networks of any level of heterogeneity. We uncover, in particular for highly heterogeneous networks, subtle crossover phenomena, nontrivial scaling forms, and violations of hyperscaling. In this way we clarify the origin of inconsistencies in the previous literature.

Femtosecond laser pulse propagation in a relativistic self-trapping (RST) regime in a near-critical density plasma makes it possible to maximize the total charge of the accelerating electrons and laser-to-electrons conversion rate, that can be used to provide a large amount of the terahertz range coherent transition radiation. The three-dimensional particle-in-cell simulations demonstrate how such transition radiation generates when electrons escape into vacuum either from the low-density target itself, or after passing through a thin foil located at the target end. The advantage of the RST regime for the generation of terahertz pulses is clearly demonstrated as compared to laser irradiation of such a standard target as a foil with preplasma on its front side. The simulation performed has shown that for the optimized laser-target matching a 2-J femtosecond laser pulse is able to produce quasiunipolar terahertz pulses with energy exceeding 100 mJ.

Electromagnetic showers developing from the collision of an ultraintense laser pulse with a beam of high-energy electrons or photons are investigated under conditions relevant to future experiments on multipetawatt laser facilities. A semianalytical model is derived that predicts the shower multiplicity, i.e., the number of pairs produced per incident seed particle (electron or γ photon). The model is benchmarked against particle-in-cell simulations and shown to be accurate over a wide range of seed particle energies (from 100 MeV to 40 GeV), laser relativistic field strengths (10

This paper analyzes the influence of laterally enforced solutal gradients on the steady and bifurcated periodic dynamics in binary fluids contained in horizontally heated slots, taking into account the Soret and Dufour effects. Numerical Newton-Krylov continuation techniques to follow the primary and secondary branches of steady solutions and periodic orbits are applied. The stability of all these branches is also analyzed. A great variety of stable steady and periodic states is found, depending on the ratio of the thermal and solutal gradients. The proximity to parameters that balance the buoyancy forces delays the onset of center-symmetric oscillations to very large values of the thermal Rayleigh number, while large solutal gradients tend to restabilize the steady flows after the onset of center-symmetric oscillations, and to give rise to spatiotemporal symmetric waves of broken center symmetry at larger thermal Rayleigh number. The work done by the thermal buoyancy force is essential for the restabilization of the steady states and the change of the ulterior dynamics. It is also shown that the transition to temporal chaos depends strongly on the absence or intensity of the solutal gradients.