15:45 〜 16:00
[ACG47-14] 気候システムにおける情報エネルギー変換：マクスウェル悪魔としての境界流同期
★招待講演
キーワード：同期、黒潮、メキシコ湾流、確率微分方程式、ゆらぎの熱力学、非平衡物理
The climate system consists of components on various timescales, where short-timescale variations can be regarded as stochastic noise relative to longer-timescale dynamics (Hasselmann 1976). Generally, such noise induces only random back-and-forth movements without producing net directional changes. However, net displacement can be extracted when information about the system's state is utilized. This process, known as information-to-energy conversion, has been experimentally demonstrated in laboratory settings (Toyabe et al. 2010). Our research shows that this information-to-energy conversion can also occur autonomously in the climate system through synchronization (Yasuda and Kohyama 2025).
Specifically, we focus on the synchronization of sea surface temperatures (SSTs) between the Gulf Stream and the Kuroshio Current, referred to as boundary current synchronization (BCS; Kohyama et al. 2021). To describe the BCS, we employ a bivariate stochastic differential equation, with coefficients estimated from observational and numerical simulation data.
The estimated equation is interpreted as a Maxwell's demon system. Maxwell's demon is a classic problem in physics that explains how ordered motion can be extracted from random fluctuations (Shiraishi 2023). A Maxwell's demon system consists of two subsystems: a "Demon" and a "Particle." The Demon measures the Particle and applies feedback to extract coherent directional motions from random fluctuations of the Particle. In the BCS, the Gulf Stream plays the role of the Particle, and the Kuroshio Current acts as the Demon. This interpretation reveals the asymmetric roles of the two ocean currents. The Gulf Stream forces the SST of the Kuroshio Current to be in phase, while the Kuroshio Current maintains the phase by interfering with the relaxation of the Gulf Stream SST. When the Gulf Stream and the Kuroshio Current are coupled in an appropriate parameter regime, synchronization is realized with atmospheric and oceanic fluctuations as the driving source. This synchronization demonstrates how small-scale fluctuations can be converted into coherent variations (i.e., information-to-energy conversion).
References
[1] Hasselmann (1976), Tellus, 28 (6), 473–485.
[2] Toyabe et al. (2010), Nature Physics, 6 (12), 988–992.
[3] Yasuda and Kohyama (2025), arXiv:2408.01133 (in press, Journal of Climate).
[4] Kohyama et al. (2021), Science, 374, 341-346.
[5] Shiraishi (2023), Springer.
Specifically, we focus on the synchronization of sea surface temperatures (SSTs) between the Gulf Stream and the Kuroshio Current, referred to as boundary current synchronization (BCS; Kohyama et al. 2021). To describe the BCS, we employ a bivariate stochastic differential equation, with coefficients estimated from observational and numerical simulation data.
The estimated equation is interpreted as a Maxwell's demon system. Maxwell's demon is a classic problem in physics that explains how ordered motion can be extracted from random fluctuations (Shiraishi 2023). A Maxwell's demon system consists of two subsystems: a "Demon" and a "Particle." The Demon measures the Particle and applies feedback to extract coherent directional motions from random fluctuations of the Particle. In the BCS, the Gulf Stream plays the role of the Particle, and the Kuroshio Current acts as the Demon. This interpretation reveals the asymmetric roles of the two ocean currents. The Gulf Stream forces the SST of the Kuroshio Current to be in phase, while the Kuroshio Current maintains the phase by interfering with the relaxation of the Gulf Stream SST. When the Gulf Stream and the Kuroshio Current are coupled in an appropriate parameter regime, synchronization is realized with atmospheric and oceanic fluctuations as the driving source. This synchronization demonstrates how small-scale fluctuations can be converted into coherent variations (i.e., information-to-energy conversion).
References
[1] Hasselmann (1976), Tellus, 28 (6), 473–485.
[2] Toyabe et al. (2010), Nature Physics, 6 (12), 988–992.
[3] Yasuda and Kohyama (2025), arXiv:2408.01133 (in press, Journal of Climate).
[4] Kohyama et al. (2021), Science, 374, 341-346.
[5] Shiraishi (2023), Springer.