Narrow Results

We investigate the role played by conservative forces in dissipative particle dynamics (DPD) simulation of single-component and binary fluids. We employ equations from kinetic theory for matching the coefficients of DPD interparticle force to the macroscopic properties of fluid such as: density, temperature, diffusion coefficient, kinematic viscosity and sound velocity. The sound velocity c is coupled with scaling factor π₁ of conservative component of the DPD collision operator. Its value sets up an upper limit on the mass S of a single particle in DPD fluid. The Kirkwood–Alder fluid–solid transition is observed for a sufficiently large S. We emphasize the role of the scaling factor π₁₂ for particles of different types in simulating phase separation in binary fluids. The temporal growth of average domain size R(t) in the phase separation process depends on the value of immiscibility coefficient Δ = π₁₂ - π₁. For small immiscibility, R (t) ∝ t^β, where β ≈ 1/2 for R (t) < R_H and β ≈ 2/3 for R (t) > R_H, R_H is the hydrodynamic length. Finally, both phases separate out completely. For larger immiscibility, R(t) increases exponentially at the beginning of simulation, while finally the domain growth process becomes marginal. We also observe the creation of emulsion-like structures. This effect results from an increase of the surface tension on the two-phase interface along with increasing immiscibility.

In this paper the Penna bit-string model of biological aging with different lengths of bit-strings genome is considered. We show from computer simulation that changes in genome length may be crucial for determining population characterization and seem to be irreversible by scaling the other model control parameters.

In this paper we computationally investigate the magnetization for three-dimensional (3D) InAs/GaAs nanorings with different radii in an external magnetic field. Our simulation model includes: (i) the effective mass Hamiltonian in nonparabolic approximation, (ii) the position- and energy-dependent quasi-particle effective mass approximation, (iii) the finite hard wall confinement potential, and (iv) the Ben Daniel–Duke boundary conditions. The nonlinear iterative method is applied to solve the 3D problem. With the developed computer simulator, we find the magnetization for the 3D InAs/GaAs ring is a negative function and oscillates nonperiodically. The oscillation saturates when the applied magnetic filed is increased. This result provides an alternative for the nanoring energy shell structure study and is useful for spintronics applications.

A social group is represented by a graph, where each pair of nodes is connected by two oppositely directed links. At the beginning, a given amount p(i) of resources is assigned randomly to each node i. Also, each link r(i,j) is initially represented by a random positive value, which means the percentage of resources of node i which is offered to node j. Initially, the graph is fully connected, i.e., all nondiagonal matrix elements r(i,j) are different from zero. During the simulation, the amounts of resources p(i) change according to the balance equation. The nodes reorganize their activity with time to give more resources to those which give them more. This is the rule of varying the coefficients r(i,j). The result is that after some transient time, only some pairs (m,n) of nodes survive with nonzero p(m) and p(n), each pair with symmetric and positive r(m,n)=r(n,m). Other coefficients r(m,i≠n) vanish. Unpaired nodes remain with no resources, i.e., their p(i)=0, and they cease to be active as they have nothing to offer. The percentage of survivors (i.e., those with p(i) positive) increases with the velocity of varying the numbers r(i,j), and it slightly decreases with the size of the group. The picture and the results can be interpreted as a description of a social algorithm leading to marriages.

We simulate the progression of the HIV-1 infection in untreated host organisms. The phenotype features of the virus are represented by the replication rate, the probability of activating the transcription, the mutation rate and the capacity to stimulate an immune response (the so-called immunogenicity).

It is very difficult to study in-vivo or in-vitro how these characteristics of the virus influence the evolution of the disease. Therefore we resorted to simulations based on a computer model validated in previous studies.

We observe, by means of computer experiments, that the virus continuously evolves under the selective pressure of an immune response whose effectiveness downgrades along with the disease progression. The results of the simulations show that immunogenicity is the most important factor in determining the rate of disease progression but, by itself, it is not sufficient to drive the disease to a conclusion in all cases.

Science and technology have a fundamental role in the economic development. Although this statement is generally well accepted, the internal mechanisms which are responsible for these interactions are not clear. In the last decade, dealing with this problem, many models have been proposed. In this paper, we introduce a model that creates an artificial world economy that is a network of countries. Each country has its own national system of innovation and the interactions between countries are given by functions that connect the competitiveness of their prices and their technological capabilities. Starting from different configurations, the artificial world economy self-organizes itself and creates a hierarchies of countries.

In this work, we study a three-state opinion formation model considering two distinct mechanisms, namely independence and conviction. Independence is introduced in the model as a noise by means of a probability of occurrence q. On the other hand, conviction acts as a disorder in the system, and it is introduced by two discrete probability distributions. We analyze the effects of such two mechanisms on the phase transitions of the model, and we found that the critical exponents are universal over the order–disorder frontier, presenting the same universality class of the mean-field Ising model. In addition, for one of the probability distributions, the transition may be eliminated for a wide range of the parameters.

In this work, we study a model of tax evasion. We considered a fixed population divided in three compartments, namely honest tax payers, tax evaders and a third class between the mentioned two, which we call susceptibles to become evaders. The transitions among those compartments are ruled by probabilities, similarly to a model of epidemic spreading. These probabilities model social interactions among the individuals, as well as the government’s fiscalization. We simulate the model on fully-connected graphs, as well as on scale-free and random complex networks. For the fully-connected and random graph cases, we observe that the emergence of tax evaders in the population is associated with an active-absorbing nonequilibrium phase transition, that is absent in scale-free networks.

In this work, we study a simple model of social contagion that aims to represent the dynamics of social influences among politicians in an artificial corrupt parliament. We consider an agent-based model with three distinct types of artificial individuals (deputies), namely honest deputies, corrupt deputies and inflexible corrupt deputies. These last agents are committed to corruption, and they never change their state. The other two classes of agents are susceptible deputies, that can change state due to social pressure of other agents. We analyze the dynamic and stationary properties of the model as functions of the frozen density of inflexible corrupt individuals and two other parameters related to the strength of the social influences. We show that the honest individuals can disappear in the steady state, and such disappearance is related to an active-absorbing nonequilibrium phase transition that appears to be in the directed percolation universality class. We also determine the conditions leading to the survival of honesty in the long-time evolution of the system, and the regions of parameters for which the honest deputies can be the either the majority or the minority in the artificial parliament.

In this work, we study a continuous opinion dynamics model considering 3-agent interactions and group pressure. Agents interact in a fully-connected population, and two parameters govern the dynamics: the agents’ convictions $\lambda$ that are homogeneous in the population, and the group pressure $p$. Stochastic parameters also drive the interactions. Our analytical and numerical results indicate that the model undergoes symmetry-breaking transitions at distinct critical points ${\lambda }_c$ for any value of $p<p^{\ast }=2/3$, i.e. the transition can be suppressed for sufficiently high group pressure. Such transition separates two phases: for any $\lambda \le {\lambda }_c$, the order parameter $O$ is identically null ($O=0$, a symmetric, absorbing phase), while for $\lambda >{\lambda }_c$, we have $O>0$, i.e. a symmetry-broken phase (ferromagnetic). The numerical simulations also reveal that the increase of group pressure leads to a wider distribution of opinions, decreasing the extremism in the population.

In this work, we study a dynamics of tax evasion. We considered a fully-connected population divided in three compartments, namely honest tax payers, tax evaders and susceptibles, a class that is composed by honest tax payers that can become evaders. We consider a contagion model where the transitions among the compartments are governed by probabilities. Such probabilities represent the possible interactions among the individuals, as well as the government fiscalization. We show by analytical and numerical calculations that the emergence of tax evaders in the population is associated with an active-absorbing nonequilibrium first-order phase transition. In the absorbing phase, only honest tax payers survive in the steady states of the model, and we observe a coexistence of the three subpopulations in the active phase.

An example of three-dimensional animation of Monte Carlo simulation results of liquid crystal lattice models is presented. Molecular configurations are obtained from Monte Carlo simulations on a VAX cluster and downloaded to a 486 personal computer. Visualization of molecular organizations and of their change at a phase transition is obtained by suitable colour coding of orientations and of other relevant physical information on the personal computer, and recorded on a VHS system using a genlock card. The animation sequences generated have a twofold interest: they are useful for educational purposes and, from a scientific point of view, they provide a tool for exploring a large amount of data and investigating the phenomena under study in a non-numerical way.

A Monte Carlo method with boundary conditions of a self-consistent maximum entropy type has been applied to the classical Heisenberg model.

We present a Monte Carlo simulation of a model of a twisted nematic display on a lattice starting from purely microscopic interactions. We visualize the simulated display calculating optical textures under crossed polarizers corresponding to the Monte Carlo microscopic configurations. We also investigate the orientational order and the molecular organizations in the different regions of the lattice, introducing and calculating suitable order parameters.

Power laws are found in a wide range of different systems: From sand piles to word occurrence frequencies and to the size distribution of cities. The natural emergence of these power laws in so many different systems, which has been called self-organized criticality, seems rather mysterious and awaits a rigorous explanation. In this letter we study the stationary regime of a previously introduced dynamical microscopic model of the stock market. We find that the wealth distribution among investors spontaneously converges to a power law. We are able to explain this phenomenon by simple general considerations. We suggest that similar considerations may explain self-organized criticality in many other systems. They also explain the Levy distribution.

The temperature behavior of a system of dipoles with long-range interactions has been simulated via a two-dimensional lattice Monte Carlo on a massively SIMD platform (Quadrics/APE100). Thermodynamic quantities have been evaluated in order to locate and to characterize the phase transition in absence of applied field. Emphasis is given to the code implementation on the SIMD architecture and to the relevant features which have been used to improve code capabilities and performances.

The implementation of a Monte Carlo code for simulations of liquid crystal lattice models on the Quadrics massively parallel SIMD supercomputer is described. The use of a Quadrics with 512 processors is proving essential in studying the nematic–isotropic phase transition to an unprecedented level of accuracy using more than 10⁶ particles. Here some tests on the Lebwohl–Lasher model with and without an applied field are presented.

The Monte Carlo (MC) method is applied to the modeling of a liquid crystal display based on the in-plane switching effect. This is the first attempt to simulate this device features starting from purely microscopic molecular interactions. The optical textures are obtained from the Monte Carlo generated microscopic equilibrium configurations by means of a Müller matrix approach. Suitable order parameters are also calculated to quantify the ordering and the molecular organization across the display cell.

A computer simulation study of the lateral diffusion of conformationally-disordered lipid molecules in a monolayer structure is reported. The simulations were carried out with dynamic Monte Carlo methods, employing two different representations of the internal motions of the lipid chains. The results indicate that the dependence of the lateral diffusion coefficients on the density (area-per-molecule) in the monolayer is determined by the conformational behavior of the lipid chains. The classical Cohen–Turnbull theory is found to provide a good description of the simulated lateral diffusion coefficients at moderate densities. The substantial deviations found at low densities are attributed to the small density fluctuations creating the free volume needed for the lateral diffusion process.

Molecular dynamics and Monte Carlo methods are applied to study the liquid free surfaces in model liquid crystals. The simulation results suggest that the attractive interactions promote parallel alignment of the molecules at the nematic free surface in the Gay–Berne model, in agreement with theoretical predictions. A change in the orientation from planar to homeotropic is observed and explained in terms of a competing effect between attractive and repulsive interactions. Finally, the simulation results give clear evidence that the hard-core repulsions favor homeotropic orientation at the nematic free surface, in agreement with most theories.