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Large Deviations for Continuous Time Random Walks

Recently observation of random walks in complex environments like the cell and other glassy systems revealed that the spreading of particles, at its tails, follows a spatial exponential decay instead of the canonical Gaussian. We use the widely applicable continuous time random walk model and obtain...

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Detalles Bibliográficos
Autores principales: Wang, Wanli, Barkai, Eli, Burov, Stanislav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517236/
https://www.ncbi.nlm.nih.gov/pubmed/33286470
http://dx.doi.org/10.3390/e22060697
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author Wang, Wanli
Barkai, Eli
Burov, Stanislav
author_facet Wang, Wanli
Barkai, Eli
Burov, Stanislav
author_sort Wang, Wanli
collection PubMed
description Recently observation of random walks in complex environments like the cell and other glassy systems revealed that the spreading of particles, at its tails, follows a spatial exponential decay instead of the canonical Gaussian. We use the widely applicable continuous time random walk model and obtain the large deviation description of the propagator. Under mild conditions that the microscopic jump lengths distribution is decaying exponentially or faster i.e., Lévy like power law distributed jump lengths are excluded, and that the distribution of the waiting times is analytical for short waiting times, the spreading of particles follows an exponential decay at large distances, with a logarithmic correction. Here we show how anti-bunching of jump events reduces the effect, while bunching and intermittency enhances it. We employ exact solutions of the continuous time random walk model to test the large deviation theory.
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spelling pubmed-75172362020-11-09 Large Deviations for Continuous Time Random Walks Wang, Wanli Barkai, Eli Burov, Stanislav Entropy (Basel) Article Recently observation of random walks in complex environments like the cell and other glassy systems revealed that the spreading of particles, at its tails, follows a spatial exponential decay instead of the canonical Gaussian. We use the widely applicable continuous time random walk model and obtain the large deviation description of the propagator. Under mild conditions that the microscopic jump lengths distribution is decaying exponentially or faster i.e., Lévy like power law distributed jump lengths are excluded, and that the distribution of the waiting times is analytical for short waiting times, the spreading of particles follows an exponential decay at large distances, with a logarithmic correction. Here we show how anti-bunching of jump events reduces the effect, while bunching and intermittency enhances it. We employ exact solutions of the continuous time random walk model to test the large deviation theory. MDPI 2020-06-22 /pmc/articles/PMC7517236/ /pubmed/33286470 http://dx.doi.org/10.3390/e22060697 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Wanli
Barkai, Eli
Burov, Stanislav
Large Deviations for Continuous Time Random Walks
title Large Deviations for Continuous Time Random Walks
title_full Large Deviations for Continuous Time Random Walks
title_fullStr Large Deviations for Continuous Time Random Walks
title_full_unstemmed Large Deviations for Continuous Time Random Walks
title_short Large Deviations for Continuous Time Random Walks
title_sort large deviations for continuous time random walks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517236/
https://www.ncbi.nlm.nih.gov/pubmed/33286470
http://dx.doi.org/10.3390/e22060697
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