在平衡状态下,分区系统的信息内容和最大
Holger Metzler1,2,3,4, Carlos A Sierra1
1Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10, 07745 Jena, Germany.
Entropy (Basel, Switzerland)
|October 28, 2025
概括
本研究将信息理论应用于质量平衡的分区系统,使用马尔科夫链来量化轨迹的不确定性和过渡. 这种方法揭示了系统结构,并有助于模型选择,克服了经典测量的局限性.
科学领域:
- 复杂的系统复杂的系统.
- 信息理论 信息理论
- 统计力学 统计力学
背景情况:
- 对于散散动态的质量平衡区间系统,经典的度措施失败了.
- 开放的隔间系统被重新解释为吸收连续时间的马尔科夫链.
研究的目的:
- 将信息理论原则应用于决定性动态系统.
- 在分区系统中量化轨迹不确定性和过渡不确定性.
- 为了扩展模型选择的最大原则.
主要方法:
- 将分隔系统解释为连续时间的马尔科夫链.
- 应用香农的信息来推导路径和率.
- 为这些在平衡中的数量推导闭式表达式.
主要成果:
- 开发了一个新的信息理论框架,用于区块动态.
- 导出路径和率的闭式表达式.
- 扩展了最大原则 (MaxEnt) 用于模型选择.
结论:
- 该框架系统地解决了分区模型中的等终性.
- 揭示复杂系统的隐藏结构性质,比如全球碳循环.
- 提供了分析决定性动态系统的新视角.
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