Rounding Error Analysis in Solving M-Matrix Linear Systems of Block Hessenberg Form

The problem of solving large M-matrix linear systems with sparse coefficient matrix in block Hessenberg form is here addressed. In previous work of the authors a divide-and-conquer strategy was proposed and a backward error analysis of the resulting algorithm was presented showing its effectiveness for the solution of computational problems of queueing theory and Markov chains. In particular, it was shown that for block Hessenberg M-matrices the algorithm is weakly backward stable in the sense that the computed solution is the exact solution of a nearby linear system, where the norm of the perturbation is proportional to the condition number of the coefficient matrix. In this note a better error estimate is given by showing that for block Hessenberg M-matrices the algorithm is even backward stable.     

An equivalent polynomial approximation technique in nonlinear structural dynamics

Summary A new technique is proposed to obtain an approximate probability density for the response of a general nonlinear system under Gaussian white noise excitations. In this new technique, the original nonlinear system is replaced by another equivalent nonlinear system, structured by the polynomial formula, for which the exact solution of stationary probability density function is obtainable. Since the equivalent nonlinear system structured in this paper originates directly from certain classes of real nonlinear mechanical systems, the technique is applied to some very challenging nonlinear systems in order to show its power and efficiency. The calculated results show that applying the technique presented here can yield exact stationary solutions for the nonlinear oscillators. This is obtained by using an energy-dependent system, and for a nonlinearity of a more complex type. A more accurate approximate solution is then available, and is compared with the approximation. Application of the technique is illustrated by examples.     

INVARIANCE PRINCIPLE FOR THE INTEGRAL PERIODOGRAM OF A MULTIPLE TIME SERIES

Many authers have studied the asymptotic behavior of the integral periodogram of a Gaussian stationary series. In this paper, the invariance principle for the integral periodogram of a multiple time series is investigated. We have obtained the following theorem:Let X, be a real M -dimensional stationary time series with spectral density matrix f(λ) which satis-fies the conditions:M,and X, can be represented in theform: Xn =whereξ, is the M-dimensional fourth order moment existedstationary martingale series, thenweakly converges to a Gauss process η(λ) withEη(λ) = 0,where V and Q are the second and fourth moment of the martingale seriesξ , respectively.From this theorem, two corollaries have been given, which cover some results of [2][5][6].     

用于高斯光束均匀化的非球面透镜系统分析与设计

提出一种用于高斯光束均匀化的透镜系统，论述这一系统实现高斯光束均匀化的基本原理，介绍系统的具体设计方法，并在具体参数下给出实际的加工曲线和光学结构。     

Multi-funnel optimization using Gaussian underestimation

In several applications, underestimation of functions has proven to be a helpful tool for global optimization. In protein–ligand docking problems as well as in protein structure prediction, single convex quadratic underestimators have been used to approximate the location of the global minimum point. While this approach has been successful for basin-shaped functions, it is not suitable for energy functions with more than one distinct local minimum with a large magnitude. Such functions may contain several basin-shaped components and, thus, cannot be underfitted by a single convex underestimator. In this paper, we propose using an underestimator composed of several negative Gaussian functions. Such an underestimator can be computed by solving a nonlinear programming problem, which minimizes the error between the data points and the underestimator in the L ¹ norm. Numerical results for simulated and actual docking energy functions are presented.     

Bounds on the Mass for the High Dimensional Gaussian Lattice Field between Two Hard Walls

We consider the d(≥3)-dimensional Gaussian lattice field confined between two hard walls. We show that the field becomes massive and identify the precise asymptotic behavior of the mass and the variance of the field as the height of the wall goes to infinity.     

Gaussian optical design of a submillimeter-wave and far-infrared laser sideband heterodyne spectrometer

A submillimeter-wave/far-infrared (SMM/FIR) laser sideband heterodyne spectrometer has been built for molecular rotational spectroscopy application in the frequency range of 600–3000 GHz. Based on Gaussian optics, optical system of the spectrometer is designed to be quasi-achromatic and low losses. In this article the optical design and the performance of the spectrometer are presented.     

Irradiance map of an apertured Gaussian beam affected by coma

The Gaussian amplitude of a laser beam incident on an optical system affected by coma is expanded until the fourth order. This expansion is included in the Huygens-Fresnel integral calculation to obtain the amplitude and irradiance distribution on the focal plane of an optical system affected by coma. The analytical results obtained here are compared with a previous model of a comatic Gaussian beam. Appropriateness of the analytical model is also validated by the fitting with experimental data.     

View factor for inclined plane with Gaussian source

The view factor (angle factor) for a differential inclined plane in the case of a radiating source of radially Gaussian intensity is considered. This information is useful for modelling of solar radiation in certain applications. The view factor is expressed in terms of two integrals, one of which is obtained in closed form in terms of special functions, and the other is approximated. A compact estimate for the view factor is presented which is suitable for machine computation. While the relative error associated with the final estimate is typically less than 0.01%, and in all cases, less than 0.2%, the method is easily extended to yield even greater accuracy.