On optimal solution error covariances in variational data assimilation problems

The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find unknown parameters such as distributed model coefficients or boundary conditions. The equation for the optimal solution error is derived through the errors of the input data (background and observation errors), and the optimal solution error covariance operator through the input data error covariance operators, respectively. The quasi-Newton BFGS algorithm is adapted to construct the covariance matrix of the optimal solution error using the inverse Hessian of an auxiliary data assimilation problem based on the tangent linear model constraints. Preconditioning is applied to reduce the number of iterations required by the BFGS algorithm to build a quasi-Newton approximation of the inverse Hessian. Numerical examples are presented for the one-dimensional convection–diffusion model.     

以全球谱模式为约束的四维变分资料同化系统YH4DVAR的设计和实现

四维变分资料同化仍将是未来相当长时间内业务数值天气预报中所使用的主流同化方法．针对全球数值天气预报业务系统对气象资料同化技术的需求,在WRFDA软件框架结构的基础上,发展了一个与全球谱模式配套使用的四维变分资料同化系统YH4DVAR．系统将背景场、观测处理、重力波控制和偏差订正进行综合考虑,设计了一体化目标函数,引入了小波背景场误差协方差模型,实现了增量方法以及卫星遥感资料的直接同化．单点试验表明YH4DVAR的背景场误差模型具有各向异性、垂直相关和水平相关不可分离性、以及与位置的相关等特性．从2009年7月到2010年6月的分析预报试验结果表明,由YH4DVAR和全球谱模式组成的分析预报系统在北半球和亚洲地区的可用预报时效可以达到8天以上．     

变分同化结合广义变分最佳分析对微波散射计资料进行海面风场反演

针对微波散射计资料的海面风场反演,本文首先利用QuikSCAT卫星散射计的近实时资料,借助荷兰皇家气象学会的SeaWinds散射计数据处理模式,在不同风速和海域的情况下,采用多解方案结合二维变分同化方法进行风向的模糊去除,达到消除解的不唯一性的目的,且对4种反演结果（低速风、中速风、高速风和近海岸风）与美国国家海洋和大气管理局卫星资料中心的近实时风场数据的对比分析,说明了该技术的有效性.在此基础上,对反演得到的中速风场利用广义变分最佳分析方法进行了调整,调整后的风场结构有了进一步的改善.此方法可为我国散射计资料反演海面风场的研究提供新的思路和方法.     

Regeneration of small eddies by data assimilation in turbulence

The effect of data assimilation of large-scale eddies on small-scale eddies in turbulence is studied by direct numerical simulations (DNSs) of Navier-Stokes turbulence with Taylor microscale Reynolds numbers up to 179. The DNSs show that even if the data of small-scale eddies are lost at some initial instant, they can be regenerated from the data of large-scale eddies under the condition that Fourier modes with wave number less than a critical wave number k(*) are continuously assimilated, where k(*) approximately 0.2eta(-1) with eta identical with(nu(3)/epsilon)(1/4), epsilon the mean energy dissipation rate, and nu the viscosity.     

Macroscopic cell representation of density matrix equation and optimal choice of projectors by variational principle

We introduce a complete set of projectors on Liouvillespace and a “cell representation” of the equation of motion of the density matrixρ adjusted to the macroscopic observables of the system. Using a variational principle, the projector on the relevant density matrixρ _rel is determined by the postulate that the subdynamics ofρ _rel should include an optimal part of the Liouvillean?. The relation of the reduced subdynamics equation to wellknown master equations is investigated.     

Growth optimal investment and pricing of derivatives

We introduce a criterion how to price derivatives in incomplete markets, based on the theory of growth optimal strategy in repeated multiplicative games. We present reasons why these growth-optimal strategies should be particularly relevant to the problem of pricing derivatives. Under the assumptions of no trading costs, and no restrictions on lending, we find an appropriate equivalent martingale measure that prices the underlying and the derivative security. We compare our result with other alternative pricing procedures in the literature, and discuss the limits of validity of the lognormal approximation. We also generalize the pricing method to a market with correlated stocks. The expected estimation error of the optimal investment fraction is derived in a closed form, and its validity is checked with a small-scale empirical test.     

Diagnosis and impacts of non-Gaussianity of innovations in data assimilation

Most of the atmospheric and oceanic data assimilation (DA) schemes rely on the Best Linear Unbiased Estimator (BLUE), which is sub-optimal if errors of assimilated data are non-Gaussian, thus calling for a full Bayesian data assimilation. This paper contributes to the study of the non-Gaussianity of errors in the observational space. Possible sources of non-Gaussianity range from the inherent statistical skewness and positiveness of some physical observables (e.g. moisture, chemical species), the nonlinearity, both of the data assimilation models and of the observation operators among others. Deviations from Gaussianity can be justified from a priori hypotheses or inferred from statistical diagnostics of innovations (observation minus background), leading to consistency relationships between the error statistics. From samples of observations and backgrounds as well as their specified error variances, we evaluate some measures of the innovation non-Gaussianity, such as the skewness, kurtosis and negentropy. Under the assumption of additive errors and by relating statistical moments from both data errors and innovations, we identify potential sources of the innovation non-Gaussianity. These sources range from: (1) univariate error non-Gaussianity, (2), nonlinear correlations between errors, (3) spatio-temporal variability of error variances (heteroscedasticity) and (4) multiplicative noise. Observational and background errors are often assumed independent. This leads to variance-dependent bounds for the skewness and the kurtosis of errors. From innovation statistics, we assess the potential DA impact of some scenarios of non-Gaussian errors. This impact is measured through the mean square difference between the BLUE and the Minimum Variance Unbiased Estimator (MVUE), obtained with univariate observations and background estimates. In order to accomplish this, we compute maximum entropy probability density functions (pdfs) of the errors, constrained by the first four order moments. These pdfs are then used to compute the Bayesian posterior pdf and the MVUE. The referred impact is studied for a large range of statistical moments, being higher for skewed innovations and growing in average with the skewness of data errors, specially if the skewnesses have the same sign. An application has been performed to the quality-accepted ECMWF innovations of brightness temperatures of a set of High Resolution Infrared Sounder (HIRS) channels. In this context, the MVUE has led in some extreme cases to a potential reduction of 20%-60% of the posterior error variance as compared to the BLUE, specially for extreme values of the innovations.     

On the validity of the variational approximation in discrete nonlinear Schrödinger equations

The variational approximation is a well known tool to approximate localized states in nonlinear systems. In the context of a discrete nonlinear Schrödinger equation with a small coupling constant, we prove error estimates for the variational approximations of site-symmetric, bond-symmetric, and twisted discrete solitons. This is shown for various trial configurations, which become increasingly more accurate as more parameters are taken. It is also shown that the variational approximation yields the correct spectral stability result and controls the oscillatory dynamics of stable discrete solitons for long but finite time intervals.     

Validity of the time-dependent variational approximation to the Gaussian wavepacket method applied to double-well systems

We have examined the validity of the time-dependent variational approximation (TDVA) to the Gaussian wavepacket method (GWM) for quantum double-well (DW) systems, by using the quasi-exact spectral method (SM). Comparisons between results of wavefunctions, averages of position and momentum, the auto-correlation function, and an uncertainty product calculated by SM and TDVA have been made. It has been shown that a given initial Gaussian wavepacket in SM is quickly deformed at t>0$t>0$ where a wavepacket cannot be expressed by a single Gaussian, and that assumptions on averages of higher-order fluctuations in TDVA are not justified. These results cast some doubt on an application of TDVA to DW systems. Gaussian wavepacket dynamics in anharmonic potential systems is studied also.     

Statistical mechanics of learning: a variational approach for real data

Using a variational technique, we generalize the statistical physics approach of learning from random examples to make it applicable to real data. We demonstrate the validity and relevance of our method by computing approximate estimators for generalization errors that are based on training data alone.     

On the reconstruction of an optical potential on the basis of experimental data in the WKB approximation

The inverse scattering problem at a fixed energy for a complex-valued potential is solved in the WKB approximation. The method is used to reconstruct the optical potential for elastic ¹⁶O + ¹⁶O scattering at E _lab = 350 MeV. The stability of the solution against small changes in the scattering matrix is studied.     

The use of neural networks for approximation of nuclear data

The article discusses the possibility of using neural networks for approximation or reconstruction of data such as the reaction cross sections. The quality of the approximation using fitting criteria is also evaluated. The activity of materials under irradiation is calculated from data obtained using neural networks.     

Analysis of the Fenton-Karma model through an approximation by a one-dimensional map

The Fenton-Karma model is a simplification of complex ionic models of cardiac membrane that reproduces quantitatively many of the characteristics of heart cells; its behavior is simple enough to be understood analytically. In this paper, a map is derived that approximates the response of the Fenton-Karma model to stimulation in zero spatial dimensions. This map contains some amount of memory, describing the action potential duration as a function of the previous diastolic interval and the previous action potential duration. Results obtained from iteration of the map and numerical simulations of the Fenton-Karma model are in good agreement. In particular, the iterated map admits different types of solutions corresponding to various dynamical behavior of the cardiac cell, such as 1:1 and 2:1 patterns. (c) 2002 American Institute of Physics.     

Quantum computing by an optimal control algorithm for unitary transformations

Quantum computation is based on implementing selected unitary transformations representing algorithms. A generalized optimal control theory is used to find the driving field that generates a prespecified unitary transformation. The approach is independent of the physical implementation of the quantum computer and it is illustrated for one and two qubit gates in model molecular systems, where only part of the Hilbert space is used for computation.     

Improvement of variational approach in an interacting two-fermion system

A more reasonable trial ground state wave function is constructed for the relative motion of an interacting two-fermion system in a one-dimensional(1D) harmonic potential. At the boundaries both the wave function and its first derivative are continuous and the quasi-momentum is determined by a more practical constraint condition which associates two variational parameters. The upper bound of the ground state energy is obtained by applying the variational principle to the expectation value of the Hamiltonian of relative motion on the trial wave function. The resulted energy and wave function show better agreement with the analytical solution than the original proposal.     

Diffracted wavefield by an arbitrary aperture from Maggi-Rubinowicz transformation: Fraunhofer approximation

Fraunhofer diffraction patterns through apertures in opaque screens are the cases of most interest in optics. The major purpose of this paper is to establish a general and explicit formula for calculating diffracted wavefield from Maggi-Rubinowicz transformation. The 2-D integration (Rayleigh-Sommerfeld or Helmholtz-Kirchhoff integral formulas) is reduced to a 1-D integration over the rim of the aperture. Some examples for elliptical and polygonal apertures are given.