International Journal of Modern Physics C

Interaction dynamics induced by finite-capacity effect is a typical diffusion model on networks. Although several significant properties of it like condensation have been well studied, the origin of its highly nonlinear complexity, influenced by complex structure and interactive behavior, is still missing. Aimed at filling this gap, we propose entropy to quantify the complexity and exhibit its strong dependence on two coupled crucial elements of nodes, the local topology and the finite capacity. Further, the performance of interaction dynamics, efficiency function is also analyzed in terms of entropy rate and relatively promoted through routing strategy arguments supported by maximum entropy theory studies. This will play a crucial role for inference problems emerging in the field of interaction dynamics on complex networks.

We review Schmidt and Kraus decompositions in the form of singular value decomposition using operations of reshaping, vectorization and reshuffling. We use the introduced notation to analyze the correspondence between quantum states and operations with the help of Jamiołkowski isomorphism. The presented matrix reorderings allow us to obtain simple formulae for the composition of quantum channels and partial operations used in quantum information theory. To provide examples of the discussed operations, we utilize a package for the Mathematica computing system implementing basic functions used in the calculations related to quantum information theory.

The bosonic atom–molecule conversion via Feshbach resonance is investigated by a semi-analytical method. The many-particle model is used and the independent crossing approximation (ICA) is utilized in calculation. An explicit formula is obtained for the conversion efficiency. The many-particle simulation supports our formula.

This work proposes and studies the concept of Functional Data Analysis transform, applying it to the performance improving of volumetric Bouligand–Minkowski fractal descriptors. The proposed transform consists essentially in changing the descriptors originally defined in the space of the calculus of fractal dimension into the space of coefficients used in the functional data representation of these descriptors. The transformed descriptors are used here in texture classification problems. The enhancement provided by the FDA transform is measured by comparing the transformed to the original descriptors in terms of the correctness rate in the classification of well known datasets.

In the present manuscript, we introduce a finite-difference scheme to approximate solutions of the two-dimensional version of Fisher's equation from population dynamics, which is a model for which the existence of traveling-wave fronts bounded within (0,1) is a well-known fact. The method presented here is a nonstandard technique which, in the linear regime, approximates the solutions of the original model with a consistency of second order in space and first order in time. The theory of M-matrices is employed here in order to elucidate conditions under which the method is able to preserve the positivity and the boundedness of solutions. In fact, our main result establishes relatively flexible conditions under which the preservation of the positivity and the boundedness of new approximations is guaranteed. Some simulations of the propagation of a traveling-wave solution confirm the analytical results derived in this work; moreover, the experiments evince a good agreement between the numerical result and the analytical solutions.

In this paper, a new lattice model is presented with the consideration of the honk effect. The stability condition is obtained by the linear stability analysis. The modified Korteweg–de Vries (KdV) equation is derived to describe the phase transition of traffic flow through nonlinear analysis. The space is divided into three regions: the stable region, the metastable region and the unstable region, respectively. And numerical simulation is carried out to validate the analytic results. The results implied that the honk effect could stabilize traffic flow and suppress the traffic jam in lattice model of traffic flow.

A lattice Boltzmann model using upstream finite volume scheme has been employed in the investigation of bifurcation and transition of flow through suddenly-expanded channels. To enhance the stability and accuracy of simulation, a fifth-order Runge–Kutta method is used for the time-marching and upwind biasing factors based on pressure are used as flux correctors in the lattice Boltzmann equation. In the range of Reynolds numbers investigated, the laminar flow through the expansion underwent a symmetry-breaking bifurcation. The critical Reynolds number evaluated from the experiments and the simulations were compared to other values reported in the literature. Comparisons are found to be quantitatively accurate. Furthermore, the results show that the critical Reynolds number decreases with increasing channel expansion ratio. At a fixed supercritical Reynolds number, the location at which the jet first impinges on the channel wall grows with the expansion ratio.

The stochastic optimal velocity (SOV) model, which is a cellular automata model, has been widely used because of its good reproducibility of the fundamental diagram, despite its simplicity. However, it has a drawback: in SOV, a vehicle that is temporarily stopped takes a long time to restart. This study proposes a revised SOV model that suppresses this particular defect; the basic concept of this model is derived from the car-following model, which considers the velocity gap between a particular vehicle and the preceding vehicle. A series of simulations identifies the model parameters and clarifies that the proposed model can reproduce the three traffic phases: free, jam, and even synchronized phases, which cannot be achieved by the conventional SOV model.