894 resultados para kirkwood superposition approximation


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Size-uniform Si nanodots (NDs) are synthesized on an AlN buffer layer at low Si(111) substrate temperatures using inductively coupled plasma-assisted magnetron sputtering deposition. High-resolution electron microscopy reveals that the sizes of the Si NDs range from 9 to 30 nm. Room-temperature photoluminescence (PL) spectra indicate that the energy peak shifts from 738 to 778 nm with increasing the ND size. In this system, the quantum confinement effect is fairly strong even for relatively large (up to 25 nm in diameter) NDs, which is promising for the development of the next-generation all-Si tandem solar cells capable of effectively capturing sunlight photons with the energies between 1.7 (infrared: large NDs) and 3.4 eV (ultraviolet: small NDs). The strength of the resulting electron confinement in the Si/AlN ND system is evaluated and justified by analyzing the measured PL spectra using the ionization energy theory approximation.

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The charge of an isolated dust grain and ion drag forces on the grain in a collisionless, high-voltage, capacitive rf sheath are studied theoretically. The studies are carried out assuming that the positive ions are monoenergetic, as well as in more realistic approximation, assuming that the time-averaged energy distribution of ions impinging on the dust grain has a double-peaked hollow profile. For the nonmonoenergetic case, an analytical expression for the ion flux to the dust grain is obtained. It is studied how the dust charge and ion drag forces depend on the rf frequency, electron density at plasma-sheath boundary, electron temperature and ratio of the effective oscillation amplitude of rf current to the electron Debye length. It is shown that the dust charge and ion drag forces obtained in the monoenergetic ion approximation may differ from those calculated assuming that the ions are nonmonoenergetic. The difference increases with increasing the width of the ion energy spread in the ion distribution. © 2009 American Institute of Physics.

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The effect of ambipolar fluxes on nanoparticle charging in a typical low-pressure parallel-plate glow discharge is considered. It is shown that the equilibrium values of the nanoparticle charge in the plasma bulk and near-electrode areas are strongly affected by the ratio S ath i of the ambipolar flux and the ion thermal velocities. Under typical experimental conditions the above ratio is neither S ath i≪ 1 nor S ath i≫1, which often renders the commonly used approximations of the purely thermal or "ion wind" ion charging currents inaccurate. By using the general approximation for the ambipolar drift-affected ion flux on the nanoparticle surface, it appears possible to obtain more accurate values of the nanoparticle charge that usually deviate within 10-25 % from the values obtained without a proper accounting for the ambipolar ion fluxes. The implications of the results obtained for glow discharge modeling and nanoparticle manipulation in low-pressure plasmas are discussed.

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The self-modulation process of a high-frequency surface wave (SW) in a wave-guiding structure - a semibounded magnetoactive plasma and perfectly conducting metal wall - is considered for the weak nonlinearity approximation. Estimates are given for the contributions to the nonlinear frequency shift of the SW from the two principal self-action channels: via the generation of a signal of the doubled frequency and of static surface perturbations, arising as the result of the action of a ponderomotive force. Solutions for the field envelope of the nonlinear wave are examined with regard to their stability with respect to longitudinal and transverse perturbations.

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The results of a study on the influence of the nonparabolicity of the free carriers dispersion law on the propagation of surface polaritons (SPs) located near the interface between an n-type semiconductor and a metal arc reported. The semiconductor plasma is assumed to be warm and nonisothermal. The nonparabolicity of the electron dispersion law has two effects. The first one is associated with nonlinear self-interaction of the SPs. The nonlinear dispersion equation and the nonlinear Schrodinger equation for the amplitude of the SP envelope are obtained. The nonlinear evolution of the SP is studied on the base of the above mentioned equations. The second effect results in third harmonics generation. Analysis shows that these third harmonics may appear as a pure surface polariton, a pseudosurface polariton, or a superposition of a volume wave and a SP depending on the wave frequency, electron density and lattice dielectric constant.

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The nonlinear effect of hf surface waves self-interaction in a magnetoactive planar plasma waveguide is studies. The waveguide structure under consideration can be formed by gaseous or semiconducting homogeneous plasma, which is limited by a perfectly conducting metal surface. The surface (localized near the surface) wave perturbations propagating on the plasma-metal boundary perpendicular to the constant external magnetic field, are investigated. The nonlinear frequency shift connected with interaction of the second harmonic and static surface perturbations with the main frequency wave, is determined using the approximation of weak nonlinearity. It is shown that the process of double-frequency signal generation is the dissipative one as a result of bulk wave excitation on the surface wave second harmonic.

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In approximation of weak heating influence of electron heating in the high-frequency surface wave field on propagation of surface wave (heating nonlinearity) is considered. It is shown that high-frequency surface wave propagates in direction perpendicular to the external magnetic field at the semiconductor-metal interface. A nonlinear dispersion equation is obtained and studied that allows to make conclusions about the contribution of heating nonlinearity to nonlinear process of considered interaction.

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The results of theoretical investigations of two-channel waveguide modulator based on Surface Wave (SW) propagation are presented. The structure studied consists of two n-type semiconductor waveguide channels separated from each other by a dielectric gap and coated by a metal. The SW propagates at the semiconductor-metal interface across an external magnetic field which is parallel to the interface. An external dc voltage is applied to the metal surface of one channel to provide a small phase shift between two propagating modes. In a coupled mode approximation, two possible regimes of operation of the structure, namely as a directional coupler and as an electro-optical modulator, are considered. Our results suggest new applications in millimeter and submillimeter wave solid-state electronics and integrated optics.

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We examine the effect of a kinetic undercooling condition on the evolution of a free boundary in Hele--Shaw flow, in both bubble and channel geometries. We present analytical and numerical evidence that the bubble boundary is unstable and may develop one or more corners in finite time, for both expansion and contraction cases. This loss of regularity is interesting because it occurs regardless of whether the less viscous fluid is displacing the more viscous fluid, or vice versa. We show that small contracting bubbles are described to leading order by a well-studied geometric flow rule. Exact solutions to this asymptotic problem continue past the corner formation until the bubble contracts to a point as a slit in the limit. Lastly, we consider the evolving boundary with kinetic undercooling in a Saffman--Taylor channel geometry. The boundary may either form corners in finite time, or evolve to a single long finger travelling at constant speed, depending on the strength of kinetic undercooling. We demonstrate these two different behaviours numerically. For the travelling finger, we present results of a numerical solution method similar to that used to demonstrate the selection of discrete fingers by surface tension. With kinetic undercooling, a continuum of corner-free travelling fingers exists for any finger width above a critical value, which goes to zero as the kinetic undercooling vanishes. We have not been able to compute the discrete family of analytic solutions, predicted by previous asymptotic analysis, because the numerical scheme cannot distinguish between solutions characterised by analytic fingers and those which are corner-free but non-analytic.

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In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0⩽tapproximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.

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In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0 ≤ t < u ≤ n. The idea behind the Micali-Sidney scheme is to generate and distribute secret seeds S = s1, . . . , sd of a poly-random collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where f s i (·)’s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali-Sidney scheme is a special case of this general construction.We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.

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Bayesian experimental design is a fast growing area of research with many real-world applications. As computational power has increased over the years, so has the development of simulation-based design methods, which involve a number of algorithms, such as Markov chain Monte Carlo, sequential Monte Carlo and approximate Bayes methods, facilitating more complex design problems to be solved. The Bayesian framework provides a unified approach for incorporating prior information and/or uncertainties regarding the statistical model with a utility function which describes the experimental aims. In this paper, we provide a general overview on the concepts involved in Bayesian experimental design, and focus on describing some of the more commonly used Bayesian utility functions and methods for their estimation, as well as a number of algorithms that are used to search over the design space to find the Bayesian optimal design. We also discuss other computational strategies for further research in Bayesian optimal design.

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Thin plate spline finite element methods are used to fit a surface to an irregularly scattered dataset [S. Roberts, M. Hegland, and I. Altas. Approximation of a Thin Plate Spline Smoother using Continuous Piecewise Polynomial Functions. SIAM, 1:208--234, 2003]. The computational bottleneck for this algorithm is the solution of large, ill-conditioned systems of linear equations at each step of a generalised cross validation algorithm. Preconditioning techniques are investigated to accelerate the convergence of the solution of these systems using Krylov subspace methods. The preconditioners under consideration are block diagonal, block triangular and constraint preconditioners [M. Benzi, G. H. Golub, and J. Liesen. Numerical solution of saddle point problems. Acta Numer., 14:1--137, 2005]. The effectiveness of each of these preconditioners is examined on a sample dataset taken from a known surface. From our numerical investigation, constraint preconditioners appear to provide improved convergence for this surface fitting problem compared to block preconditioners.

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The foliage of a plant performs vital functions. As such, leaf models are required to be developed for modelling the plant architecture from a set of scattered data captured using a scanning device. The leaf model can be used for purely visual purposes or as part of a further model, such as a fluid movement model or biological process. For these reasons, an accurate mathematical representation of the surface and boundary is required. This paper compares three approaches for fitting a continuously differentiable surface through a set of scanned data points from a leaf surface, with a technique already used for reconstructing leaf surfaces. The techniques which will be considered are discrete smoothing D2-splines [R. Arcangeli, M. C. Lopez de Silanes, and J. J. Torrens, Multidimensional Minimising Splines, Springer, 2004.], the thin plate spline finite element smoother [S. Roberts, M. Hegland, and I. Altas, Approximation of a Thin Plate Spline Smoother using Continuous Piecewise Polynomial Functions, SIAM, 1 (2003), pp. 208--234] and the radial basis function Clough-Tocher method [M. Oqielat, I. Turner, and J. Belward, A hybrid Clough-Tocher method for surface fitting with application to leaf data., Appl. Math. Modelling, 33 (2009), pp. 2582-2595]. Numerical results show that discrete smoothing D2-splines produce reconstructed leaf surfaces which better represent the original physical leaf.

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We consider a discrete agent-based model on a one-dimensional lattice, where each agent occupies L sites and attempts movements over a distance of d lattice sites. Agents obey a strict simple exclusion rule. A discrete-time master equation is derived using a mean-field approximation and careful probability arguments. In the continuum limit, nonlinear diffusion equations that describe the average agent occupancy are obtained. Averaged discrete simulation data are generated and shown to compare very well with the solution to the derived nonlinear diffusion equations. This framework allows us to approach a lattice-free result using all the advantages of lattice methods. Since different cell types have different shapes and speeds of movement, this work offers insight into population-level behavior of collective cellular motion.