International Journal of Modern Physics C

We investigate the thermal quench of Ising and Potts models via Monte Carlo dynamics. We find that the local distribution of the site-site interaction energy has the same form as in the equilibrium case, a result that allows us to define an instantaneous temperature θ during the systems relaxation. We also find that, after an undercritical quench, θ equals the heat bath temperature in a finite time, while the total system energy is still decreasing due to the coarsening process.

The dynamic phase transitions are studied, within a mean-field approach, in the kinetic Blume-Emery-Grifftihs model under the presence of a time varying (sinusoidal) magnetic field by using the Glauber-type stochastic dynamics and the set of the dynamic equations of motion is obtained. The behavior of the time-dependence of the order parameters and the behavior of the average order parameters in a period, which is also called the dynamic order parameters, as a function of the reduced temperature are investigated. The nature (continuous and discontinuous) of transition is characterized by studying the average order parameters in a period. The dynamic phase transition points are obtained and the phase diagrams are presented in the reduced magnetic field amplitude and reduced temperature plane. We have found that the behavior of system strongly depends on the interaction parameters and nine main different phase diagram topologies have been obtained. We also calculate the Liapunov exponents to verify the stability of the solutions and the dynamic phase transition points.

We introduce variants of the Ma-Dasgupta renormalization-group (RG) approach for random quantum spin chains, in which the energy-scale is reduced by decimation built on either perturbative or non-perturbative principles. In one non-perturbative version of the method, we require the exact invariance of the lowest gaps, while in a second class of perturbative Ma-Dasgupta techniques, different decimation rules are utilized. For the S = 1 random antiferromagnetic Heisenberg chain, both type of methods provide the same type of disorder dependent phase diagram, which is in agreement with density-matrix renormalization-group calculations and previous studies.

As computational power is increasing, molecular dynamics simulations are becoming more important in materials science, chemistry, physics, and other fields of science. We demonstrate weak and strong scaling of our classical molecular dynamics code SPaSM on Livermore's BlueGene/L architecture containing 131 072 IBM PowerPC440 processors. A maximum of 320 billion atoms have been simulated in double precision, corresponding to a cubic piece of solid copper with an edge length of 1.56 μm.

We present the results from simulation studies of evaporation of a single fluid in a capillary porous medium. Employing a three-dimensional site-bond correlated network model to represent a porous medium, namely Clashac sandstone, we analyze different aspects of the phase distribution by evaporation of a single fluid in the porous medium. As a direct consequence of the porous medium utilized, we analyze the influence of a strongly disordered porous media with a broad range of pore and throat size distributions in the evaporation process. Experimental data togheter with throat and pore size distributions were used to build and match the network model, allowing us to determine the porosimetric curve for the Clashac sandstone for different degrees of correlation. Also, the correlation length was obtained from the percolation theory. In our case study the evaporation process modeled was insensitive to the different degrees of correlation that might occur between pores and throats. In addition, it was observed that the evaporation pattern was the same for all analyzed networks above the correlation length.

Bak, Tang, and Wiesenfeld [Phys. Rev. Lett.59, 381 (1987)] introduced their sand-pile (BTW sand-pile) as the cellular automata coming to their critical state without tuning any inner model parameters. The main model features deal with grains falling slowly onto the two-dimensional lattice and a quick deterministic transport of the superfluous grains to the boundary. The simplest modifications of the BTW sand-pile develop a random transport mechanism instead of a deterministic one. The model transportation of the grains generates avalanches. We find that before the big avalanches the height of the pile increases and the singular grains organize themselves in special clusters. These observations lead to the formal algorithm that predicts the big avalanches in advance with a certain efficiency. However the efficiency for the BTW sand-pile is worse than that for its stochastic modifications.

This paper presents the results of a modification of well known simple model of social phenomena called Sznajd Model. Although this model has been extensively studied and applied to different topologies I am going to show the influence of slight randomization introduced into the most basic one-dimensional approach. The modification leads to a drastic increase of time needed to reach one of the steady states and to the stabilization of lifetime of governments.

This paper treats the opinion dynamics of an unequal, initial opinion distribution. We simulate the Deffuant model on a directed Barabási–Albert network with discrete opinions and several subjects. We notice a focusing of the the resulting opinion distribution during the simulation towards the average value of the initial opinion distribution. A small change of the focusing is seen. A dependency of this change on the number of subjects and opinions is detected and indicates the change as a consequence of discretization of the opinions. Hereby the average value of the initial opinion distribution can be identified as the guide of opinion forming.

We explore the statistical laws behind the plurality voting system by investigating the election results for the mayor in Brazil in 2004. Our analysis indicate that the vote partition among mayor candidates of the same city tends to be "polarized" between two candidates, a phenomenon that can be closely described by means of a simple fragmentation model. Complex concepts like "government continuity" and "useful vote" can be identified and even statistically quantified through our approach.

Many real networks are embedded in a metric space: the interactions among individuals depend on their spatial distances and usually take place among their nearest neighbors. In this paper, we introduce a modified susceptible-infected-susceptible (SIS) model to study geographical effects on the spread of diseases by assuming that the probability of a healthy individual infected by an infectious one is inversely proportional to the Euclidean distance between them. It is found that geography plays a more important role than hubs in disease spreading: the more geographically constrained the network is, the more highly the epidemic prevails.

We have modified the Penna standard sexual model in such a way, that the state of each individual has been determined by the individual fluctuation and the fluctuation of the environment. If the sum of both fluctuations is higher than the assumed limit, the organism dies. Additionally, the individuals can learn the trends of the environment's fluctuations, diminishing their deleterious effects. This mechanism leads to the higher mortality of the youngest individuals and the lowest mortality of individuals just before reaching the minimum reproduction age. These phenomena are observed in any mortality curve describing the age structures of human populations.

The dynamical behavior of the Korean treasury bond (KTB) futures is investigated using a modified rescaled range (R/S) analysis. Lo's modified R/S analysis as well as classical Hurst's R/S statistics are utilized in order to analyze tick data of KTB futures. The Hurst exponent can be estimated by both classical and modified R/S statistics. The results of this study show that a series of returns has larger long-term correlation as the time lag increases. The Hurst exponent that shows a memory effect for the tick data of KTB futures is larger than 0.5, while the Hurst exponent has a value of nearly 0.5 for the corresponding shuffled data.