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Crossover from anomalous to normal diffusion

  • Abstract The emerging diffusive dynamics in many complex systems show a characteristic crossover behaviour from anomalous to normal diffusion which is otherwise fitted by two independent power-laws. A prominent example for a subdiffusive–diffusive crossover are viscoelastic systems such as lipid bilayer membranes, while superdiffusive–diffusive crossovers occur in systems of actively moving biological cells. We here consider the general dynamics of a stochastic particle driven by so-called tempered fractional Gaussian noise, that is noise with Gaussian amplitude and power-law correlations, which are cut off at some mesoscopic time scale. Concretely we consider such noise with built-in exponential or power-law tempering, driving an overdamped Langevin equation (fractional Brownian motion) and fractional Langevin equation motion. We derive explicit expressions for the mean squared displacement and correlation functions, including different shapes of the crossover behaviour depending on the concrete tempering, and discuss the physicalAbstract The emerging diffusive dynamics in many complex systems show a characteristic crossover behaviour from anomalous to normal diffusion which is otherwise fitted by two independent power-laws. A prominent example for a subdiffusive–diffusive crossover are viscoelastic systems such as lipid bilayer membranes, while superdiffusive–diffusive crossovers occur in systems of actively moving biological cells. We here consider the general dynamics of a stochastic particle driven by so-called tempered fractional Gaussian noise, that is noise with Gaussian amplitude and power-law correlations, which are cut off at some mesoscopic time scale. Concretely we consider such noise with built-in exponential or power-law tempering, driving an overdamped Langevin equation (fractional Brownian motion) and fractional Langevin equation motion. We derive explicit expressions for the mean squared displacement and correlation functions, including different shapes of the crossover behaviour depending on the concrete tempering, and discuss the physical meaning of the tempering. In the case of power-law tempering we also find a crossover behaviour from faster to slower superdiffusion and slower to faster subdiffusion. As a direct application of our model we demonstrate that the obtained dynamics quantitatively describes the subdiffusion–diffusion and subdiffusion–subdiffusion crossover in lipid bilayer systems. We also show that a model of tempered fractional Brownian motion recently proposed by Sabzikar and Meerschaert leads to physically very different behaviour with a seemingly paradoxical ballistic long time scaling.zeige mehrzeige weniger

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Verfasserangaben:Daniel Molina-Garcia, Trifce SandevORCiD, Hadiseh SafdariORCiD, Gianni Pagnini, Aleksei V. ChechkinORCiDGND, Ralf MetzlerORCiDGND
URN:urn:nbn:de:kobv:517-opus4-422590
DOI:https://doi.org/10.25932/publishup-42259
ISSN:1866-8372
Titel des übergeordneten Werks (Englisch):Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
Untertitel (Englisch):truncated power-law noise correlations and applications to dynamics in lipid bilayers
Schriftenreihe (Bandnummer):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (507)
Publikationstyp:Postprint
Sprache:Englisch
Datum der Erstveröffentlichung:15.01.2019
Erscheinungsjahr:2019
Veröffentlichende Institution:Universität Potsdam
Datum der Freischaltung:15.01.2019
Freies Schlagwort / Tag:anomalous diffusion; lipid bilayer membrane dynamics; truncated power-law correlated noise
Ausgabe:507
Seitenanzahl:28
Quelle:New Journal of Physics 20 (2018) Art. 103027 DOI: 10.1088/1367-2630/aae4b2
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
Peer Review:Referiert
Publikationsweg:Open Access
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
Externe Anmerkung:Bibliographieeintrag der Originalveröffentlichung/Quelle
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