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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2401.09993 |
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| _version_ | 1866929214510333952 |
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| author | Dinis, L. Parrondo, J. M. R. |
| author_facet | Dinis, L. Parrondo, J. M. R. |
| contents | Measurement and feedback allows an external agent to extract work from a system in contact with a single thermal bath. The maximum amount of work that can be extracted in a single measurement and the corresponding feedback loop is given by the information acquired via the measurement, a result that manifests the close relation between information theory and stochastic thermodynamics. In this paper we show how to reversibly confine a Brownian particle in an optical tweezer potential and then extract the corresponding increase of the free energy as work. By repeatedly tracking the position of the particle and modifying the potential accordingly, we can extract work optimally even with a high degree of inaccuracy in the measurements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_09993 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Extracting work optimally with imprecise measurements Dinis, L. Parrondo, J. M. R. Statistical Mechanics Measurement and feedback allows an external agent to extract work from a system in contact with a single thermal bath. The maximum amount of work that can be extracted in a single measurement and the corresponding feedback loop is given by the information acquired via the measurement, a result that manifests the close relation between information theory and stochastic thermodynamics. In this paper we show how to reversibly confine a Brownian particle in an optical tweezer potential and then extract the corresponding increase of the free energy as work. By repeatedly tracking the position of the particle and modifying the potential accordingly, we can extract work optimally even with a high degree of inaccuracy in the measurements. |
| title | Extracting work optimally with imprecise measurements |
| topic | Statistical Mechanics |
| url | https://arxiv.org/abs/2401.09993 |