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We study the influence of ripple waves originating from the electromechanical effects on spin relaxation caused by electromagnetic fields in armchair and zigzag graphene nanoribbons (GNRs). By utilizing analytical expressions supported by numerical simulations, we show that it is possible to tune the spin flip behaviors ON and OFF due to ripple waves in GNRs for potential applications in straintronic devices. This finding is similar to recently made observations on the design of spintronic devices in III-V semiconductor quantum dots, where the sign change in the effective Land$\mathrm{\acute{e}}$ $g$-factor can be engineered with the application of gate controlled electric fields. In particular, we show that the tuning of spin extends to larger widths for the armchair GNRs than for the zigzag GNRs. Here we also report that the relaxation rate vanishes like $L^5$., Comment: 8 pages and 7 figures

The Applied Mathematics, Modelling, and Computational Science (AMMCS) conference aims to promote interdisciplinary research and collaboration. The contributions in this volume cover the latest research in mathematical and computational sciences, modeling, and simulation as well as their applications in natural and social sciences, engineering and technology, industry, and finance. The 2013 conference, the second in a series of AMMCS meetings, was held August 26–30 and organized in cooperation with AIMS and SIAM, with support from the Fields Institute in Toronto, and Wilfrid Laurier University. There were many young scientists at AMMCS-2013, both as presenters and as organizers. This proceedings contains refereed papers contributed by the participants of the AMMCS-2013 after the conference. This volume is suitable for researchers and graduate students, mathematicians and engineers, industrialists, and anyone who would like to delve into the interdisciplinary research of applied and computational mathematics and its areas of applications.

In this paper, a detailed analysis of anisotropic effects on the phonon induced spin relaxation rate in III-V semiconductor quantum dots (QDs) is carried out. We show that the accidental degeneracy due to level crossing between the first and second excited states of opposite electron spin states in both isotropic and anisotropic QDs can be manipulated with the application of externally applied gate potentials. In particular, anisotropic gate potentials enhance the phonon mediated spin-flip rate and reduce the cusp-like structure to lower magnetic fields, in addition to the lower QDs radii in III-V semiconductor QDs. In InAs QDs, only the Rashba spin-orbit coupling contributes to the phonon induced spin relaxation rate. However, for GaAs QDs, the Rashba spin-orbit coupling has a contribution near the accidental degeneracy point and the Dresselhaus spin-orbit coupling has a contribution below and above the accidental degeneracy point in the manipulation of phonon induced spin relaxation rates in QDs., Comment: 7 pages, 5 figures

Modern applications require a robust and theoretically strong tool for the realistic modeling of electronic states in low dimensional nanostructures. The $k \cdot p$ theory has fruitfully served this role for the long time since its creation. During last two decades several problems have been detected in connection with the application of the $k \cdot p$ approach to such nanostructures. These problems are closely related to the violation of the ellipticity conditions for the underlying system, the fact that until recently has been largely overlooked. We demonstrate that in many cases the models derived by a formal application of the Luttinger-Kohn theory fail to satisfy the ellipticity requirements. The detailed analysis, presented here on an example of the $6 \times 6$ Hamiltonians, shows that this failure has a strong impact on the physically important properties conventionally studied with these models., 1 figure in PDF-3D format

We study the variation in the Land$\acute{\text{e}}$ g-factor of electron spins induced by both anisotropic gate potentials and magnetic fields in InAs quantum dots for possible implementation towards solid state quantum computing. In this paper, we present analytical expressions and numerical simulations of the variation in the Land$\acute{\text{e}}$ g-factor for both isotropic and anisotropic quantum dots. Using both analytical techniques and numerical simulations, we show that the Rashba spin-orbit coupling has a major contribution in the variation of the g-factor with electric fields before the regime, where level crossing or anticrossing occurs. In particular, the electric field tunability is shown to cover a wide range of g-factor through strong Rashba spin-orbit interaction. Another major result of this paper is that the anisotropic gate potential gives quenching effect in the orbital angular momentum that reduces the variation in the E-field and B-field tunability of the g-factor if the area of the symmetric and asymmetric quantum dots is held constant. We identify level crossings and anticrossings of the electron states in the variation of the Land$\acute{\text{e}}$ g-factor. We model the wavefunctions of electron spins and estimate the size of the anticrossing for the spin states $|0,-1,+1/2>$ and $|0,0,-1/2>$ corresponding to a quantum dot that has been recently studied experimentally (Phys. Rev. Lett. \textbf{104}, 246801 (2010))., 9 pages and 8 figures

The synthesis of dsRNA is analyzed using a pathway model with amplifications caused by the aberrant RNAs. The transgene influx rate is assumed time-decaying considering the fact that the number of transgenes can not be infinite. The dynamics of the transgene induced RNA silencing is investigated using a system of coupled nonautonomous ordinary nonlinear differential equations which describe the model phenomenologically. The silencing phenomena are detected after a period of transcription. Important contributions of certain parameters are discussed with several numerical examples.

The results of Brownian dynamics simulations of a single DNA molecule in shear flow are presented taking into account the effect of internal viscosity. The dissipative mechanism of internal viscosity is proved necessary in the research of DNA dynamics. A stochastic model is derived on the basis of the balance equation for forces acting on the chain. The Euler method is applied to the solution of the model. The extensions of DNA molecules for different Weissenberg numbers are analyzed. Comparison with the experimental results available in the literature is carried out to estimate the contribution of the effect of internal viscosity., Keywords: effect of internal viscosity, dumbbell model, Brownian dynamics, DNA molecules in shear flow

The first passage time (FPT) problem is ubiquitous in many applications. In finance, we often have to deal with stochastic processes with jump-diffusion, so that the FTP problem is reducible to a stochastic differential equation with jump-diffusion. While the application of the conventional Monte-Carlo procedure is possible for the solution of the resulting model, it becomes computationally inefficient which severely restricts its applicability in many practically interesting cases. In this contribution, we focus on the development of efficient Monte-Carlo-based computational procedures for solving the FPT problem under the multivariate (and correlated) jump-diffusion processes. We also discuss the implementation of the developed Monte-Carlo-based technique for multivariate jump-diffusion processes driving by several compound Poisson shocks. Finally, we demonstrate the application of the developed methodologies for analyzing the default rates and default correlations of differently rated firms via historical data., Keywords: Default Correlation, First Passage Time, Multivariate Jump-Diffusion Processes, Monte-Carlo Simulation, Multivariate Uniform Sampling Method

In this paper, phase combinations among martensitic variants in shape memory alloys patches and bars are simulated by a hybrid optimization methodology. The mathematical model is based on the Landau theory of phase transformations. Each stable phase is associated with a local minimum of the free energy function, and the phase combinations are simulated by minimizing the bulk energy. At low temperature, the free energy function has double potential wells leading to non-convexity of the optimization problem. The methodology proposed in the present paper is based on an initial estimate of the global solution by a genetic algorithm, followed by a refined quasi-Newton procedure to locally refine the optimum. By combining the local and global search algorithms, the phase combinations are successfully simulated. Numerical experiments are presented for the phase combinations in a SMA patch under several typical mechanical loadings., Keywords: phase combinations, shape memory alloys, variational problem, genetic algorithm, quasi-Newton methods

The ``first passage-time'' (FPT) problem is an important problem with a wide range of applications in mathematics, physics, biology and finance. Mathematically, such a problem can be reduced to estimating the probability of a (stochastic) process first to reach a critical level or threshold. While in other areas of applications the FPT problem can often be solved analytically, in finance we usually have to resort to the application of numerical procedures, in particular when we deal with jump-diffusion stochastic processes (JDP). In this paper, we develop a Monte-Carlo-based methodology for the solution of the FPT problem in the context of a multivariate jump-diffusion stochastic process. The developed methodology is tested by using different parameters, the simulation results indicate that the developed methodology is much more efficient than the conventional Monte Carlo method. It is an efficient tool for further practical applications, such as the analysis of default correlation and predicting barrier options in finance., Keywords: Monte-Carlo simulations, first passage time, multivariate jump-diffusion process; 10 pages, 3 figures

Evaluation of default correlation is an important task in credit risk analysis. In many practical situations, it concerns the joint defaults of several correlated firms, the task that is reducible to a first passage time (FPT) problem. This task represents a great challenge for jump-diffusion processes (JDP), where except for very basic cases, there are no analytical solutions for such problems. In this contribution, we generalize our previous fast Monte-Carlo method (non-correlated jump-diffusion cases) for multivariate (and correlated) jump-diffusion processes. This generalization allows us, among other things, to evaluate the default events of several correlated assets based on a set of empirical data. The developed technique is an efficient tool for a number of other applications, including credit risk and option pricing., Keywords: Default correlation, First passage time problem, Monte Carlo simulation

Many problems in finance require the information on the first passage time (FPT) of a stochastic process. Mathematically, such problems are often reduced to the evaluation of the probability density of the time for such a process to cross a certain level, a boundary, or to enter a certain region. While in other areas of applications the FPT problem can often be solved analytically, in finance we usually have to resort to the application of numerical procedures, in particular when we deal with jump-diffusion stochastic processes (JDP). In this paper, we propose a Monte-Carlo-based methodology for the solution of the first passage time problem in the context of multivariate (and correlated) jump-diffusion processes. The developed technique provide an efficient tool for a number of applications, including credit risk and option pricing. We demonstrate its applicability to the analysis of the default rates and default correlations of several different, but correlated firms via a set of empirical data., Keywords: First passage time; Monte Carlo simulation; Multivariate jump-diffusion processes; Credit risk

In this paper, the finite volume method is developed to analyze coupled dynamic problems of nonlinear thermoelasticity. The major focus is given to the description of martensitic phase transformations essential in the modelling of shape memory alloys. Computational experiments are carried out to study the thermo-mechanical wave interactions in a shape memory alloy rod, and a patch. Both mechanically and thermally induced phase transformations, as well as hysteresis effects, in a one-dimensional structure are successfully simulated with the developed methodology. In the two-dimensional case, the main focus is given to square-to-rectangular transformations and examples of martensitic combinations under different mechanical loadings are provided., Keywords: shape memory alloys, phase transformations, nonlinear thermo-elasticity, finite volume method

In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of conservation law equations is proposed. This framework allows us to demonstrate an intrinsic link between microscopic and macroscopic models for evolution via the concept of perturbed generalized dynamic systems. The main result is exemplified with a number of illustrative examples where efficient numerical approximations follow directly from network-based computational models, viewed here as Markov chain approximations. Finally, stability and consistency conditions of such computational models are discussed., 21 pages, 5 figures

We demonstrate that the conventional application of linear models to the analysis of optoelectromechanical properties of nanostructures in bandstructure engineering could be inadequate. The focus of the present paper is on a model based on the coupled Schrodinger-Poisson system where we account consistently for the piezoelectric effect and analyze the influence of different nonlinear terms in strain components. The examples given in this paper show that the piezoelectric effect contributions are essential and have to be accounted for with fully coupled models. While in structural applications of piezoelectric materials at larger scales, the minimization of the full electromechanical energy is now a routine in many engineering applications, in bandstructure engineering conventional approaches are still based on linear models with minimization of uncoupled, purely elastic energy functionals with respect to displacements. Generalizations of the existing models for bandstructure calculations are presented in this paper in the context of coupled effects., 24 pages, 1 table, 15 figures

In this paper we analyze mathematically how human factors can be effectively incorporated into the analysis and control of complex systems. As an example, we focus our discussion around one of the key problems in the Intelligent Transportation Systems (ITS) theory and practice, the problem of speed control, considered here as a decision making process with limited information available. The problem is cast mathematically in the general framework of control problems and is treated in the context of dynamically changing environments where control is coupled to human-centered automation. Since in this case control might not be limited to a small number of control settings, as it is often assumed in the control literature, serious difficulties arise in the solution of this problem. We demonstrate that the problem can be reduced to a set of Hamilton-Jacobi-Bellman equations where human factors are incorporated via estimations of the system Hamiltonian. In the ITS context, these estimations can be obtained with the use of on-board equipment like sensors/receivers/actuators, in-vehicle communication devices, etc. The proposed methodology provides a way to integrate human factor into the solving process of the models for other complex dynamic systems., 19 pages

A numerical model is constructed for modelling macroscale damping effects induced by the first order martensite phase transformations in a shape memory alloy rod. The model is constructed on the basis of the modified Landau-Ginzburg theory that couples nonlinear mechanical and thermal fields. The free energy function for the model is constructed as a double well function at low temperature, such that the external energy can be absorbed during the phase transformation and converted into thermal form. The Chebyshev spectral methods are employed together with backward differentiation for the numerical analysis of the problem. Computational experiments performed for different vibration energies demonstrate the importance of taking into account damping effects induced by phase transformations., Comment: Keywords: martensite transformation, thermo-mechanical coupling, vibration damping, Ginzburg-Landau theory