Abstract

Nowadays, the stochastic resetting process is an attractive research topic in stochastic process. At the same time, a series of researches on stochastic diffusion in complex structures introduced ways to understand the anomalous diffusion in complex systems. In this work, we propose a non-static stochastic resetting model in the context of comb structure that consists of a structure formed by backbone in x axis and branches in y axis. Then, we find the exact analytical solutions for marginal distribution concerning x and y axis. Moreover, we show the time evolution behavior to mean square displacements (MSD) in both directions. As a consequence, the model revels that until the system reaches the equilibrium, i.e., constant MSD, there is a Brownian diffusion in y direction, i.e., ⟨ ( Δ y ) 2 ⟩ ∝ t , and a crossover between sub and ballistic diffusion behaviors in x direction, i.e., ⟨ ( Δ x ) 2 ⟩ ∝ t 1 2 and ⟨ ( Δ x ) 2 ⟩ ∝ t 2 respectively. For static stochastic resetting, the ballistic regime vanishes. Also, we consider the idealized model according to the memory kernels to investigate the exponential and tempered power-law memory kernels effects on diffusive behaviors. In this way, we expose a rich class of anomalous diffusion process with crossovers among them. The proposal and the techniques applied in this work are useful to describe random walkers with non-static stochastic resetting on comb structure.

Highlights

  • The statistical models in physics offer ways to understand the implicit behaviors of the stochastic process in nature

  • We investigated the non-static stochastic resetting process on comb model

  • The non-static characteristic allows resetting the system on a point that moves with a constant velocity v on dorsal backbone in comb structure

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Summary

Introduction

The statistical models in physics offer ways to understand the implicit behaviors of the stochastic process in nature. A series of investigations have been carried out using several diffusive models on comb structure, we can mention some of these advances: models associated with sub-diffusive processes on fractal comb [33], heterogeneous diffusion models on comb structure [34], first passage problem associated with systems that remove particles on the structure of the comb [35], a random search for target [36] and fractional kinetic on comb structure [37] In this sense, this work brings a detailed study about non-static stochastic resetting [12] on comb structure.

The Model
Kxk2x e
The Model with Memory Kernels Effects
First Case
Second Case
Conclusions
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