求解狭义逃逸问题的蒙特卡罗跟踪漂移扩散轨迹算法

IF 0.8 Q3 STATISTICS & PROBABILITY Monte Carlo Methods and Applications Pub Date : 2020-08-06 DOI:10.1515/mcma-2020-2073
K. Sabelfeld, N. Popov
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引用次数: 1

摘要

摘要本研究处理了一个窄逃逸问题,这是一个众所周知的难题,用于评估扩散粒子到达远离粒子起始位置的边界的一小部分的概率。扩散轨迹的直接模拟将花费大量的计算机模拟时间。相反,我们使用了一种不同的方法,通过引入指向目标位置的人工漂移速度,大大提高了扩散轨迹跟踪算法的效率。该方法可以有效地应用于解决一个方向上长扩展域的窄逃逸问题,这在生物学和化学的许多实际问题中都是如此。该算法在空间和时间上都是无网格的,并且很好地应用于解决复杂领域中的高维问题。本文对长方体情况下的方法进行了详细的数值分析。处理了稳态和瞬态扩散问题。
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Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems
Abstract This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particle to reach a small part of a boundary far away from the starting position of the particle. A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a different approach which drastically improves the efficiency of the diffusion trajectory tracking algorithm by introducing an artificial drift velocity directed to the target position. The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry. The algorithm is meshless both in space and time, and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled.
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来源期刊
Monte Carlo Methods and Applications
Monte Carlo Methods and Applications STATISTICS & PROBABILITY-
CiteScore
1.20
自引率
22.20%
发文量
31
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