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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7517236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT wangwanli largedeviationsforcontinuoustimerandomwalks AT barkaieli largedeviationsforcontinuoustimerandomwalks AT burovstanislav largedeviationsforcontinuoustimerandomwalks |