Lee Miru, Szuttor Kai, Holm Christian
Institute for Computational Physics, University of Stuttgart, Allmandring 3, 70569 Stuttgart, Germany.
J Chem Phys. 2019 May 7;150(17):174111. doi: 10.1063/1.5085836.
In this article we present a computational model for the simulation of self-propelled anisotropic bacteria. To this end we use a self-propelled particle model and augment it with a statistical algorithm for the run-and-tumble motion. We derive an equation for the distribution of reorientations of the bacteria that we use to analyze the statistics of the random walk and that allows us to tune the behavior of our model to the characteristics of an E. coli bacterium. We validate our implementation in terms of a single swimmer and demonstrate that our model is capable of reproducing E. coli's run-and-tumble motion with excellent accuracy.
在本文中，我们提出了一个用于模拟自推进各向异性细菌的计算模型。为此，我们使用了一个自推进粒子模型，并通过一种用于游动和翻滚运动的统计算法对其进行扩充。我们推导了一个细菌重定向分布的方程，用于分析随机游走的统计数据，并使我们能够将模型的行为调整到大肠杆菌的特征。我们针对单个游动者验证了我们的实现，并证明我们的模型能够以极高的精度再现大肠杆菌的游动和翻滚运动。
