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Autori principali: Makarov, Dmitrii E., Sollich, Peter
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2506.02195
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author Makarov, Dmitrii E.
Sollich, Peter
author_facet Makarov, Dmitrii E.
Sollich, Peter
contents Molecules in dense environments, such as biological cells, are subjected to forces that fluctuate both in time and in space. While spatial fluctuations are captured by Lifson-Jackson-Zwanzig's model of "diffusion in a rough potential", and temporal fluctuations are often viewed as leading to additional friction effects, a unified view where the environment fluctuates both in time and in space is currently lacking. Here we introduce a discrete-state model of a landscape fluctuating both in time and in space. Importantly, the model accounts for the back-reaction of the diffusing particle on the landscape. As a result we find, surprisingly, that many features of the observable dynamics do not depend on the temporal fluctuation timescales and are already captured by the model of diffusion in a rough potential, even though this assumes a static energy landscape.
format Preprint
id arxiv_https___arxiv_org_abs_2506_02195
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Static vs dynamic rough energy landscapes: Where is diffusion faster?
Makarov, Dmitrii E.
Sollich, Peter
Statistical Mechanics
Biological Physics
Chemical Physics
Molecules in dense environments, such as biological cells, are subjected to forces that fluctuate both in time and in space. While spatial fluctuations are captured by Lifson-Jackson-Zwanzig's model of "diffusion in a rough potential", and temporal fluctuations are often viewed as leading to additional friction effects, a unified view where the environment fluctuates both in time and in space is currently lacking. Here we introduce a discrete-state model of a landscape fluctuating both in time and in space. Importantly, the model accounts for the back-reaction of the diffusing particle on the landscape. As a result we find, surprisingly, that many features of the observable dynamics do not depend on the temporal fluctuation timescales and are already captured by the model of diffusion in a rough potential, even though this assumes a static energy landscape.
title Static vs dynamic rough energy landscapes: Where is diffusion faster?
topic Statistical Mechanics
Biological Physics
Chemical Physics
url https://arxiv.org/abs/2506.02195