Stochastic resetting with stochastic returns using external trap

In the past few years, stochastic resetting has become a subject of immense interest. Most of the theoretical studies so far focused on instantaneous resetting which is, however, a major impediment to practical realisation or experimental verification in the field. This is because in the real world, taking a particle from one place to another requires finite time and thus a generalization of the existing theory to incorporate non-instantaneous resetting is very much in need. In this paper, we propose a method of resetting which involves non-instantaneous returns facilitated by an external confining trap potential U(x) centered at the resetting location. We consider a Brownian particle that starts its random motion from the origin. Upon resetting, the trap is switched on and the particle starts experiencing a force towards the center of the trap which drives it to return to the origin. The return phase ends when the particle makes a first passage to this center. We develop a general framework to study such a set up. Importantly, we observe that the system reaches a non-equilibrium steady state which we analyze in full details for two choices of U(x), namely, (i) linear and (ii) harmonic. Finally, we perform numerical simulations and find an excellent agreement with the theory. The general formalism developed here can be applied to more realistic return protocols opening up a panorama of possibilities for further theoretical and experimental applications.

Automated summary

This paper introduces a method of non-instantaneous resetting by utilizing an external confining trap potential to drive a Brownian particle back to its origin. The system reaches a non-equilibrium steady state, which is analyzed in detail, and numerical simulations show excellent agreement with the theoretical predictions. The general formalism developed in this study can be applied to realistic return protocols, offering a wide range of possibilities for further theoretical and experimental applications.