International Journal of Modern Physics C

Capital usually leads to income and income is more accurately and easily measured. Thus, we summarize income distributions in USA, Germany, etc.

In real urban traffic, roadways are usually multilane with lane-specific velocity limits. Most previous researches are derived from single-lane car-following theory which in the past years has been extensively investigated and applied. In this paper, we extend the continuous single-lane car-following model (full velocity difference model) to simulate the three-lane-changing behavior on an urban roadway which consists of three lanes. To meet incentive and security requirements, a comprehensive lane-changing rule set is constructed, taking safety distance and velocity difference into consideration and setting lane-specific speed restriction for each lane. We also investigate the effect of lane-changing behavior on distribution of cars, velocity, headway, fundamental diagram of traffic and energy dissipation. Simulation results have demonstrated asymmetric lane-changing “attraction” on changeable lane-specific speed-limited roadway, which leads to dramatically increasing energy dissipation.

Using numerical simulations of the time-dependent Schrödinger equation, we study the full quantum dynamics of the motion of an atomic ion in a linear Paul trap. Such a trap is based on a time-varying, periodic electric field and hence corresponds to a time-dependent potential for the ion, which we model exactly. We compare the center-of-mass motion with that obtained from classical equations of motion, as well as to results based on a time-independent effective potential. We also study the oscillations of the width of the ion’s wave packet, including close to the border between stable (bounded) and unstable (unbounded) trajectories. Our results confirm that the center-of-mass motion always follows the classical trajectory, that the width of the wave packet is bounded for trapping within the stability region, and therefore that the classical trapping criterion is fully applicable to quantum motion.

We study transport dynamics of quantum systems with long-range steps on the Watts–Strogatz network (WSN) which is generated by rewiring links of the regular ring. First, we probe physical systems modeled by the discrete nonlinear schrödinger (DNLS) equation. Using the localized initial condition, we compute the time-averaged occupation probability of the initial site, which is related to the nonlinearity, the long-range steps and rewiring links. Self-trapping transitions occur at large (small) nonlinear parameters for coupling $ϵ=-1$ (1), as long-range interactions are intensified. The structure disorder induced by random rewiring, however, has dual effects for $ϵ=-1$ and inhibits the self-trapping behavior for $ϵ=1$. Second, we investigate continuous-time quantum walks (CTQW) on the regular ring ruled by the discrete linear schrödinger (DLS) equation. It is found that only the presence of the long-range steps does not affect the efficiency of the coherent exciton transport, while only the allowance of random rewiring enhances the partial localization. If both factors are considered simultaneously, localization is greatly strengthened, and the transport becomes worse.

We investigate the inactive–active phase transition in an array of additive (exclusive-or) cellular automata (CA) under noise. The model is closely related with the Domany-Kinzel (DK) probabilistic cellular automaton (PCA), for which there are rigorous as well as numerical estimates on the transition probabilities. Here, we characterize the critical behavior of the noisy additive cellular automaton by mean field analysis and finite-size scaling and show that its phase transition belongs to the directed percolation universality class of critical behavior. As a by-product of our analysis, we argue that the critical behavior of the noisy elementary CA 90 and 102 (in Wolfram’s enumeration scheme) must be the same. We also perform an empirical investigation of the mean field equations to assess their quality and find that away from the critical point (but not necessarily very far away) the mean field approximations provide a reasonably good description of the dynamics of the PCA.

Computational modeling plays an important role in biology and medicine to assess the effects of hemodynamic alterations in the onset and development of vascular pathologies. Synthetic analytic indices are of primary importance for a reliable and effective a priori identification of the risk. In this scenario, we propose a multiscale fluid-structure interaction (FSI) modeling approach of hemodynamic flows, extending the recently introduced three-band decomposition (TBD) analysis for moving domains. A quantitative comparison is performed with respect to the most common hemodynamic risk indicators in a systematic manner. We demonstrate the reliability of the TBD methodology also for deformable domains by assuming a hyperelastic formulation of the arterial wall and a Newtonian approximation of the blood flow. Numerical simulations are performed for physiologic and pathologic axially symmetric geometry models with particular attention to abdominal aortic aneurysms (AAAs). Risk assessment, limitations and perspectives are finally discussed.

On the basis of one-lane comfortable driving model, this paper established a two-lane traffic cellular automata model, which improves the slow randomization effected by brake light. Considering the driver psychological characteristics and mixed traffic, we studied the lateral influence between vehicles on adjacent lanes. Through computer simulation, the space-time diagram and the fundamental figure under different conditions are obtained. The study found that aggressive driver makes a slight congestion in low-density traffic and improves the capacity of high-density traffic, when the density exceeds 20pcu/km the more aggressive drivers the greater the flow, when the density below 40pcu/km driver character makes an effect, the more cautious driver, the lower the flow. The ratio of big cars has the same effect as the ratio of aggressive drivers. Brake lights have the greatest impact on traffic flow and when the density exceeds 10pcu/km the traffic flow fluctuates. Under periodic boundary conditions, the disturbance of road length on traffic is minimal. The lateral influence only play a limited role in the medium-density conditions, and only affect the average speed of traffic at low density.

In this paper, we have studied the power spectra of the entire particle occupancy in the totally asymmetric exclusion processes on lattices with a junction, at which two lanes I and II merge into lane III. We have performed the investigations, utilizing both Monte Carlo simulations and theoretical analysis based on linearized Langevin equations. The effect of lane length, particle entry rates at lanes I and II, and particle exit rate at lane III have been discussed. The transition from damped periodic oscillation to irregular oscillation as well as disappearance of oscillation has been observed. In particular, when lanes I, II, III are simultaneously in low density (LD) state or high density (HD) state, and the length $L_1$ of lane I is not remarkably different from the length $L_2$ of lane II, the damped periodic oscillations could be observed and the minima of the power spectra could be calculated via weighted average. However, when $L_1$ is notably different from $L_2$, the oscillation becomes irregular.

We propose a simple preferential attachment model of growing network using the complementary probability of Barabási–Albert (BA) model, i.e. $\mathrm{\Pi }(k_i)\propto 1-\frac{k_i}{{\sum }_j{k}_j}$. In this network, new nodes are preferentially attached to not well connected nodes. Numerical simulations, in perfect agreement with the master equation solution, give an exponential degree distribution. This suggests that the power law degree distribution is a consequence of preferential attachment probability together with “rich get richer” phenomena. We also calculate the average degree of a target node at time t$(〈k_s(t)〉)$ and its fluctuations, to have a better view of the microscopic evolution of the network, and we also compare the results with BA model.

We study the structure of fermionic networks, i.e. a model of networks based on the behavior of fermionic gases, and we analyze dynamical processes over them. In this model, particle dynamics have been mapped to the domain of networks, hence a parameter representing the temperature controls the evolution of the system. In doing so, it is possible to generate adaptive networks, i.e. networks whose structure varies over time. As shown in previous works, networks generated by quantum statistics can undergo critical phenomena as phase transitions and, moreover, they can be considered as thermodynamic systems. In this study, we analyze fermionic networks and opinion dynamics processes over them, framing this network model as a computational model useful to represent complex and adaptive systems. Results highlight that a strong relation holds between the gas temperature and the structure of the achieved networks. Notably, both the degree distribution and the assortativity vary as the temperature varies, hence we can state that fermionic networks behave as adaptive networks. On the other hand, it is worth to highlight that we did not finding relation between outcomes of opinion dynamics processes and the gas temperature. Therefore, although the latter plays a fundamental role in gas dynamics, on the network domain, its importance is related only to structural properties of fermionic networks.

Coherent effects of ultra-relativistic particles in crystals is an area of science under development. DYNECHARM + + is a toolkit for the simulation of coherent interactions between high-energy charged particles and complex crystal structures. The particle trajectory in a crystal is computed through numerical integration of the equation of motion. The code was revised and improved in order to exploit parallelization on multi-cores and vectorization of single instructions on multiple data. An Intel Xeon Phi card was adopted for the performance measurements. The computation time was proved to scale linearly as a function of the number of physical and virtual cores. By enabling the auto-vectorization flag of the compiler a three time speedup was obtained. The performances of the card were compared to the Dual Xeon ones.

In this paper, we propose a single-lane cellular automata (CA) traffic model which takes into account the disorder in the length and the maximal speed of the vehicles (i.e. slow and fast) to study the satisfaction rate of the fast vehicles (i.e. the number of vehicles that run with their desired speed) with open boundary conditions in the case of a chain of one entry; where $\alpha$ is the injecting rate of vehicles independent of their nature and $\beta$ is the extracting rate. The slow vehicles are injected with the conditional probability ${\alpha }_s$, where $0\le {\alpha }_s=\chi \alpha \le \alpha$ and $\chi$ is the concentration of the slow vehicles. It is found that for the low value of the injecting rate $\alpha$ and for the high extraction rate $\beta$, the satisfaction rate takes higher values. It also depends on the concentration of the slow vehicles injected on the road. Furthermore, we have shown that, in the case when $\alpha =\beta$, the satisfaction rate undergoes a transition from the maximal value to the minimal one and it takes a value near to zero in the case of $\alpha >\beta$. We have also found that the satisfaction rate depends strongly on the probability of overtaking, also the phase diagrams ($\alpha ,\beta$) are established for the different values of the slow vehicles concentrations $\chi$.