在低雷诺兹数下进行信息最佳混合
Luca Cocconi1, Yihong Shi1, Andrej Vilfan2
1Max Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany.
Physical review letters
|August 4, 2025
概括
研究人员开发了一种新的方法来测量使用相互信息的混合效率. 这种方法揭示了在低雷诺斯数系统中混合的通用,时间逆转对称的最佳协议.
科学领域:
- 物理 物理学 物理
- 统计力学 统计力学
- 流体动力学 流体动力学
背景情况:
- 在微流体和软物质中,混合效率至关重要.
- 低雷诺兹数流由斯托克斯方程控制,表现出动力学可逆性.
- 量化混合效率通常需要假设或特定的系统知识.
研究的目的:
- 引入一种普遍的,无假设的混合效率衡量标准.
- 确定在平面剪切流中混合的最佳控制协议.
- 在不平衡系统中确定信息删除的最低能源成本.
主要方法:
- 使用混合前和混合后粒子位置之间的相互信息.
- 导出一个紧的表达式,作为切割协议的函数来表达相互信息.
- 解决极端化问题,以在剪切和散射约束下实现最佳控制.
主要成果:
- 相互信息提供了混合效率的普遍衡量标准,并考虑了斯托克斯方程的可逆性.
- 导出最佳的混合协议,并发现它们是通用的和时间逆转对称的.
- 对于漂移扩散系统中信息删除的最低能源成本是建立的.
结论:
- 相互信息是量化低雷诺兹数流中的混合的一个强大的工具.
- 最佳的混合策略本质上是时间逆转对称和普遍的.
- 这项工作为不平衡系统中的信息热力学提供了基本的见解.
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