论文标题

奔跑的细菌慢慢接近扩散状态

Run-and-tumble bacteria slowly approaching the diffusive regime

论文作者

Villa-Torrealba, Andrea, Raby, Cristóbal Chávez, de Castro, Pablo, Soto, Rodrigo

论文摘要

奔跑的(RT)动力学随后是细菌游泳者,由于其持久性,然后通过连续滚动而引起的弹道运动,从而引起了扩散过程。在这里,我们调查了稀释游泳者悬架达到扩散状态需要多长时间,以及与扩散动力学的偏差的幅度是多少。均方位移(MSD)的线性时间依赖性不足以表征扩散,因此我们还专注于位移分布的过量峰度。考虑了四种游泳策略:(i)在翻滚后具有完全重新定位的常规RT模型,(ii)部分重新定位的情况,其特征是分散角度的分布,(iii)具有旋转扩散的运行和退向模型,以及(iv)RT粒子均取决于内部蛋白质的旋转速率。通过分析概率密度函数的相关动力学方程并模拟模型,我们发现对于模型(ii),(iii)和(iv)扩散的放松可能比平均跌落事件之间的平均时间更长,这表明粒子位移中大尾巴的存在。此外,多余的峰度可以假设较大的正值。在模型(ii)中,MSD可能达到线性时间依赖性的某些分布,但仍然长时间仍然是非高斯的。小旋转扩散率也是模型(III)中的情况。对于所有模型,还获得了长期扩散系数。理论方法依赖于van Hove功能的特征值和角度傅立叶扩展,这与模拟非常吻合。

The run-and-tumble (RT) dynamics followed by bacterial swimmers gives rise first to a ballistic motion due to their persistence, and later, through consecutive tumbles, to a diffusive process. Here we investigate how long it takes for a dilute swimmer suspension to reach the diffusive regime as well as what is the amplitude of the deviations from the diffusive dynamics. A linear time dependence of the mean-squared displacement (MSD) is insufficient to characterize diffusion and thus we also focus on the excess kurtosis of the displacement distribution. Four swimming strategies are considered: (i) the conventional RT model with complete reorientation after tumbling, (ii) the case of partial reorientation, characterized by a distribution of tumbling angles, (iii) a run-and-reverse model with rotational diffusion, and (iv) a RT particle where the tumbling rate depends on the stochastic concentration of an internal protein. By analyzing the associated kinetic equations for the probability density function and simulating the models, we find that for models (ii), (iii), and (iv) the relaxation to diffusion can take much longer than the mean time between tumble events, evidencing the existence of large tails in the particle displacements. Moreover, the excess kurtosis can assume large positive values. In model (ii) it is possible for some distributions of tumbling angles that the MSD reaches a linear time dependence but, still, the dynamics remains non-Gaussian for long times. This is also the case in model (iii) for small rotational diffusivity. For all models, the long-time diffusion coefficients are also obtained. The theoretical approach, which relies on eigenvalue and angular Fourier expansions of the van Hove function, is in excellent agreement with the simulations.

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