Some basic remarks on eigenmode expansions of time-delay dynamics

We describe in elementary terms how eigenmode expansions can be used to deal with differential-difference equations. As particular applications we present the full analytical solution of linear stochastic time-delay systems and the weakly nonlinear analysis of nonlinear differential-difference equations in the limit of large time delay. Our exposition is essentially based on an explicit analytical expression for the linear spectrum in terms of the Lambert W-function and on the explicit formula for the eigenfunctions of the adjoint equation.     

Intermittent magnetic field excitation by a turbulent flow of liquid sodium

The magnetic field measured in the Madison dynamo experiment shows intermittent periods of growth when an axial magnetic field is applied. The geometry of the intermittent field is consistent with the fastest-growing magnetic eigenmode predicted by kinematic dynamo theory using a laminar model of the mean flow. Though the eigenmodes of the mean flow are decaying, it is postulated that turbulent fluctuations of the velocity field change the flow geometry such that the eigenmode growth rate is temporarily positive. Therefore, it is expected that a characteristic of the onset of a turbulent dynamo is magnetic intermittency.     

Chaotic regime of Alfvén Eigenmode wave-particle interaction

The chaotic regime in Alfvén eigenmode wave-particle interaction is identified for the first time in the tokamak plasma of the Joint European Torus. The Alfvén modes are driven by energetic hydrogen minority ions produced by ion cyclotron resonance heating. The experimental signatures of the chaotic regime include spectral broadening, phase flips, and nonperiodic amplitude variations. These phenomena are found to be consistent with a general nonlinear theory of kinetic instabilities near stability threshold developed by Berk, Breizman, and Pekker.     

First passage time of nonlinear ship rolling in narrow band non-stationary random seas

The generalized extended stochastic central difference (GESCD) method is applied to study the response statistics and first passage time of nonlinear ship rolling in narrow band stationary and non-stationary random seas. The GESCD method is based on a combination of the extended stochastic central difference method with a statistical linearization technique, modified adaptive time scheme, and time coordinate transformation. The extended stochastic central difference method is, however, an extension of the stochastic central difference method for the determination of the recursive mean square or covariance of responses of systems under narrow band stationary and non-stationary random disturbances. Approximate first passage probabilities of nonlinear systems based on the modified mean rate of various crossings proposed earlier by the first author were determined. It is concluded that the GESCD method is very accurate, simple and efficient to apply compared with Monte Carlo simulation. The proposed method is applicable to cases with large nonlinearities and intensive random excitations. The approximate first passage probabilities of the nonlinear system determined by the proposed approach are very accurate as they are in excellent agreement with those evaluated by the Monte Carlo simulation. It is believed that the model considered in this paper is a closer representation to reality than those reported earlier in the literature.     

Modeling of Kerr nonlinear photonic components with mode expansion

We present an efficient numerical technique to simulate the third order Kerr effect in wavelength scale dielectric structures by expanding upon the eigenmode expansion method. A two-dimensional spatial grid models the intensity dependent refractive index. By performing an iteration of linear eigenmode calculations, this index grid converges to the rigorous continuous-wave nonlinear solution. Because the underlying eigenmode tool is bidirectional, feedback effects such as bistability can be calculated. We describe the influence of grid size, quantitative agreement with the literature and a photonic crystal switch. The differences with other methods, such as finite-difference time-domain and beam propagation method, are discussed.     

Spin-wave eigenmodes of a saturated magnetic square at different precession angles

Using low-loss dielectric magnetic films in combination with space-resolved Brillouin light scattering spectroscopy we have studied nonlinear modification of eigenmode spatial distributions in saturated magnetic squares. We have found that, as the angle of magnetization precession increases, the eigenmode spatial distributions experience significant qualitative changes due to a nonlinear coupling between forming them standing spin waves. We show that the found nonlinear eigenmodes cannot be described by means of the linear theoretical approach even qualitatively.     

Nonlinear Coupling of Reversed Shear Alfvén Eigenmode and Toroidal Alfvén Eigenmode during Current Ramp

Two novel nonlinear mode coupling processes for reversed shear Alfvén eigenmode(RSAE) nonlinear saturation are proposed and investigated. In the first process, the RSAE nonlinearly couples to a co-propagating toroidal Alfvén eigenmode(TAE) with the same toroidal and poloidal mode numbers, and generates a geodesic acoustic mode. In the second process, the RSAE couples to a counter-propagating TAE and generates an ion acoustic wave quasi-mode. The condition for the two processes to occur is favored during current ramp. Both the processes contribute to effectively saturate the Alfvénic instabilities, as well as nonlinearly transfer of energy from energetic fusion alpha particles to fuel ions in burning plasmas.     

A survey of numerical methods for nonlinear filtering problems

The main goal of filtering is to obtain, recursively in time, good estimates of the state of a stochastic dynamical system based on noisy partial observations of the same. In settings where the signal/observation dynamics are significantly nonlinear or the noise intensities are high, an extended Kalman filter (EKF), which is essentially a first order approximation to an infinite dimensional problem, can perform quite poorly: it may require very frequent re-initializations and in some situations may even diverge. The theory of nonlinear filtering addresses these difficulties by considering the evolution of the conditional distribution of the state of the system given all the available observations, in the space of probability measures. We survey a variety of numerical schemes that have been developed in the literature for approximating the conditional distribution described by such stochastic evolution equations; with a special emphasis on an important family of schemes known as the particle filters. A numerical study is presented to illustrate that in settings where the signal/observation dynamics are non linear a suitably chosen nonlinear scheme can drastically outperform the extended Kalman filter.     

Multiple ionization in fast ion-atom collisions: simultaneous measurement of recoil momentum and projectile energy loss

The stability of nonlinear laser light filaments in a homogeneous isothermal plasma with respect to coupled electromagnetic and density perturbations is examined. In addition to the previously known modulational instability of a trapped electromagnetic mode, a new fast growing resonant instability is found. It corresponds to the growth of an excited eigenmode in the waveguide formed by the filament density depletion, the associated density response being supersonic and transversally localized. The evolution of the instability is illustrated by numerical simulations in two and three spatial dimensions.     

A self-consistent approach to quantum field theory for extended particles

A notion of quantum space-time is introduced, physically defined as the totality of all flows of quantum test particles in free fall. In quantum space-time the classical notion of deterministic inertial frames is replaced by that of stochastic frames marked by extended particles. The same particles are used both as markers of quantum space-time points as well as natural clocks, each species of quantum test particle thus providing a standard for space-time measurements. In the considered flat-space case, the fluctuations in coordinate values with respect to stochastic frames are described by coordinate probability amplitudes related to irreducible stochastic phase space representations of the Poincaré group. Lagrangian field theory on quantum space-time is formulated. The ensuing equations of motion for interacting fields contain no singularities in their nonlinear terms, and therefore can be handled by methods borrowed from classical nonlinear analysis.Supported in part by an NSERC grant.     

Recent developments in the theory of orographic cyclogenesis: Impact of orographic modifications on statistical properties

Summary Recent developments in the normal mode theory of lee cyclogenesis are presented. The topographic modifications of the most unstable eigenmode are computed in the most general case of primitive equations and isolated topography. The basic state about which linearization is performed is a midlatitude jet with maximum speed at tropopause level. The orographic modification consists in a pressure dipole scaling on the Rossby deformation radius already found in previous theoretical and numerical studies. The modifications of the statistical properties introduced by topography on the nonlinear feedback between zonal wind and transient waves are determined using a simple quasi-geostrophic two-layer model. Systematic differences are found to be consistent with the predictions of linear theories. A brief discussion on the limits of the linear theory is also included Paper presented at the IV Congresso del Gruppo Nazionale per la Fisica dell'Atmosfera e dell'Oceano, June 22–24, 1987, Rome.     

Stochastic Quantization of Time-Dependent Systems by the Haba and Kleinert Method

The stochastic quantization method recently developed by Haba and Kleinert is extended to non-autonomous mechanical systems, in the case of the time-dependent harmonic oscillator. In comparison with the autonomous case, the quantization procedure involves the solution of a nonlinear, auxiliary equation. Using a rescaling transformation, the Schrö-din-ger equation for the time-dependent harmonic oscillator is obtained after averaging of a classical stochastic differential equation.     

Stochastic Quantization of Time-Dependent Systems by the Haba and Kleinert Method

The stochastic quantization method recently developed by Haba and Kleinert is extended to non-autonomous mechanical systems, in the case of the time-dependent harmonic oscillator. In comparison with the autonomous case, the quantization procedure involves the solution of a nonlinear, auxiliary equation. Using a rescaling transformation, the Schrödinger equation for the time-dependent harmonic oscillator is obtained after averaging of a classical stochastic differential equation.     

A LINEARIZED PROCEDURE FOR SOLVING INVERSE SENSITIVITY EQUATIONS OF NON-DEFECTIVE SYSTEMS

A linearized algorithm for solving inverse sensitivity equations of non-defective systems is presented. It is based on the orthonormal decomposition of the first order directional derivatives and directional continuity along τ of the τ−λ base. The least-squares methods which minimize the trace of eigenmode matrix suggested by Pešek and Lallement, respectively, for self-adjoint systems are extended to general non-defective systems in this paper. Moreover, the new algorithm has intuitive simple geometrical significance and is consistent with the first order Taylor expansion of the τ−λ base. The numerical results calculated from the aforementioned three methods are compared, respectively, with the exact solution using two simulation examples. It demonstrates that the results of the proposed algorithm are the nearest to the exact solution.     

Filtering skill for turbulent signals for a suite of nonlinear and linear extended Kalman filters

The filtering skill for turbulent signals from nature is often limited by errors due to utilizing an imperfect forecast model. In particular, real-time filtering and prediction when very limited or no a posteriori analysis is possible (e.g. spread of pollutants, storm surges, tsunami detection, etc.) introduces a number of additional challenges to the problem. Here, a suite of filters implementing stochastic parameter estimation for mitigating model error through additive and multiplicative bias correction is examined on a nonlinear, exactly solvable, stochastic test model mimicking turbulent signals in regimes ranging from configurations with strongly intermittent, transient instabilities associated with positive finite-time Lyapunov exponents to laminar behavior. Stochastic Parameterization Extended Kalman Filter (SPEKF), used as a benchmark here, involves exact formulas for propagating the mean and covariance of the augmented forecast model including the unresolved parameters. The remaining filters use the same nonlinear forecast model but they introduce model error through different moment closure approximations and/or linear tangent approximation used for computing the second-order statistics of the augmented stochastic forecast model. A comprehensive study of filter performance is carried out in the presence of various moment closure errors which are enhanced by additional model errors due to incorrect parameters inducing additive and multiplicative stochastic biases. The estimation skill of the unresolved stochastic parameters is also discussed and it is shown that the linear tangent filter, despite its popularity, is completely unreliable in many turbulent regimes for both parameter estimation and filtering; moreover, regimes of filter divergence for the linear tangent filter are identified. The results presented here provide useful guidelines for filtering turbulent, high-dimensional, spatially extended systems with more general model errors, as well as for designing more skillful methods for superparameterization of unresolved intermittent processes in complex multi-scale models. They also provide unambiguous benchmarks for the capabilities of linear and nonlinear extended Kalman filters using incorrect statistics on an exactly solvable test bed with rich and realistic dynamics.     

Analyzing multiple nonlinear time series with extended Granger causality

Identifying causal relations among simultaneously acquired signals is an important problem in multivariate time series analysis. For linear stochastic systems Granger proposed a simple procedure called the Granger causality to detect such relations. In this work we consider nonlinear extensions of Granger's idea and refer to the result as extended Granger causality. A simple approach implementing the extended Granger causality is presented and applied to multiple chaotic time series and other types of nonlinear signals. In addition, for situations with three or more time series we propose a conditional extended Granger causality measure that enables us to determine whether the causal relation between two signals is direct or mediated by another process.     

一种基于二阶非线性级联的新颖全光开关

利用光子流概念研究了三波混频中本征模状态的相位和光子流的变化,以及该状态对光波的初始相位和初始光子流的要求,研究了三波混频中只有光子流的交换却没有相位变化的特殊状态,提出了本征模状态推拉式非线性光环镜的全光开关,并数值计算了这种全光开关的性能,数值结果表明,该光开关的性能稳定性好,并且易于实现和控制输出信号光的光强及相位. 关键词： 二阶非线性 级联 全光开关 光子流 三波混频 非线性光环镜     

Projector formalism of generalized Brownian motion theory applied to dissipative and noisy systems

The projector formalism of Zwanzig-Mori type is extended to obtain generalized Fokker-Planck and generalized nonlinear Langevin equations for coarse-grained variables when the underlying microscopic dynamics is dissipative and noisy (stochastic).