International Journal of Modern Physics C

In this paper, we investigate two different entanglement measures, the negativity and concurrence, in the case of pure and mixed states of two-qubit system basing on the spin coherent states. For two-qubit pure states, the negativity is the same as the concurrence. For mixed states, using a simplified expression of concurrence in Wootters' measure of entanglement, we write the bounds of Verstraete et al.¹ as a function of some new parameters and we compare the both measures for a class of mixed states.

A new model for describing the disaster system including instantaneous and continuous action synchronously has been developed. The model is composed of three primary parts, that is, the impact from its causative disaster events, stochastic noise of disaster node and self-healing function, and every part is modeled concretely in terms of their characteristics in practice. Some key parameters, namely link appearance probability, retardation coefficient, ultimate repair capacity of government, dynamical modes considering different disaster evolving chains, and the positions of link with the specific performance in disaster network system are involved. Combined with a case study, the proposed model is applied to a certain disaster evolution system, and the influence law of different parameters on disaster evolution process, in disaster networks with instantaneous-action and/or continuous-action, is presented and compared. The results indicate that the destructive impact in the networks by link in continuous action is far greater an order of magnitude than that in instantaneous action. If a link in continuous action emerges in the disaster network system, properties of the causative event for the link, link appearance probability and its position in the network all have a notable influence to the severity of the disaster network. In addition, some peculiar phenomena are also commendably observed in the disaster evolution process based on the model, such as the multipeaks emerging in the destroyed rate number curve for some crisis nodes caused by their various inducing paths together with the relevant retardation coefficients, the existence of the critical value for ultimate repair capacity to recover the disaster node, and so on.

Verbal language is a dynamic mental process. Ideas emerge by means of the selection of words from subjective and individual characteristics throughout the oral discourse. The goal of this work is to characterize the complex network of word associations that emerge from an oral discourse from a discourse topic. Because of that, concepts of associative incidence and fidelity have been elaborated and represented the probability of occurrence of pairs of words in the same sentence in the whole oral discourse. Semantic network of words associations were constructed, where the words are represented as nodes and the edges are created when the incidence-fidelity index between pairs of words exceeds a numerical limit (0.001). Twelve oral discourses were studied. The networks generated from these oral discourses present a typical behavior of complex networks and their indices were calculated and their topologies characterized. The indices of these networks obtained from each incidence-fidelity limit exhibit a critical value in which the semantic network has maximum conceptual information and minimum residual associations. Semantic networks generated by this incidence-fidelity limit depict a pattern of hierarchical classes that represent the different contexts used in the oral discourse.

Molecular dynamics and Monte Carlo techniques are employed for the study of Lennard–Jones fluids near the solid–liquid transition region. Systematic comparisons between the predictions of both techniques are discussed, with particular emphasis on the structural evolution and location of the transition (melting) temperature T_m.

A novel cryptography method based on the Lorenz's attractor chaotic system is presented. The proposed algorithm is secure and fast, making it practical for general use. We introduce the chaotic operation mode, which provides an interaction among the password, message and a chaotic system. It ensures that the algorithm yields a secure codification, even if the nature of the chaotic system is known. The algorithm has been implemented in two versions: one sequential and slow and the other, parallel and fast. Our algorithm assures the integrity of the ciphertext (we know if it has been altered, which is not assured by traditional algorithms) and consequently its authenticity. Numerical experiments are presented, discussed and show the behavior of the method in terms of security and performance. The fast version of the algorithm has a performance comparable to AES, a popular cryptography program used commercially nowadays, but it is more secure, which makes it immediately suitable for general purpose cryptography applications. An internet page has been set up, which enables the readers to test the algorithm and also to try to break into the cipher.

A lattice Boltzmann model is developed for viscous compressible flows with flexible specific-heat ratio and Prandtl number. Unlike the Maxwellian distribution function or circle function used in the existing lattice Boltzmann models, a polynomial kernel function in the phase space is introduced to recover the Navier–Stokes–Fourier equations. A discrete equilibrium density distribution function and a discrete equilibrium total energy distribution function are obtained from the discretization of the polynomial kernel function with Lagrangian interpolation. The equilibrium distribution functions are then coupled via the equation of state. In this framework, a model for viscous compressible flows is proposed. Several numerical tests from subsonic to supersonic flows, including the Sod shock tube, the double Mach reflection and the thermal Couette flow, are simulated to validate the present model. In particular, the discrete Boltzmann equation with the Bhatnagar–Gross–Krook approximation is solved by the finite-difference method. Numerical results agree well with the exact or analytic solutions. The present model has potential application in the study of complex fluid systems such as thermal compressible flows.

In this paper, the traffic behavior around the weaving section, in which an on-ramp and an off-ramp are joined together by an auxiliary lane, is investigated. The drive-in vehicle should merge into the main road while the exit vehicle should diverge from the main road. The influence of those merging and diverging behavior on the dynamics of traffic around the weaving section is studied by analyzing the phase diagram in different spaces and the total flux depending on each parameter. When the number of drive-in vehicle and the number of exit vehicle are close to each other, the total flux is less disturbed. But when they have large difference, the total flux is greatly reduced. We also studied the total flux as a function of the length of the weaving section. It is shown that the weaving section should not be shorter than 150 m.

This work proposes a method for estimating the weight distribution of a network with Gauss edge weights using a time series collected from controlled measurements of the stable dynamics of the network. Comparing the weight distribution obtained using this method with that using another scheme demonstrates that the former is effective and accurate for estimating the weight distribution P(w) of coupled oscillator networks in a broad coupling strength region. This method enables the topological properties of underlying networks to be determined from only a time series of measurements because it depends on no prior information about the dynamical system. In addition, the method is rather robust against noise.

Correlation-based weighted financial networks are analyzed to present cumulative distribution of strength with a power-law tail, which suggests that a small number of hub-like stocks have greater influence on the whole fluctuation of financial market than others. The relationship between clustering and connectivity of vertices emphasizes hierarchical organization, which has been depicted by minimal span tree in previous work. These results urge us to further study the mixing patter of financial network to understand the tendency for vertices to be connected to vertices that are like (or unlike) them in some way. The measurement of average nearest-neighbor degree running over classes of vertices with degree k shows a descending trend when k increases. This interesting result is first uncovered in our work, and suggests the disassortative mixing of financial network which refers to a bias in favor of connections between dissimilar vertices. All the results in weighted complex network aspect may provide some insights to deeper understand the underlying mechanism of financial market and model the evolution of financial market.

In this paper, traffic flow at a signal controlled T-shaped intersection with three input roads is investigated by using the cellular automata model. When each road is a double lane, the model only exists in three conflict points among three directions of flows. We introduce three-phase traffic signal and two types of signal controlling strategies, i.e. fixed signal phase order as well as adaptive signal phase order strategy, to control the traffic flow at the intersection. The phase diagram, the capacity and the average travel time of the system are investigated and compared under both strategies. The simulation results show that the traffic adaptive signal strategy is better than the fixed signal phase order strategy.