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Fractional Brownian motion with random Hurst exponent

  • Fractional Brownian motion, a Gaussian non-Markovian self-similar process with stationary long-correlated increments, has been identified to give rise to the anomalous diffusion behavior in a great variety of physical systems. The correlation and diffusion properties of this random motion are fully characterized by its index of self-similarity or the Hurst exponent. However, recent single-particle tracking experiments in biological cells revealed highly complicated anomalous diffusion phenomena that cannot be attributed to a class of self-similar random processes. Inspired by these observations, we here study the process that preserves the properties of the fractional Brownian motion at a single trajectory level; however, the Hurst index randomly changes from trajectory to trajectory. We provide a general mathematical framework for analytical, numerical, and statistical analysis of the fractional Brownian motion with the random Hurst exponent. The explicit formulas for probability density function, mean-squared displacement,Fractional Brownian motion, a Gaussian non-Markovian self-similar process with stationary long-correlated increments, has been identified to give rise to the anomalous diffusion behavior in a great variety of physical systems. The correlation and diffusion properties of this random motion are fully characterized by its index of self-similarity or the Hurst exponent. However, recent single-particle tracking experiments in biological cells revealed highly complicated anomalous diffusion phenomena that cannot be attributed to a class of self-similar random processes. Inspired by these observations, we here study the process that preserves the properties of the fractional Brownian motion at a single trajectory level; however, the Hurst index randomly changes from trajectory to trajectory. We provide a general mathematical framework for analytical, numerical, and statistical analysis of the fractional Brownian motion with the random Hurst exponent. The explicit formulas for probability density function, mean-squared displacement, and autocovariance function of the increments are presented for three generic distributions of the Hurst exponent, namely, two-point, uniform, and beta distributions. The important features of the process studied here are accelerating diffusion and persistence transition, which we demonstrate analytically and numerically.show moreshow less

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Metadaten
Author details:Michal BalcerekORCiD, Krzysztof BurneckiORCiD, Samudrajit Thapa, Agnieszka WylomanskaORCiD, Aleksei ChechkinORCiDGND
DOI:https://doi.org/10.1063/5.0101913
ISSN:1054-1500
ISSN:1089-7682
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/36182362
Title of parent work (English):Chaos : an interdisciplinary journal of nonlinear science
Subtitle (English):accelerating diffusion and persistence transitions
Publisher:AIP Publishing
Place of publishing:Melville
Publication type:Article
Language:English
Date of first publication:2022/09/13
Publication year:2022
Release date:2024/09/20
Volume:32
Issue:9
Article number:093114
Number of pages:15
Funding institution:Beethoven Grant [DFG-NCN 2016/23/G/ST1/04083]; Pikovsky-Valazzi matching; scholarship, Tel Aviv University; Sackler postdoctoral fellowship;; National Center of Science under Opus Grant [2020/37/B/HS4/00120];; Polish National Agency for Academic Exchange (NAWA)
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
DDC classification:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
Peer review:Referiert
License (German):License LogoKeine öffentliche Lizenz: Unter Urheberrechtsschutz
External remark:Erratum: https://doi.org/10.1063/5.0210418
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