Geometric decomposition of information flow: New insights into information thermodynamics
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914535943700480 |
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| author | Maekawa, Yoh Nagayama, Ryuna Yoshimura, Kohei Ito, Sosuke |
| author_facet | Maekawa, Yoh Nagayama, Ryuna Yoshimura, Kohei Ito, Sosuke |
| contents | We propose a decomposition of information flow into housekeeping and excess components for autonomous bipartite systems described by Markov jump processes. We introduce this decomposition using the geometric structure of probability currents and the conjugate thermodynamic forces. The housekeeping component arises from cyclic modes caused by violations of detailed balance and maintains the correlations between the two subsystems. In contrast, the excess component arises from conservative forces and alters the mutual information between the two subsystems. With this decomposition, we generalize previous results, such as the second law of information thermodynamics, the cyclic decomposition, and the information-thermodynamic extensions of thermodynamic trade-off relations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_21985 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Geometric decomposition of information flow: New insights into information thermodynamics Maekawa, Yoh Nagayama, Ryuna Yoshimura, Kohei Ito, Sosuke Statistical Mechanics We propose a decomposition of information flow into housekeeping and excess components for autonomous bipartite systems described by Markov jump processes. We introduce this decomposition using the geometric structure of probability currents and the conjugate thermodynamic forces. The housekeeping component arises from cyclic modes caused by violations of detailed balance and maintains the correlations between the two subsystems. In contrast, the excess component arises from conservative forces and alters the mutual information between the two subsystems. With this decomposition, we generalize previous results, such as the second law of information thermodynamics, the cyclic decomposition, and the information-thermodynamic extensions of thermodynamic trade-off relations. |
| title | Geometric decomposition of information flow: New insights into information thermodynamics |
| topic | Statistical Mechanics |
| url | https://arxiv.org/abs/2509.21985 |