International Journal of Modern Physics C

The problem of determining the state of a quantum system is a central task in any quantum information processing. However, there are limitations imposed by quantum mechanics on the possibilities to determine the state of a quantum system. For example, nonorthogonal states cannot be discriminated perfectly. In this paper, we propose a new method to calculate the inconclusive coefficients based on the solution of a quadratic system, replacing the determination of the roots of a polynomial of degree 8, used in an algorithm to quantum state discrimination previously defined in the literature. The new method simplifies the calculation of the inconclusive coefficients and can be extended very easily to any dimension. The method was written in Matlab and successfully applied to problems with different dimensions.

Finite-difference time-domain (FDTD) is a popular but computational intensive method to solve Maxwell's equations for electrical and optical devices simulation. This paper presents implementations of three-dimensional FDTD with convolutional perfect match layer (CPML) absorbing boundary conditions on graphics processing unit (GPU). Electromagnetic fields in Yee cells are calculated in parallel millions of threads arranged as a grid of blocks with compute unified device architecture (CUDA) programming model and considerable speedup factors are obtained versus sequential CPU code. We extend the parallel algorithm to multiple GPUs in order to solve electrically large structures. Asynchronous memory copy scheme is used in data exchange procedure to improve the computation efficiency. We successfully use this technique to simulate pointwise source radiation and validate the result by comparison to high precision computation, which shows favorable agreements. With four commodity GTX295 graphics cards on a single personal computer, more than 4000 million Yee cells can be updated in one second, which is hundreds of times faster than traditional CPU computation.

In this work we have used the Detrended Fluctuation Analysis (DFA) technique to investigate an oil reservoir. The system we address here is situated at Bacia de Namorados, RJ, Brazil. The data corresponds to well logs of five geophysical variables: sonic, porosity, electrical resistivity, gamma ray and density measured in 56 wells. The objective of this work is to analyze the correlation or similarity among the DFA index of several geophysical quantities. We perform a linear correlation test to compare pairs of DFA indices of the geophysical quantities for the well logs. We have not found a major similarity among the five variables which indicates an absence of correlation for these variables. Therefore, we argue that the DFA index should be used with caution in the characterization of oil reservoirs. In this way we suggest to integrate the information of DFA of several physical quantities to adequately model this kind of system.

A new general multistep predictor-corrector (PC) pair form is introduced for the numerical integration of second-order initial-value problems. Using this form, a new symmetric eight-step predictor-corrector method with minimal phase-lag and algebraic order ten is also constructed. The new method is based on the multistep symmetric method of Quinlan–Tremaine,¹ with eight steps and 8th algebraic order and is constructed to solve numerically the radial time-independent Schrödinger equation. It can also be used to integrate related IVPs with oscillating solutions such as orbital problems. We compare the new method to some recently constructed optimized methods from the literature. We measure the efficiency of the methods and conclude that the new method with minimal phase-lag is the most efficient of all the compared methods and for all the problems solved.

We present a systematic Density Functional Theory (DFT) calculations for the RgF_n(Rg = Kr,Xe; n = 2,4,6) molecules. The dissociation energies, harmonic vibrational frequencies and equilibrium bond lengths of these molecules are determined using several hybrid density functional methods. Results are compared with other theoretical studies and experimental values available. The accuracy of the DFT results is found to depend upon the functionals employed.

This paper deals with a new type of synchronization scheme for chaotic neural networks with delays, called modified function projective synchronization, in which chaotic neural networks synchronize up to a scaling function matrix. Based on the nonlinear state observer, a control scheme is derived through the placement technique by designing a state-observer of the derived system to synchronize chaotic neural networks up to a scaling function matrix. This technique, capable of adjusting the scaling function factor arbitrarily for the value of scaling function factor, has no effect on the controllability of error system. That overcomes some limitation in earlier literature. A chaotic cellular neural network and a chaotic Hopfield neural model are used as numerical examples to demonstrate the effectiveness of the proposed synchronization technique.

In this paper, we investigate two two-route traffic models, i.e. asymmetric and symmetric two-route traffic models, with mean velocity information feedback strategy. The simulation results show that, for asymmetric two-route model, average flux can be significantly improved if only partial road information is provided for road users. However, for symmetric two-route model, average flux of the two routes adopting information feedback cannot outweigh the flux of two routes chosen completely at random. We explain the results by studying the vehicle number on two routes. We hope the study may provide a good suggestion to the design of Advanced Traveler Information Systems.

Despite the rule that cyclists must ride on the right half of the road is written into the state vehicle code, the phenomenon of riding against the bicycle flow is still serious. To investigate the effect of bicycles going in the wrong direction, a Bi-Directional Adaptive EBCA model is developed in this paper. The phase transition F-J as well as the phase transition F-S-F are suggested by observing the spatial-temporal pattern. The deterministic case that the linear relationship between the average flow rate and the bicycle number disappears when the average density exceeds a particular value is shown. Under the stochastic case, the impacts of the avoiding probability Ps and the returning probability Pr on the traffic system are analyzed. The results of the simulation are in good agreement with the realistic bicycle flow.