Hunting for Maxwell's Demon in the Wild
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866911663380234240 |
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| author | Buisson, Johan du Ehrich, Jannik Leighton, Matthew P. Kundu, Avijit Saha, Tushar K. Bechhoefer, John Sivak, David A. |
| author_facet | Buisson, Johan du Ehrich, Jannik Leighton, Matthew P. Kundu, Avijit Saha, Tushar K. Bechhoefer, John Sivak, David A. |
| contents | The paradox of Maxwell's demon motivated the development of information thermodynamics and the creation of nanoscale information engines. We now understand that machines such as the molecular motors within cells can in principle harvest fluctuations and thereby operate as a Maxwell demon -- but do they? Answering this question would seemingly require simultaneous measurement of all system degrees of freedom, which is generally intractable in single-molecule experiments. Here, we derive a simple statistical estimator to infer both the direction and magnitude of subsystem heat flows, and thus determine whether -- and how strongly -- a motor operates as a Maxwell demon. The estimator uses only trajectory measurements for a single degree of freedom. Simulating both colloidal information engines and kinesin molecular motors, we show that our estimator can precisely and accurately detect Maxwell-demon behavior with experimentally accessible resolution and quantities of data. Moreover, we find that kinesin transitions to a Maxwell-demon mechanism in the presence of nonequilibrium noise, with a corresponding increase in velocity consistent with experiments. These findings suggest that molecular motors may have evolved to leverage active fluctuations within cells. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_11329 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Hunting for Maxwell's Demon in the Wild Buisson, Johan du Ehrich, Jannik Leighton, Matthew P. Kundu, Avijit Saha, Tushar K. Bechhoefer, John Sivak, David A. Statistical Mechanics Biological Physics The paradox of Maxwell's demon motivated the development of information thermodynamics and the creation of nanoscale information engines. We now understand that machines such as the molecular motors within cells can in principle harvest fluctuations and thereby operate as a Maxwell demon -- but do they? Answering this question would seemingly require simultaneous measurement of all system degrees of freedom, which is generally intractable in single-molecule experiments. Here, we derive a simple statistical estimator to infer both the direction and magnitude of subsystem heat flows, and thus determine whether -- and how strongly -- a motor operates as a Maxwell demon. The estimator uses only trajectory measurements for a single degree of freedom. Simulating both colloidal information engines and kinesin molecular motors, we show that our estimator can precisely and accurately detect Maxwell-demon behavior with experimentally accessible resolution and quantities of data. Moreover, we find that kinesin transitions to a Maxwell-demon mechanism in the presence of nonequilibrium noise, with a corresponding increase in velocity consistent with experiments. These findings suggest that molecular motors may have evolved to leverage active fluctuations within cells. |
| title | Hunting for Maxwell's Demon in the Wild |
| topic | Statistical Mechanics Biological Physics |
| url | https://arxiv.org/abs/2504.11329 |