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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Accesso online: | https://arxiv.org/abs/2506.02195 |
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| _version_ | 1866915320212488192 |
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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 |