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Journal Article

Restoring ergodicity of stochastically reset anomalous-diffusion processes


Wang,  Wei
Max Planck Institute for the Physics of Complex Systems, Max Planck Society;

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Wang, W., Cherstvy, A. G., Metzler, R., & Sokolov, I. M. (2022). Restoring ergodicity of stochastically reset anomalous-diffusion processes. Physical Review Research, 4(1): 013161. doi:10.1103/PhysRevResearch.4.013161.

Cite as: https://hdl.handle.net/21.11116/0000-000A-78FC-4
How do different reset protocols affect ergodicity of a diffusion process in single-particle-tracking experiments? We here address the problem of resetting of an arbitrary stochastic anomalous-diffusion process (ADP) from the general mathematical points of view and assess ergodicity of such reset ADPs for an arbitrary resetting protocol. The process of stochastic resetting describes the events of the instantaneous restart of a particle's motion via randomly distributed returns to a preset initial position (or a set of those). The waiting times of such resetting events obey the Poissonian, Gamma, or more generic distributions with specified conditions regarding the existence of moments. Within these general approaches, we derive general analytical results and support them by computer simulations for the behavior of the reset mean-squared displacement (MSD), the new reset increment-MSD (iMSD), and the mean reset time-averaged MSD (TAMSD). For parental nonreset ADPs with the MSD(t)proportional to t(mu) we find a generic behavior and a switch of the short-time growth of the reset iMSD and mean reset TAMSDs from proportional to Delta(mu) for subdiffusive to proportional to Delta(1) for superdiffusive reset ADPs. The critical condition for a reset ADP that recovers its ergodicity is found to be more general than that for the nonequilibrium stationary state, where obviously the iMSD and the mean TAMSD are equal. The consideration of the new statistical quantifier, the iMSD-as compared to the standard MSD-restores the ergodicity of an arbitrary reset ADP in all situations when the mu th moment of the waiting-time distribution of resetting events is finite. Potential applications of these new resetting results are, inter alia, in the area of biophysical and soft-matter systems.