International Journal of Modern Physics C

We demonstrate that a temperature schedule for single-spin flip transition matrix calculations can be simply and rapidly generated by monitoring the average size of the Wolff clusters at a set of discrete temperatures. Optimizing this schedule yields a potentially interesting quantity related to the fractal structure of Ising clusters. We also introduce a technique in which the transition matrix is constructed at a sequence of discrete temperatures at which Wolff cluster reversals are alternated with certain series of single-spin flip steps. The single spin-flip transitions are then employed to construct a single transition matrix.

In recent years, community detection has gradually become a hot topic in the complex network data mining field. The research of community detection is helpful not only to understand network topology structure but also to explore network hiding function. In this paper, we improve FluidC which is a novel community detection algorithm based on fluid propagation, by ameliorating the quality of seed set based on positive feedback and determining the node update order. We first summarize the shortcomings of FluidC and analyze the reasons result in these drawbacks. Then, we took some effective measures to overcome them and proposed an efficient community detection algorithm, called FluidC+. Finally, experiments on the generated network and real-world network show that our method not only greatly improves the performance of the original algorithm FluidC but also is better than many state-of-the-art algorithms, especially in the performance on real-world network with ground truth.

In the gas kinetic theory, it is shown that the zeroth order of the density distribution function $f^{(0)}$ and local equilibrium density distribution function were the Maxwellian distribution $f^{(\mathrm{\text{eq}})}(\rho ,u,T)$ with an external force term, where $\rho$ is the fluid density, $u$ is the physical velocity and $T$ is the temperature, while in the lattice Boltzmann equation (LBE) method, numerous force treatments were proposed with a discrete density distribution function $f_i$ apparently relaxed to a given state $f_i^{(\mathrm{\text{eq}})}(\rho ,u^{\ast })$, where the given velocity $u^{\ast }$ could be different with $u$, and the Chapman–Enskog (CE) analysis showed that $f_i^{(0)}$ and local equilibrium density distribution function should be $f_i^{(\mathrm{\text{eq}})}(\rho ,u^{\ast })$ in the literature. In this paper, we start from the kinetic theory and show that the $f_i^{(0)}$ and local equilibrium density distribution function in LBE should obey the Maxwellian distribution $f_i^{(\mathrm{\text{eq}})}(\rho ,u)$ with $f_i$ relaxed to $f_i^{(\mathrm{\text{eq}})}(\rho ,u^{\ast })$, which are consistent with kinetic theory. Then the general requirements for the force term are derived, by which the correct hydrodynamic equations could be recovered at Navier–Stokes (NS) level, and numerical results confirm our theoretical analysis.

Financial markets have been known to exhibit plentiful nonlinear complex volatility behaviors. In order to reproduce the volatility dynamics of financial price changes, the agent-based financial model is established by stochastic finite-range exclusion process. The exclusion process is a kind of statistical physics system, which is considered as modeling particle Markov motion with conserved number of particles. To measure the volatility of financial return series, a novel statistic called maximum monotonic volatility rate is put forward to measure the speed of monotonic volatility of returns. Meanwhile, average monotonic volatility duration of returns is also investigated, which can reflect the average volatility level. For verifying the rationality of the model, matching energy analysis that can detect chaos and complexity in nonlinear time series is applied to study the new statistics. Further, empirical mode decomposition and multifractal are employed to study the behaviors of monotonic volatility duration. The model has similar complexity behaviors with real markets in terms of monotonic volatility with matching energy analysis, and the proposed financial model and real markets both show multifractal and anti-correlation for average monotonic volatility series by MFDFA method. The results display that the model is feasible with respect to above volatility analyses.

The heat transfer from nanoparticles (NPs) to gas of photothermal effect is investigated by taking into account both conduction and radiation. The steady-state and unsteady-state heat transfer processes are studied analytically and numerically, respectively. In contrast to the photothermal effect in liquid with metal NPs, in which the radiation is negligible, we found that the thermal radiation must be taken into account in the nanoparticle–gas system. The reason is that the thermal boundary conductance (TBC) of gas–solid interface is several orders of magnitude smaller than the TBC of liquid–solid interface, especially when the diameter of nanoparticle is comparable to or smaller than the mean free path of gas molecules. We propose a method to measure the ultra-low TBC of interface between nanoparticle and gas based on our investigations.

In order to study the effect of crossing pedestrians on traffic performance at crosswalk without signal control, the work develops a game theory-based description of pedestrian–vehicle interactions, considering the decision-making uncertainty. The hybrid strategy of the game is obtained. The relevant parameters of the game model are calibrated by collected video data. The cellular automaton simulation system composed of a two-way four-lane traffic flow and pedestrian flow is constructed with the game model imbedded for identifying the effect of crossing pedestrians on traffic performance. The influencing factors are identified with their correlation analyzed by numerical simulation of different traffic conditions. According to the simulation results, the arrival rate of pedestrians has a great impact on traffic volume and pedestrian delay. The severity of conflicts between vehicles and pedestrians is classified and the causes are identified by analyzing the arrival rate of pedestrians and vehicles, respectively, and their relationship between one another. In addition, the threshold of traffic flow and pedestrian flow causing traffic conflicts and delay is proposed, also including the threshold of pedestrian arrival rate which will induce force crossing behaviors. The results show that the proposed model reconstructs the traits of traffic and pedestrian flow and their conflicts phenomenon at crosswalks. It provides some practical references for transportation agencies to meet pedestrians time-cost and comfort needs in crossing streets when they design pedestrian crossing facilities.

This study analyzed the scar-like localization in the time-average of a time-evolving wavepacket on a desymmetrized stadium billiard. When a wavepacket is launched along the orbits, it emerges on classical unstable periodic orbits as a scar in stationary states. This localization along the periodic orbit is clarified through the semiclassical approximation. It essentially originates from the same mechanism of a scar in stationary states: piling up of the contribution from the classical actions of multiply repeated passes on a primitive periodic orbit. To achieve this, several states are required in the energy range determined by the initial wavepacket.

Considering pedestrian preferences for the minimum distance, the minimum number of queuing pedestrians and the shortest estimated time, three pedestrian choice strategies of ticket gate machine are proposed. Pedestrian choice strategies of ticket gate machine are added into pedestrian simulation model which is based on cellular automata, and pedestrian choice behavior simulation model of ticket gate machine is obtained. On the platform of MATLAB simulation software, pedestrian choice behavior is simulated. Simulation results indicate that choice strategies of ticket gate machine proposed in this paper describe pedestrian choice behavior well, and it needs to consider the ratio of bidirectional pedestrian generation rate in the process of setting ticket gate machines in the bidirectional passage.

In this work, we developed a hybrid scheme for Gilson–Pickering equation by extracting advantageous features of collocation method and B-splines. Collocation method involves satisfying a differential equation to some tolerance at finite number of points and has low computational cost. The idea is to extract the superior accuracy and smoothness of B-spline functions with the low computational cost of collocation scheme. In the vision of a superficial periodic force, we obtain the quasiperiodic and chaotic behaviors of the forced Gilson–Pickering equation by perusing phase portrait technique, time series and Poincaré section. The sequel of frequency ($\omega$) of the superficial periodic force is very prime in case of transition from weakly chaotic feature to quasiperiodic feature of the forced Gilson–Pickering equation.

The present study transfers molecular dynamics (MD) in condensed matter physics to simulate human memory. In our MD model, a spatial representation of memory of an object is identified where constituent elements of the object are depicted in terms of physical particles. Learning is implemented as attractive forces between particles, which drive particles to gather gradually together and form closely packed clusters eventually. With this, the robustness of the memory is elucidated by the total distance between particles within the cluster. Commonly, a well-established memory of an object corresponds to a cluster with small inter-particle distances. As a demonstration, the present MD model captures a set of interference effects, including retroactive interference, proactive interference and interference between concurrently learned materials that are similar to each other. Different from the existing computational models, our MD model, relying essentially on only one parameter of the force between particles, may be useful to simulate and understand diverse phenomena associated with memory and learning.