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arXiv 2012.14155cond-mat.softcond-mat.stat-mechphysics.bio-ph
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二维主动-被动布朗粒子

Active-Passive Brownian Particle in Two Dimensions

Tayeb Jamali

AI总结:

本文提出速度在0与s间按随机电报过程切换的二维主动-被动布朗粒子模型,推导位移矩和有效扩散系数,并将奔跑-翻滚粒子映射到该模型。

摘要:

我们描述了一个用于主动粒子的二维模型,其自推进速度并非固定,而是随时间变化,并且其运动同时受到平动扩散和转动扩散的影响。在主动布朗运动的常规处理中,自推进速度被视为常数——这一假设便于分析,但与许多真实系统并不匹配。在这里,我们放宽该假设,允许速度 v(t) 在两个值之间随机波动:v=0(被动状态)和 v=s(主动状态)。这些状态之间的转换被设定为遵循随机电报过程。这种“主动-被动布朗粒子”继承了纯主动和纯被动布朗两种情形的极限行为。关于前两个位移矩以及由此产生的有效扩散系数的解析表达式,使这种双重特性变得明确。此外,通过适当的参数对应,run-and-tumble particle(奔跑-翻滚粒子)——例如运动细菌——可以映射到该模型上,从而使它们的大尺度扩散系数一致。

英文摘要:

We describe a two-dimensional model for active particles whose self-propulsion speed is not fixed, but varies in time, and whose motion is subject to both translational and rotational diffusion. In the conventional treatment of active Brownian motion, the self-propulsion speed is taken to be constant - an assumption convenient for analysis but poorly matched to many real systems. Here we relax that assumption, allowing the speed $v(t)$ to fluctuate stochastically between two values: $v=0$ (a passive state) and $v=s$ (an active state). Transitions between these states are taken to follow a random telegraph process. This ``active-passive Brownian particle'' inherits limiting behaviors from both the purely active and purely passive Brownian cases. Analytical expressions for the first two displacement moments, and for the resulting effective diffusion coefficient, make this dual character explicit. Moreover, by an appropriate identification of parameters, a run-and-tumble particle - such as a motile bacterium - can be mapped onto this model in such a way that their large-scale diffusivities coincide.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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