International Journal of Modern Physics C

We study the influence of traffic lights on the traffic flow in cities. The urban traffic is simulated in the cellular automata framework. Both the deterministic and probabilistic models are discussed. The effects of speed limit and stochastic noise are analyzed. The operation of a traffic light is characterized by two parameters: signal period and phase allocation. With two traffic lights on road, one more parameter is prescribed: synchronization shift. The results of tuning these parameters are presented in the fundamental diagram. We examine the traffic flow and discuss the choice of optimized setting in different density regions.

The Rayleigh–Ritz variational method is carried out with a multiconfiguration-interaction wave function and restricted variational method to obtain the relativistic energies of the 1s²2s2p ¹P^o, 1s²2s2p ³P^o, and 1s²2p²³P states for the beryllium-like isoelectronic sequence (Z=4–10), including the mass polarization and relativistic corrections. The oscillator strengths and transition rates are also calculated. The results are compared with other theoretical and experimental data in the literature. The hyperfine structure of the low-lying excited states for this system is also explored.

In this paper the Solomon network is simulated by means of 1D and 2D Ising model with additional — not only geometrical — neighbors. A "social phase transition" at nonzero Curie-like temperature is observed, also in one dimension. The critical exponent describing the behavior of the magnetization in the vicinity of the transition is also evaluated.

The conformational transitions of the heptapeptide Deltorphin (H-Tyr¹-D-Met²-Phe³-His⁴-Leu⁵-Met⁶-Asp⁷-NH₂) are predicted by using the detailed representation of the energy landscape. The visualization of the whole rugged landscape covering the entire energy and temperature ranges is found useful for the determination of the conformational transitions and the glassy behavior of peptides.

The support vector machine (SVM) is used in the classification of sonar signals and DNA-binding proteins. Our study on the classification of sonar signals shows that SVM produces a result better than that obtained from other classification methods, which is consistent from the findings of other studies. The testing accuracy of classification is 95.19% as compared with that of 90.4% from multilayered neural network and that of 82.7% from nearest neighbor classifier. From our results on the classification of DNA-binding proteins, one finds that SVM gives a testing accuracy of 82.32%, which is slightly better than that obtained from an earlier study of SVM classification of protein–protein interactions. Hence, our study indicates the usefulness of SVM in the identification of DNA-binding proteins. Further improvements in SVM algorithm and parameters are suggested.

This paper explores the reasons as to why the quantum paradigm is not so easy to extend to all of the classical computational algorithms. We also explain the failure of programmability and scalability in quantum speed-up. Due to the presence of quantum entropy, quantum algorithm cannot obviate the curse of dimensionality encountered in solving many complex numerical and optimization problems. Finally, the stringent condition that quantum computers have to be interaction-free, leave them with little versatility and practical utility.

In this paper, a generalized extended tanh-function method for constructing exact solutions of nonlinear evolution equations (NEEs) is presented and implemented in a computer algebraic system. Applying the generalized method, with the aid of Maple, we consider the system of the approximate equations for long water waves and find the new more general explicit exact solutions. The properties of the new solitary wave solutions are shown by some figures.

The average cohesive energy of the GdMg solid solution for various composition from x=0.10 to 0.90 has been worked out by simulation at 300 K, using Monte Carlo (MC) technique and was found that at x=0.58 there is a structural phase transition. This is compared with the available experimental results and was discussed.

Monte Carlo simulations, using the PERM algorithm, of interacting self-avoiding walks (ISAW) and interacting self-avoiding trails (ISAT) in five dimensions are presented which locate the collapse phase transition in those models. It is argued that the appearance of a transition (at least) as strong as a pseudo-first-order transition occurs in both models. The values of various theoretically-conjectured dimension-dependent exponents are shown to be consistent with the data obtained. Indeed the first-order nature of the transition is even stronger in five dimensions than four. The agreement with the theory is better for ISAW than ISAT and it cannot be ruled out that ISAT have a true first-order transition in dimension five. This latter difference would be intriguing if true. On the other hand, since simulations are more difficult for ISAT than ISAW at this transition in high dimensions, any discrepancy may well be due to the inability of the simulations to reach the true asymptotic regime.

A detailed analysis on the characteristics of transitional turbulent flow over a bell-shape stenosis for a physiological pulsatile flow is presented. The comparison of the numerical solutions to three types of pulsatile flows, including a physiological flow, an equivalent pulsatile flow and a simple pulsatile flow, are made in this work. Then the effects of the Reynolds number, Womersley number and constriction ratio of stenosis on the pulsatile turbulent flow fields for the physiological flow are considered. The comparison of the three pulsatile flows shows that the flow characteristics cannot be properly estimated if an equivalent or simple pulsatile inflow is used instead of actual physiological one in the study of the pulsatile flows through arterial stenosis. The equivalent or simple pulsatile inflow can lead to higher disturbance intensity in the vicinity of the stenosis than the physiological inflow. For a physiological flow, the recirculation zones with high disturbance intensity occur mainly in the distal of the stenosis. The larger Reynolds number and severer constriction ratio may result in more complex flow field and cause some important flow variables to increase dramatically near stenosis. The higher Womersley number leads to a larger phase lag between the imposed flow rate changes and the final converged flow field in one cycle. The turbulence intensity decreases with the increase of Womersley number for the same Reynolds number.

Firstly twenty-four types of doubly-periodic solutions of the reduction mKdV equation are given. Secondly based on the reduction mKdV equation and its solutions, a systemic transformation method (called the reduction mKdV method) is developed to construct new doubly-periodic solutions of nonlinear equations. Thirdly with the aid of symbolic computation, we choose the KdV equation, the coupled variant Boussinesq equation and the cubic nonlinear Schrödinger equation to illustrate our method. As a result many types of solutions are obtained. These show that this method is simple and powerful to obtain more exact solutions including doubly-periodic solutions, soliton solutions and singly-periodic solutions to a wide class of nonlinear wave equations. Finally we further extended the method to a general form.

In computational experiments with cellular automaton models of affective solutions, where chemical species represent happiness, anger, fear, confusion and sadness, we study phenomena of space–time dynamic of emotions. We demonstrate feasibility of the affective solution paradigm in example of emotional abuse therapy. Results outlined in the present paper offer unconventional but promising technique to design, analyze and interpret spatio-temporal dynamic of mass moods in crowds.

A new and efficient algorithm is presented for the calculation of the partition function in the S=±1 Ising model. As an example, we use the algorithm to obtain the thermal-dependence of the magnetic spin susceptibility of an Ising antiferromagnet for a 8×8 square lattice with open boundary conditions. The results agree qualitatively with the prediction of the Monte Carlo simulations and the experimental data, and they are better than the mean field approach results. For the 8×8 lattice, the algorithm reduces the computation time by nine orders of magnitude.

Standard Cellular Automata (CA) are ahistoric (memoryless), i.e., the new state of a cell depends only on the neighborhood configuration at the preceding time step. This article introduces an extension of the standard framework of CA by considering automata implementing memory capabilities. While the update rules of the CA remains the same, each site remembers a weighted mean of all its past states, with a decreasing weight of states farther back in the past. The historic weighting is defined by a potential series of coefficients, t^k, k acting as a forgetting factor. This paper considers the time evolution of one-dimensional, legal CA rules with accumulative memory.