Anomalous diffusion, non-Gaussianity, and nonergodicity for subordinated fractional Brownian motion with a drift.


Journal

Physical review. E
ISSN: 2470-0053
Titre abrégé: Phys Rev E
Pays: United States
ID NLM: 101676019

Informations de publication

Date de publication:
Aug 2023
Historique:
received: 20 01 2023
accepted: 11 08 2023
medline: 19 9 2023
pubmed: 19 9 2023
entrez: 19 9 2023
Statut: ppublish

Résumé

The stochastic motion of a particle with long-range correlated increments (the moving phase) which is intermittently interrupted by immobilizations (the trapping phase) in a disordered medium is considered in the presence of an external drift. In particular, we consider trapping events whose times follow a scale-free distribution with diverging mean trapping time. We construct this process in terms of fractional Brownian motion with constant forcing in which the trapping effect is introduced by the subordination technique, connecting "operational time" with observable "real time." We derive the statistical properties of this process such as non-Gaussianity and nonergodicity, for both ensemble and single-trajectory (time) averages. We demonstrate nice agreement with extensive simulations for the probability density function, skewness, kurtosis, as well as ensemble and time-averaged mean-squared displacements. We place a specific emphasis on the comparisons between the cases with and without drift.

Identifiants

pubmed: 37723819
doi: 10.1103/PhysRevE.108.024143
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

024143

Auteurs

Yingjie Liang (Y)

College of Mechanics and Materials, Hohai University, 211100 Nanjing, China.
University of Potsdam, Institute of Physics and Astronomy, 14476 Potsdam-Golm, Germany.

Wei Wang (W)

University of Potsdam, Institute of Physics and Astronomy, 14476 Potsdam-Golm, Germany.

Ralf Metzler (R)

University of Potsdam, Institute of Physics and Astronomy, 14476 Potsdam-Golm, Germany.
Asia Pacific Centre for Theoretical Physics, Pohang 37673, Republic of Korea.

Classifications MeSH