Exact first-passage time distributions for three random diffusivity models

Abstract

We study the extremal properties of a stochastic process $x_t$ defined by a Langevin equation ${\dot{x}}_t=\sqrt{2D_{0}V(B_t)}{\xi }_t$, where ${\xi }_t$ is a Gaussian white noise with zero mean, $D_0$ is a constant scale factor, and $V(B_t)$ is a stochastic "diffusivity" (noise strength), which itself is a functional of independent Brownian motion $B_t$. We derive exact, compact expressions for the probability density functions (PDFs) of the first passage time (FPT) $t$ from a fixed location $x_0$ to the origin for three different realisations of the stochastic diffusivity: a cut-off case $V(B_t)=\Theta (B_t)$ (Model I), where $\Theta (x)$ is the Heaviside theta function; a Geometric Brownian Motion $V(B_t)=\exp (B_t)$ (Model II); and a case with $V(B_t)=B_t^2$ (Model III). We realise that, rather surprisingly, the FPT PDF has exactly the Lévy-Smirnov form (specific for standard Brownian motion) for Model II, which concurrently exhibits a strongly anomalous diffusion. For Models I and III either the left or right tails (or both) have a different functional dependence on time as compared to the Lévy-Smirnov density. In all cases, the PDFs are broad such that already the first moment does not exist. Similar results are obtained in three dimensions for the FPT PDF to an absorbing spherical target.

arXiv comment8 pages, 3 figures, RevTeX

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