発表者名 |
東條 開斗 |
指導教員名 |
沙川 貴大 教授 |
発表題目(英語) |
Optimizing optimal transport: role of final distributions in finite-time thermodynamics |
要旨(英語) |
In thermodynamics, the second law is considered the most fundamental principle. However, equality is achieved only via a quasi-static limit, which is impractical for real-world applications. It is well established that the minimum entropy production which is necessary for transitions between fixed initial and final states in finite time and the protocol achieving it can be derived using optimal transport theory [1].
When multiple final states can fulfill a desired objective, optimal transport allows the final state to be adjusted to further minimize thermodynamic costs. In contrast to previous studies that minimized costs for specific tasks like information erasure, measurement, and feedback in particular settings [2,3,4], our research introduces a unified framework for thermodynamic optimization in overdamped Langevin systems. This framework optimizes thermodynamic costs such as entropy production and work in finite time while ensuring that state-dependent quantities like expectation values of physical quantities or mutual information reach their desired targets. The optimization problem is formulated as a variational problem over transport maps. Consequently, our approach addresses various settings such as particle transport, fluctuation reduction processes, information erasure, measurement, and feedback.
In this presentation, we will introduce the basic concepts of stochastic thermodynamics and then present results of our study.
[1] E. Aurell, K. Gawedzki, C. Meija-Monasterio, R. Mohayaee, and P. Muratore-Ginanneschi, Journal of Statistical Physics 147, 487 (2012).
[2] K. Proesmans, J. Ehrich, and J. Bechhoefer, Phys. Rev. Lett. 125, 100602 (2020).
[3] R. Nagase and T. Sagawa, Phys. Rev. Res. 6, 033239 (2024).
[4] R. Nagase and T. Sagawa, arxiv:2503.12802 (2025). |
発表言語 |
日本語 |