Local large deviation principle for Wiener process with random resetting
arXiv:1911.06751
Abstract
We consider a class of Markov processes with resettings, where at random times, the Markov processes are restarted from a predetermined point or a region. These processes are frequently applied in physics, chemistry, biology, economics, and in population dynamics. In this paper we establish the local large deviation principle (LLDP) for the Wiener processes with random resettings, where the resettings occur at the arrival time of a Poisson process. Here, at each resetting time, a new resetting point is selected at random, according to a conditional distribution.
References in corpus (9)
- Diffusion with Stochastic Resetting
- First order transition for the optimal search time of Lévy flights with resetting
- Stochastic resetting in backtrack recovery by RNA polymerases
- Stochastic multiplicative processes with reset events
- Large deviations for Markov processes with resetting
- Switching and growth for microbial populations in catastrophic responsive environments
- Properties of additive functionals of Brownian motion with resetting
- A continuous-time Ehrenfest model with catastrophes and its jump-diffusion approximation
- The local principle of large deviations for compound Poisson process with catastrophes