首页> 外文会议>Conference on photonic and phononic crystal materials and devices IX; 20090127-29; San Jose, CA(US) >Discretely disordered photonic bandgap structures: a more accurate invariant measure calculation
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Discretely disordered photonic bandgap structures: a more accurate invariant measure calculation

机译:离散无序光子带隙结构:更准确的不变量度计算

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In the one-dimensional optical analog to Anderson localization, a periodically layered medium has one or more parameters randomly disordered. Such a randomized system can be modeled by an infinite product of 2×2 random transfer matrices with the upper Lyapunov exponent of the matrix product identified as the localization factor (inverse localization length) for the model. The theorem of Furstenberg allows us, at least theoretically, to calculate this upper Lyapunov exponent. In Furstenberg's formula we not only integrate with respect to the probability measure of the random matrices, but also with respect to the invariant probability measure of the direction of the vector propagated by the random matrices. This invariant measure is difficult to find analytically, and, as a result, the most successful approach is to determine the invariant measure numerically. A Monte Carlo simulation which uses accumulated bin counts to track the direction of the propagated vector through a long chain of random matrices does a good job of estimating the invariant probability measure, but with a level of uncertainty. A potentially more accurate numerical technique by Froyland and Aihara obtains the invariant measure as a left eigenvector of a large sparse matrix containing probability values determined by the action of the random matrices on input vectors. We first apply these two techniques to a random Fibonacci sequence whose Lyapunov exponent was determined by Viswanath. We then demonstrate these techniques on a quarter-wave stack model with binary discrete disorder in layer thickness, and compare results to the continuously disordered counterpart.
机译:在与安德森定位的一维光学模拟中,周期性分层的介质具有一个或多个随机无序的参数。这样的随机系统可以通过2×2随机转移矩阵的无穷乘积建模,矩阵乘积的上Lyapunov指数被标识为模型的局部化因子(逆局部化长度)。弗斯滕贝格定理至少在理论上使我们能够计算该上Lyapunov指数。在Furstenberg的公式中,我们不仅针对随机矩阵的概率度量进行了积分,而且针对随机矩阵传播的矢量方向的不变概率度量进行了积分。很难通过分析找到这种不变量度,因此,最成功的方法是通过数值确定不变量度。蒙特卡洛模拟使用累积的二进制数来跟踪通过一长串随机矩阵传播的矢量的方向,可以很好地估计不变概率测度,但不确定性较高。由Froyland和Aihara提出的一种可能更准确的数值技术,将获得的不变度量作为一个大型稀疏矩阵的左本征向量,该稀疏矩阵包含由随机矩阵对输入矢量的作用所确定的概率值。我们首先将这两种技术应用于由Fiswanath确定其Lyapunov指数的随机斐波那契序列。然后,我们在四分之一波堆栈模型上用层厚度的二进制离散无序来证明这些技术,并将结果与​​连续无序的对等物进行比较。

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