Anomalous diffusion, nonergodicity, non-Gaussianity, and aging of fractional Brownian motion with nonlinear clocks

Yingjie Liang, Wei Wang, Ralf Metzler, and Andrey G. Cherstvy
Phys. Rev. E 108, 034113 – Published 13 September 2023

Abstract

How do nonlinear clocks in time and/or space affect the fundamental properties of a stochastic process? Specifically, how precisely may ergodic processes such as fractional Brownian motion (FBM) acquire predictable nonergodic and aging features being subjected to such conditions? We address these questions in the current study. To describe different types of non-Brownian motion of particles—including power-law anomalous, ultraslow or logarithmic, as well as superfast or exponential diffusion—we here develop and analyze a generalized stochastic process of scaled-fractional Brownian motion (SFBM). The time- and space-SFBM processes are, respectively, constructed based on FBM running with nonlinear time and space clocks. The fundamental statistical characteristics such as non-Gaussianity of particle displacements, nonergodicity, as well as aging are quantified for time- and space-SFBM by selecting different clocks. The latter parametrize power-law anomalous, ultraslow, and superfast diffusion. The results of our computer simulations are fully consistent with the analytical predictions for several functional forms of clocks. We thoroughly examine the behaviors of the probability-density function, the mean-squared displacement, the time-averaged mean-squared displacement, as well as the aging factor. Our results are applicable for rationalizing the impact of nonlinear time and space properties superimposed onto the FBM-type dynamics. SFBM offers a general framework for a universal and more precise model-based description of anomalous, nonergodic, non-Gaussian, and aging diffusion in single-molecule-tracking observations.

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  • Received 17 April 2023
  • Accepted 7 August 2023

DOI:https://doi.org/10.1103/PhysRevE.108.034113

©2023 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsNonlinear Dynamics

Authors & Affiliations

Yingjie Liang1,2,*, Wei Wang2,†, Ralf Metzler2,3,‡, and Andrey G. Cherstvy2,§

  • 1College of Mechanics and Materials, Hohai University, 211100 Nanjing, China
  • 2Institute of Physics and Astronomy, University of Potsdam, 14476 Potsdam, Germany
  • 3Asia Pacific Center for Theoretical Physics, Pohang 37673, Republic of Korea

  • *liangyj@hhu.edu.cn
  • weiwangnuaa@gmail.com
  • rmetzler@uni-potsdam.de
  • §a.cherstvy@gmail.com

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Issue

Vol. 108, Iss. 3 — September 2023

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