论文标题
用洛伦兹力重置活性布朗颗粒的随机重置
Stochastic resetting of active Brownian particles with Lorentz force
论文作者
论文摘要
外部磁场中被动扩散颗粒系统的平衡特性不受洛伦兹力的影响。相反,活性的布朗颗粒表现出稳态现象,取决于施加磁场的强度和极性。但是,只有在系统中保持平衡密度梯度时,才能观察到洛伦兹力的有趣效应。为此,我们通过将其重置为二维的活性布朗粒子的随机重置方法,通过将它们重置为$ x = 0 $的行,以恒定的速率和周期性在$ y $方向上。在随机重置下,一个主动系统沉降到非平凡的固定态,其特征是垂直于密度梯度的不均匀密度分布,极化和散装通量。我们表明,尽管对于均匀的磁场,可以从其被动对应物中获得活性系统的固定状态的性质,但在不均匀的磁场的情况下,新颖的特征出现了,在被动系统中没有对应物。特别是存在一个依赖活性的阈值率,因此对于较小的重置速率,活动颗粒的密度分布变为非单调。我们还研究了$ x $轴的平均第一学期时间,并找到一个令人惊讶的结果:在磁场从轴上增加的情况下,从任何给定点到达目标需要更多的时间才能达到目标。理论预测是使用布朗动力学模拟验证的。
The equilibrium properties of a system of passive diffusing particles in an external magnetic field are unaffected by the Lorentz force. In contrast, active Brownian particles exhibit steady-state phenomena that depend on both the strength and the polarity of the applied magnetic field. The intriguing effects of the Lorentz force, however, can only be observed when out-of-equilibrium density gradients are maintained in the system. To this end, we use the method of stochastic resetting on active Brownian particles in two dimensions by resetting them to the line $x=0$ at a constant rate and periodicity in the $y$ direction. Under stochastic resetting, an active system settles into a nontrivial stationary state which is characterized by an inhomogeneous density distribution, polarization and bulk fluxes perpendicular to the density gradients. We show that whereas for a uniform magnetic field the properties of the stationary state of the active system can be obtained from its passive counterpart, novel features emerge in the case of an inhomogeneous magnetic field which have no counterpart in passive systems. In particular, there exists an activity-dependent threshold rate such that for smaller resetting rates, the density distribution of active particles becomes non-monotonic. We also study the mean first-passage time to the $x$ axis and find a surprising result: it takes an active particle more time to reach the target from any given point for the case when the magnetic field increases away from the axis. The theoretical predictions are validated using Brownian dynamics simulations.