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Random walk on semi-cylinders for diffusion problems with mixed Dirichlet-Robin boundary conditions

机译:具有混合Dirichlet-Robin边界条件的扩散问题在半圆柱体上的随机游动

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We suggest random walk on semi-infinite cylinders methods for solving interior and exterior diffusion problems with different types of boundary conditions which include mixed Dirichlet, Neumann, and Robin boundary conditions on different parts of the boundary. Based on probabilistic interpretation of the diffusion process, stochastic simulation algorithms take into account specific features of each boundary condition to optimally adjust the Markov chain distribution on the relevant boundary parts. In contrast to the conventional direct trajectory tracking method, the new method avoids to simulate the diffusion trajectories. Instead, it exploits exact probabilities of different events like the first passage, splitting, and survival probabilities inside the semi-infinite cylinders, depending on the domain and its boundary structure. Applications to diffusion imaging methods like the cathodoluminescence (CL) and electron beam induced current (EBIC) semiconductor analysis techniques performed in scanning electron and transmission microscopes, are discussed.
机译:我们建议在半无限圆柱体上随机行走,以解决具有不同类型边界条件的内部和外部扩散问题,这些边界条件包括边界不同部分上的混合Dirichlet,Neumann和Robin边界条件。基于对扩散过程的概率解释,随机模拟算法会考虑每个边界条件的特定特征,以最佳地调整相关边界部分上的马尔可夫链分布。与传统的直接轨迹跟踪方法相比,新方法避免了模拟扩散轨迹。取而代之的是,它根据域及其边界结构,利用不同事件的确切概率,例如半无限圆柱体内部的第一遍,分裂和生存概率。讨论了在诸如扫描电子显微镜和透射显微镜中进行的阴极发光(CL)和电子束感应电流(EBIC)半导体分析技术等扩散成像方法中的应用。

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