Geometric decomposition of information flow for overdamped Langevin systems and optimal transport in subsystems
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2025
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| author | Ito, Sosuke Maekawa, Yoh Nagayama, Ryuna Dechant, Andreas Yoshimura, Kohei |
| author_facet | Ito, Sosuke Maekawa, Yoh Nagayama, Ryuna Dechant, Andreas Yoshimura, Kohei |
| contents | Information flow between subsystems is a central concept in information thermodynamics, which provides the second-law-like inequalities for subsystems. This paper discusses the geometric decomposition of information flow, which was introduced for Markov jump systems [Y Maekawa, R Nagayama, K Yoshimura and S Ito, arXiv:2509.21985 (2025)], and applies it to overdamped Langevin systems. For overdamped Langevin systems, the geometric decomposition of information flow into excess and housekeeping contributions is related to the conventional definition of the $2$-Wasserstein distance between marginal distributions in optimal transport theory. This formulation offers an optimal-transport interpretation of subsystem dynamics, and this optimal-transport formulation is simpler for overdamped Langevin systems than for general Markov jump systems. It is also possible to handle features that are specific to overdamped Langevin systems, such as representations based on the Koopman mode decomposition, as well as their relationship with the Fisher information matrix. As with the results for Markov jump systems, we generalize the second law of information thermodynamics using housekeeping and excess information flow, leading to the concept of excess and housekeeping demons. We also derive a thermodynamic uncertainty relation and an information-thermodynamic speed limit incorporating excess information flow. These results are illustrated for the Gaussian case, and we discuss the conditions under which the excess and housekeeping demons emerge. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2512_22890 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Geometric decomposition of information flow for overdamped Langevin systems and optimal transport in subsystems Ito, Sosuke Maekawa, Yoh Nagayama, Ryuna Dechant, Andreas Yoshimura, Kohei Statistical Mechanics Information flow between subsystems is a central concept in information thermodynamics, which provides the second-law-like inequalities for subsystems. This paper discusses the geometric decomposition of information flow, which was introduced for Markov jump systems [Y Maekawa, R Nagayama, K Yoshimura and S Ito, arXiv:2509.21985 (2025)], and applies it to overdamped Langevin systems. For overdamped Langevin systems, the geometric decomposition of information flow into excess and housekeeping contributions is related to the conventional definition of the $2$-Wasserstein distance between marginal distributions in optimal transport theory. This formulation offers an optimal-transport interpretation of subsystem dynamics, and this optimal-transport formulation is simpler for overdamped Langevin systems than for general Markov jump systems. It is also possible to handle features that are specific to overdamped Langevin systems, such as representations based on the Koopman mode decomposition, as well as their relationship with the Fisher information matrix. As with the results for Markov jump systems, we generalize the second law of information thermodynamics using housekeeping and excess information flow, leading to the concept of excess and housekeeping demons. We also derive a thermodynamic uncertainty relation and an information-thermodynamic speed limit incorporating excess information flow. These results are illustrated for the Gaussian case, and we discuss the conditions under which the excess and housekeeping demons emerge. |
| title | Geometric decomposition of information flow for overdamped Langevin systems and optimal transport in subsystems |
| topic | Statistical Mechanics |
| url | https://arxiv.org/abs/2512.22890 |