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arXiv 2007.05576cond-mat.stat-mech
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随机复位下的随机加速度过程

Random acceleration process under stochastic resetting

Prashant Singh

摘要:

考虑了随机加速粒子在随机重置机制下的一维运动。分别用$x$和$v$表示位置和速度,我们考虑两种不同的复位协议-(i)完全复位:这里$x$和$v$都以恒定速率$r$复位到它们的初始值$x_0$和$v_0$,(ii)部分复位:这里只有$x$复位到$x_0$,而$v$没有中断地演化。对于完全复位,我们发现粒子在$x$和$v$中都达到定态.我们计算了$x$和$v$的非平衡联合定态,并研究了分布函数的后期弛豫。另一方面,对于部分复位,联合分布总是处于瞬态。在大$t$,位置分布具有缩放行为$(x/ \sqrt{t})$,我们严格推导。接下来,我们研究了在原点处具有吸收壁的第一通过时间特性。对于完全复位,我们发现,平均首次通过时间呈现有限的复位机制。我们明确地推导出表达式的平均首次通过时间和生存概率在大$t$。然而,在鲜明的对比,部分重置,我们发现,重置不呈现有限的平均首次通过时间。这是因为即使$x$被带到$x_0$,$v$($\sim \sqrt{t}$)的大波动也可以使粒子远离原点。所有的分析结果都得到了数值模拟的证实。

英文摘要:

We consider the motion of a randomly accelerated particle in one dimension under stochastic resetting mechanism. Denoting the position and velocity by $x$ and $v$ respectively, we consider two different resetting protocols - (i) complete resetting: here both $x$ and $v$ reset to their initial values $x_0$ and $v_0$ at a constant rate $r$, (ii) partial resetting: here only $x$ resets to $x_0$ while $v$ evolves without interruption. For complete resetting, we find that the particle attains stationary state in both $x$ and $v$. We compute the non-equilibrium joint stationary state of $x$ and $v$ and also study the late time relaxation of the distribution function. On the other hand, for partial resetting, the joint distribution is always in the transient state. At large $t$, the position distribution possesses a scaling behaviour $(x/ \sqrt{t})$ which we rigorously derive. Next, we study the first passage time properties with an absorbing wall at the origin. For complete resetting, we find that the mean first passage time is rendered finite by the resetting mechanism. We explicitly derive the expressions for the mean first passage time and the survival probability at large $t$. However, in stark contrast, for partial resetting, we find that resetting does not render finite mean first passage time. This is because even though $x$ is brought to $x_0$, the large fluctuation in $v$ ($\sim \sqrt{t}$) can take the particle substantially far from the origin. All our analytic results are corroborated by the numerical simulations.

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