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A simple model of a one-dimensional, randomly rough, non-Gaussian surface

机译:一维,随机粗糙,非高斯表面的简单模型

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Several years ago Knotts, Michel, and O'Donnell (J. Opt. Soc. Am. A10, 928 (1993)) measured and calculated the independent elements of the Stokes matrix for in-plane scattering from a one-dimensional, randomly rough, metal surface. They found that the agreement between the computer simulation results and the experimental results for these matrix elements was significantly improved if the statistical properties of the surface profile function ζ(x_1) determined experimentally were used in the simulations instead of the commonly used assumption that ζ(x_1) is a stationary zero-mean, Gaussian random process with a Gaussian surface height autocorrelation function. Specifically, they found that while the probability density function (pdf) of ζ(x_1) for the surface studied was closely a Gaussian, with a correlation function that was also closely a Gaussian, the pdf of ζ′(x_1) was lower at the origin than predicted by a Gaussian expression, and the pdf of ζ″(x_1) was skewed in the direction of positive values of this function. By starting from a function H(x_1) that is a stationary, single-valued, zero-mean, Gaussian random process, with a Gaussian surface height autocorrelation function, we show how to construct surface profile functions ζ(x_1) of the form ζ(x_1) = [H(x_1) + F(H(x_1),H′(x_1), H″(x_1))] that have statistical properties of the kind displayed by the surface studied by Knotts et al.. Results of computer simulation calculations of the Stokes matrix elements on the basis of a surface defined by H(x_1) and on the basis of profile functions ζ(x_1) obtained from it show that some of the latter can be in qualitatively and quantitatively better agreement with the experimental results of Knotts et al. than the results based on H(x_1).
机译:若干年前诺茨,米歇尔,和O'Donnell的(J.选项会志A10。PM。,928(1993))测量和计算斯托克斯矩阵的独立元件,用于面内散射从一维,随机粗糙,金属表面。他们发现,该计算机模拟结果和实验结果对于这些矩阵的元素之间的协议,如果确定进行了实验在模拟的,而不是通常使用的假设,即ζ使用的表面轮廓函数ζ的统计特性(X_1)中的溶液显著改善( X_1)是固定的零均值高斯随机具有高斯表面高度自相关函数的过程。具体地,他们发现,尽管研究了表面的概率密度函数ζ(X_1)的(PDF)是紧密的高斯,与也是密切高斯,ζ的PDF'(X_1)的相关函数在较低原点比高斯表达式预测,和ζ的“(X_1)的PDF是该函数的正值的方向偏斜。通过从函数H(X_1),其是固定的,单值的,零均值高斯随机过程开始,具有高斯面高度自相关函数,我们可以了解如何构建表面轮廓函数ζ(X_1)形式ζ的(X_1)= [H(X_1)+ F(H(X_1),H'(X_1),H“(X_1))]为具有种统计特性显示通过的纳氏等人研究的结果的表面斯托克斯的计算机模拟计算矩阵由H(X_1)限定的表面的基础上的元件,并从它获得的轮廓功能ζ(X_1)的基础上显示,一些后者可以定性被中和与定量更好协议诺茨等人的实验结果。比基于H的结果(X_1)。

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