Active particle in a harmonic trap driven by a resetting noise: an approach via Kesten variables

Mathis Gueneau, Satya N Majumdar, Gregory Schehr
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引用次数: 2

Abstract

Abstract We consider the statics and dynamics of a single particle trapped in a one-dimensional harmonic potential, and subjected to a driving noise with memory, that is represented by a resetting stochastic process. The finite memory of this driving noise makes the dynamics of this particle ‘active’. At some chosen times (deterministic or random), the noise is reset to an arbitrary position and restarts its motion. We focus on two resetting protocols: periodic resetting, where the period is deterministic, and Poissonian resetting, where times between resets are exponentially distributed with a rate r . Between the different resetting epochs, we can express recursively the position of the particle. The random relation obtained takes a simple Kesten form that can be used to derive an integral equation for the stationary distribution of the position. We provide a detailed analysis of the distribution when the noise is a resetting Brownian motion (rBM). In this particular instance, we also derive a renewal equation for the full time dependent distribution of the position that we extensively study. These methods are quite general and can be used to study any process harmonically trapped when the noise is reset at random times.
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由重置噪声驱动的谐波阱中的活跃粒子:一种通过凯斯顿变量的方法
摘要:我们考虑被困在一维谐波势中的单个粒子的静力学和动力学,并受到具有记忆的驱动噪声,该驱动噪声由重置随机过程表示。这种驱动噪声的有限记忆使得这种粒子的动力学“活跃”。在某些选定的时间(确定的或随机的),噪声被重置到任意位置并重新开始其运动。我们专注于两种重置协议:周期重置,其中周期是确定性的,和泊松重置,其中重置之间的时间以指数分布的速率r。在不同的重置时间之间,我们可以递归地表示粒子的位置。得到的随机关系采用简单的Kesten形式,可用于导出位置平稳分布的积分方程。我们详细分析了噪声为重置布朗运动时的分布。在这个特殊的例子中,我们还推导出了我们广泛研究的位置的全时间相关分布的更新方程。这些方法是非常通用的,可用于研究在随机时间复位噪声时谐波捕获的任何过程。
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