Literature DB >> 20866798

Fractional Lévy stable motion can model subdiffusive dynamics.

Krzysztof Burnecki1, Aleksander Weron.   

Abstract

We show in this paper that the sample (time average) mean-squared displacement (MSD) of the fractional Lévy α -stable motion behaves very differently from the corresponding ensemble average (second moment). While the ensemble average MSD diverges for α<2 , the sample MSD may exhibit either subdiffusion, normal diffusion, or superdiffusion. Thus, H -self-similar Lévy stable processes can model either a subdiffusive, diffusive or superdiffusive dynamics in the sense of sample MSD. We show that the character of the process is controlled by a sign of the memory parameter d=H-1/α . We also introduce a sample p -variation dynamics test which allows to distinguish between two models of subdiffusive dynamics. Finally, we illustrate a subdiffusive behavior of the fractional Lévy stable motion on biological data describing the motion of individual fluorescently labeled mRNA molecules inside live E. coli cells, but it may concern many other fields of contemporary experimental physics.

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Year:  2010        PMID: 20866798     DOI: 10.1103/PhysRevE.82.021130

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  7 in total

1.  Universal algorithm for identification of fractional Brownian motion. A case of telomere subdiffusion.

Authors:  Krzysztof Burnecki; Eldad Kepten; Joanna Janczura; Irena Bronshtein; Yuval Garini; Aleksander Weron
Journal:  Biophys J       Date:  2012-11-07       Impact factor: 4.033

2.  Guidelines for the fitting of anomalous diffusion mean square displacement graphs from single particle tracking experiments.

Authors:  Eldad Kepten; Aleksander Weron; Grzegorz Sikora; Krzysztof Burnecki; Yuval Garini
Journal:  PLoS One       Date:  2015-02-13       Impact factor: 3.240

3.  Estimating the anomalous diffusion exponent for single particle tracking data with measurement errors - An alternative approach.

Authors:  Krzysztof Burnecki; Eldad Kepten; Yuval Garini; Grzegorz Sikora; Aleksander Weron
Journal:  Sci Rep       Date:  2015-06-11       Impact factor: 4.379

4.  Discriminating between Light- and Heavy-Tailed Distributions with Limit Theorem.

Authors:  Krzysztof Burnecki; Agnieszka Wylomanska; Aleksei Chechkin
Journal:  PLoS One       Date:  2015-12-23       Impact factor: 3.240

5.  Range Entropy: A Bridge between Signal Complexity and Self-Similarity.

Authors:  Amir Omidvarnia; Mostefa Mesbah; Mangor Pedersen; Graeme Jackson
Journal:  Entropy (Basel)       Date:  2018-12-13       Impact factor: 2.524

6.  Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model.

Authors:  Lei Du; Zifang Zhao; Boyan Xu; Wenwen Gao; Xiuxiu Liu; Yue Chen; Yige Wang; Jian Liu; Bing Liu; Shilong Sun; Guolin Ma; Jiahong Gao
Journal:  Front Aging Neurosci       Date:  2020-11-19       Impact factor: 5.750

7.  Impact of Feature Choice on Machine Learning Classification of Fractional Anomalous Diffusion.

Authors:  Hanna Loch-Olszewska; Janusz Szwabiński
Journal:  Entropy (Basel)       Date:  2020-12-19       Impact factor: 2.524

  7 in total

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