Speaker
Description
Stochastic resetting is a stochastic process that is reset randomly in time to its initial position and it is used in many applications as a search strategy.
In my talk I will introduce a model whose resetting events have a random amplitude instead of a back-step to the origin [1].
In particular, we study and discuss two classes of random-amplitude stochastic resetting: independent and dependent resetting.
Independent resetting is characterized by amplitudes that are unconditioned to the resetting events, which occur in the opposite direction with respect to the average free-propagation. Dependent resetting amplitudes have in turn limits on the system states such that the particle may be only partially reset towards the trajectory’s origin.
Independent resetting is a non-stationary stochastic process which may overshoot the initial position, whose mean and variance show a linear growth in time, while dependent resetting is a generalization of stochastic resetting and is a stationary stochastic process.
Geophysical layering (Stratigraphy) and population dynamic are direct applications for both classes of random-amplitude stochastic resetting.
- M. Dahlenburg, A. V. Chechkin, R. Schumer, and R. Metzler, Stochastic resetting by a random amplitude, Phys. Rev. E, 103, 052123 (2021)
