We consider the problem of determining the arrival statistics of unbiased planar random walkers to complex target configurations. In contrast to problems posed in finite domains, simple moments of the distribution, such as the mean (MFPT) and variance, are not defined and it is necessary to obtain the full arrival statistics. We describe several methods to obtain these distributions and other associated quantities such as splitting probabilities. One approach combines a Laplace transform of the underlying parabolic equation with matched asymptotic analysis followed by numerical transform inversion. The second approach is similar, but uses a boundary integral equation method to solve for the Laplace transformed variable. To validate the results of this theory, and to obtain the arrival time statistics in very general configurations of absorbers, we introduce an efficient Kinetic Monte Carlo (KMC) method that describes trajectories as a combination of large but exactly solvable projection steps. The effectiveness of these methodologies is demonstrated on a variety of challenging examples highlighting the applicability of these methods to a variety of practical scenarios, such as source inference. A particularly useful finding arising from these results is that homogenization theories, in which complex configurations are replaced by equivalent simple ones, are remarkably effective at describing arrival time statistics.
翻译:我们考虑的是确定无偏向平板随机行走者抵达的统计与复杂目标配置的问题。与有限域的问题相比,分布的简单瞬间,如平均值(MFPT)和差异,没有定义,因此有必要获得完整的抵达统计。我们描述了获得这些分布和其他相关数量的几种方法,如分辨概率。一种方法是将基本抛物线方程的拉普尔变换与匹配的无症状分析结合起来,然后进行数字变换。第二种办法是相似的,但使用边界整体等式方法来解决拉帕特变异。为了验证这一理论的结果,并获得吸收器非常一般配置的到达时间统计,我们采用了高效的基尼特蒙特卡洛(KMC)方法,将轨迹描述为大但完全可溶化的预测步骤的组合。这些方法的有效性表现在各种具有挑战性的例子中,这些例子强调这些方法对各种实际假设的可适用性,例如来源推论。从这些结果中得出的一个特别有用的发现是,从这些结果中得出了这种理论的结果,为了验证这一理论的结果,并获得非常一般的运算。