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Kinetic lattice Monte Carlo simulation of viscoelastic subdiffusion

机译:粘弹性扩散的动力学晶格蒙特卡洛模拟

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We propose a kinetic Monte Carlo method for the simulation of subdiffusive random walks on a Cartesian lattice. The random walkers are subject to viscoelastic forces which we compute from their individual trajectories via the fractional Langevin equation. At every step the walkers move by one lattice unit, which makes them differ essentially from continuous time random walks, where the subdiffusive behavior is induced by random waiting. To enable computationally inexpensive simulations with n-step memories, we use an approximation of the memory and the memory kernel functions with a complexity O(logn). Eventual discretization and approximation artifacts are compensated with numerical adjustments of the memory kernel functions. We verify with a number of analyses that this new method provides binary fractional random walks that are fully consistent with the theory of fractional Brownian motion.
机译:我们提出了一种动力学蒙特卡洛方法,用于在笛卡尔网格上模拟次扩散随机游动。随机助步器受到粘弹性力,我们可以通过分数朗格文方程从它们的各个轨迹计算出它们。步行者每走一步都移动一个晶格单位,这使它们与连续时间随机步行本质上有所不同,在随机步行中,亚扩散行为是由随机等待引起的。为了使用n步内存实现计算上便宜的仿真,我们使用内存的近似值和复杂度为O(logn)的内存内核函数。最终的离散化和近似伪像通过内存内核函数的数值调整得到补偿。我们通过大量分析验证了该新方法提供的二进制分数随机游动与分数布朗运动理论完全一致。

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