Physical review. E最新文献

Understanding how systems respond to external perturbations is a fundamental challenge in physics, particularly for nonequilibrium and nonstationary processes. The fluctuation-dissipation theorem provides a complete framework for near-equilibrium systems and various bounds have recently been reported for specific nonequilibrium regimes. Here, we present a compact, trajectory-score-based formulation that synthesizes and generalizes linear fluctuation-response relations for arbitrary Markov processes, decomposing system response into spatial correlations of local dynamical events. This decomposition reveals that response properties are encoded in correlations between transitions and dwelling times across the network, providing a natural generalization of the fluctuation-dissipation theorem and recently developed nonequilibrium linear response relations. Our theory unifies existing response bounds, extends them to time-dependent processes, and reveals fundamental monotonicity properties of the tightness of multiparameter response inequalities. Beyond its theoretical significance, this framework enables efficient numerical evaluation of response properties from sampling unperturbed trajectories, offering significant advantages over traditional finite-difference approaches for estimating response properties of complex networks and biological systems far from equilibrium.

Constraint satisfaction problems are ubiquitous in fields ranging from the physics of solids to artificial intelligence. In many cases, such systems undergo a transition when the ratio of constraints to variables reaches some value α_{crit}. Above this critical value, it is exponentially unlikely that all constraints can be mutually satisfied. We calculate the probability that constraints can all be satisfied, P(SAT), for the spherical perceptron. Traditional replica methods, such as the Parisi ansatz, fall short. We find a new ansatz, the jammed Parisi ansatz, that correctly describes the behavior of the system in this regime. With the jammed Parisi ansatz, we calculate P(SAT) for the first time and match previous computations of thresholds. We anticipate that the techniques developed here will be applicable to general constraint satisfaction problems and the identification of hidden structures in datasets.

The aggregation of amyloid-β42 (Aβ42) peptide, a key pathological event in Alzheimer's disease, is strongly influenced by its solvent environment. While cosolvents are often used in experimental studies, their specific role in modulating the conformational stability and aggregation propensity of Aβ42 remains poorly understood. We perform molecular dynamics simulations to investigate the effects of three organic solvents-ethanol (EtOH), dimethyl sulfoxide (DMSO), and acetonitrile (ACN)-on the structural dynamics of Aβ42. Our results reveal a distinct dichotomy: EtOH and DMSO exert a stabilizing effect by promoting the α-helical content, reducing Coil formation, and extending the lifetime of intramolecular hydrogen bonds. In contrast, ACN destabilizes the native state and accelerates the formation of aggregation-prone β-sheet structures. We attribute these opposing effects to the solvents' differential disruption of the peptide's hydrophobic core and their specific interactions with the protein backbone. This work elucidates the microscopic mechanisms by which solvent environment directs Aβ42 conformational sampling, with implications for understanding aggregation pathways and designing modulating agents.

The reflection and transmission coefficients of an electromagnetic wave interacting with an inhomogeneous plasma layer produced by multiphoton ionization of an inert gas in a magnetic field are determined. The possibility of terahertz radiation amplification is revealed. If the frequency of the probe radiation matches the electron cyclotron frequency, the field strength of the transmitted and reflected radiation can be amplified by more than two orders of magnitude. The amplification arises due to the Ramsauer-Townsend effect and the non-equilibrium energy distribution of the photoelectrons. Blurring the plasma boundary by an amount equal to a few percent of the uniform layer width results in a small decrease in radiation amplification. The energy spread of photoelectrons reduces the amplification by several times.

Heterophobic interactions, which drive individuals to be repelled from others with opposite opinions, play a role as important as homophilic ones in shaping many dynamical processes on social networks, such as opinion formation, social balance, or epidemic spreading. In this paper, we use belief propagation and Monte Carlo simulations on treelike signed graphs to predict that a sufficient propensity to heterophobia can impede a consensus that would otherwise emerge via a phase transition. As the strength of heterophobic interactions and the rationality of individuals with respect to social stress decrease, this transition changes from continuous to discontinuous, with a strong dependence on the initial conditions. The size of the parameter region where consensus can be reached from any initial condition decays as a power-law function of the number of discussed topics.

Building upon the framework established in our recent work [M. Seifi et al., Phys. Rev. E 111, 054114 (2025)10.1103/PhysRevE.111.054114], wherein a generalized Maxwell-Boltzmann distribution was formulated using the Mittag-Leffler function within the superstatistical formalism, we extend this approach to the quantum domain. Specifically, we introduce two statistical distributions-termed the Mittag-Leffler-Bose-Einstein (MLBE) and Mittag-Leffler-Fermi-Dirac (MLFD) distributions-constructed by generalizing the conventional Bose-Einstein and Fermi-Dirac distributions through the Mittag-Leffler function. This generalization incorporates a deformation parameter α, which facilitates a continuous interpolation between bosonic and fermionic statistics, while inherently capturing nonequilibrium effects and generalized thermodynamic behavior. We analyze the thermodynamic geometry associated with these distributions and identify significant departures from standard statistical models. Notably, the MLBE distribution manifests a Bose-Einstein-like condensation even in the absence of interactions, whereas the MLFD distribution exhibits unconventional features, such as negative heat capacity in the low-temperature regime. These findings highlight the pivotal role of statistical deformation in determining emergent macroscopic thermodynamic phenomena.

Scale invariance is a hallmark of many natural systems, including solar flares, where energy release spans a vast range of scales. Recent computational advances, at the level of both algorithmics and hardware, have enabled high-resolution magnetohydrodynamical (MHD) simulations to span multiple scales, offering new insights into magnetic energy dissipation processes. Here, we study the scale invariance of magnetic energy dissipation in two distinct MHD simulations. Current sheets are identified and analyzed over time. Results demonstrate that dissipative events exhibit scale invariance, with power-law distributions characterizing their energy dissipation and lifetimes. Remarkably, these distributions are consistent across the two simulations, despite differing numerical and physical setups, suggesting universality in the process of magnetic energy dissipation. Comparisons between the evolution of dissipation regions reveal distinct growth behaviors in high plasma-β regions (convective zone) and low plasma-β regions (atmosphere). The latter display spatiotemporal dynamics similar to those of avalanche models, suggesting self-organized criticality and a common universality class.

We conduct standard dimensional analysis (Vaschy-Buckingham Π theorem) for the mean avalanche size 〈s〉 when particles flow through, and clog at, a small orifice on the base of a flat-bottomed silo. We consider the effect of particle diameter d, orifice diameter D, particle density ρ, particle Young's modulus E, and acceleration of gravity g. We both perform discrete element method simulations and compile available data in the literature in order to sample the parameter space. We find that our simulations and data across many experiments and simulations of frictional grains are consistent with the scaling equation ln(〈s〉+1)=A_{α}[(D/d)^{α}-1]+B_{α}sqrt[ρgd/E^{1}], where A_{α} and B_{α} are empirical constants and α is the dimensionality of the system (α=2 and α=3 for two dimensions and three dimensions, respectively). This expression successfully synthesizes the clogging behavior of a number of related clogging systems and motivates future extensions to more complex configurations involving, for example, very low friction particles or external vibrations.

We study the dynamics of an overdamped Brownian particle in a repulsive scale-invariant potential V(x)∼-x^{n+1}. For n>1, a particle starting at position x reaches infinity in a finite, randomly distributed time. We focus on the short-time tail T→0 of the probability distribution P(T,x,n) of the blowup time T for integer n>1. Krapivsky and Meerson [Phys. Rev. E 112, 024128 (2025)2470-004510.1103/1hds-9ttg] recently evaluated the leading-order asymptotics of this tail, which exhibits an n-dependent essential singularity at T=0. Here we provide a more accurate description of the T→0 tail by calculating, for all n=2,3,⋯, the previously unknown large preexponential factor of the blowup-time probability distribution. To this end, we apply a WKB (after Wentzel, Kramers and Brillouin) approximation-at both leading and subleading orders-to the Laplace-transformed backward Fokker-Planck equation governing P(T,x,n). For even n, the WKB solution alone suffices. For odd n, however, the WKB solution breaks down in a narrow boundary layer around x=0. In this case, it must be supplemented by an "internal" solution and a matching procedure between the two solutions in their common region of validity.

In standard rotating Hele-Shaw cell flows, an initially circular fluid drop, surrounded by an outer fluid of negligible density and viscosity, is centered at the rotation axis of the cell. The interplay of centrifugal and surface tension forces leads to the emergence of intricate interfacial patterns, markedly characterized by intense competition among the inward-moving fingers of the outer fluid as they penetrate the inner one. In this work, we study a variation of this traditional rotating flow problem, considering that the center of the initially circular drop is at a distance d from the cell's rotation axis. We explore this off-centered situation by employing numerical simulations based on the level set method. Our numerical results show that, at fully nonlinear stages of the flow, the off-center parameter d plays a key role in determining the morphology and dynamic competition among fingers, leading to the development of asymmetric interfacial patterns that drift away from the rotation axis of the cell. The impact of the effective surface tension parameter B (measure of the relative strength of centrifugal and capillary effects) on the main features of these complex, centrifugally driven translating patterns is also discussed.