Superstatistical generalised Langevin equation
- Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellentRecent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.…
Verfasserangaben: | Jakub ŚlęzakORCiD, Ralf MetzlerORCiDGND, Marcin Magdziarz |
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DOI: | https://doi.org/10.1088/1367-2630/aaa3d4 |
ISSN: | 1367-2630 |
Titel des übergeordneten Werks (Englisch): | New Journal of Physics |
Untertitel (Englisch): | non-Gaussian viscoelastic anomalous diffusion |
Verlag: | Deutsche Physikalische Gesellschaft / Institute of Physics |
Verlagsort: | Bad Honnef und London |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 07.02.2018 |
Erscheinungsjahr: | 2018 |
Veröffentlichende Institution: | Universität Potsdam |
Datum der Freischaltung: | 28.03.2018 |
Freies Schlagwort / Tag: | anomalous diffusion; generalised langevin equation; non-Gaussian diffusion; superstatistics |
Band: | 20 |
Ausgabe: | 023026 |
Seitenanzahl: | 25 |
Erste Seite: | 1 |
Letzte Seite: | 25 |
Fördernummer: | PA 2018_03 |
Organisationseinheiten: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie |
DDC-Klassifikation: | 5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik |
Peer Review: | Referiert |
Fördermittelquelle: | Publikationsfonds der Universität Potsdam |
Publikationsweg: | Open Access |
Lizenz (Englisch): | Creative Commons - Namensnennung 3.0 Unported |
Externe Anmerkung: | Zweitveröffentlichung in der Schriftenreihe Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe ; 413 |