Occupation time of a run-and-tumble particle with resetting

Abstract

We study the positive occupation time of a run-and-tumble particle (RTP) subject to stochastic resetting. Under the resetting protocol, the position of the particle is reset to the origin at a random sequence of times that is generated by a Poisson process with rate r. The velocity state is reset to ±v with fixed probabilities ρ1 and ρ−1 = 1 − ρ1, where v is the speed. We exploit the fact that the moment generating functions with and without resetting are related by a renewal equation, and the latter generating function can be calculated by solving a corresponding Feynman-Kac equation. This allows us to numerically locate in Laplace space the largest real pole of the moment generating function with resetting, and thus derive a large deviation principle (LDP) for the occupation time probability density using the Gartner-Ellis theorem. We explore how the LDP depends on the switching rate α of the velocity state, the resetting rate r and the probability ρ1. In particular, we show that the corresponding LDP for a Brownian particle with resetting is recovered in the fast switching limit α → ∞. On the other hand, the behavior in the slow switching limit depends on ρ1 in the resetting protocol.