Random acceleration process under stochastic resetting

Abstract

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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