论文标题
一种表征异常和瞬态扩散的位移分布函数的经验方法
An empirical method to characterize displacement distribution functions for anomalous and transient diffusion
论文作者
论文摘要
我们提出了一种实用的经验拟合功能，以表征通常在异质扩散问题上观察到的非高斯位移分布函数（DISPD）。我们首先使用Langevin Dynamics（LD）模拟的胶体粒子在两个壁之间扩散的胶体颗粒的问题首先测试了该拟合函数，该构图与晶状体玻璃体（LB）流体的覆盆子粒子进行了模拟。我们还通过在具有障碍物的正方形晶格上使用简单的异常扩散模型来测试该功能。在这两种情况下，拟合参数都提供了更多的物理信息，而不仅仅是峰度（通常是用于量化动力学异常程度的方法），包括标记DISPD尾巴开始的长度尺度。在所有情况下，随着系统的异常情况，拟合参数平滑地收敛到高斯值。
We propose a practical empirical fitting function to characterize the non-Gaussian displacement distribution functions (DispD) often observed for heterogeneous diffusion problems. We first test this fitting function with the problem of a colloidal particle diffusing between two walls using Langevin Dynamics (LD) simulations of a raspberry particle coupled to a lattice Boltzmann (LB) fluid. We also test the function with a simple model of anomalous diffusion on a square lattice with obstacles. In both cases, the fitting parameters provide more physical information than just the Kurtosis (which is often the method used to quantify the degree of anomaly of the dynamics), including a length scale that marks where the tails of the DispD begin. In all cases, the fitting parameters smoothly converge to Gaussian values as the systems become less anomalous.
