Random search with resetting in heterogeneous environments

Abstract

We investigate random searches under stochastic position resetting at rate $r$, in a bounded 1D environment with space-dependent diffusivity $D(x)$. For arbitrary shapes of $D(x)$ and prescriptions of the associated multiplicative stochastic process, we obtain analytical expressions for the average time $T$ for reaching the target (mean first-passage time), given the initial and reset positions, in good agreement with stochastic simulations. For arbitrary $D(x)$, we obtain an exact closed-form expression for $T$, within Stratonovich scenario, while for other prescriptions, like It\^o and anti-It\^o, we derive asymptotic approximations for small and large rates $r$. Exact results are also obtained for particular forms of $D(x)$, such as the linear one, with arbitrary prescriptions, allowing to outline and discuss the main effects introduced by diffusive heterogeneity on a random search with resetting. We explore how the effectiveness of resetting varies with different types of heterogeneity.