时间粗粒度和缓慢和周期动态的消除与对卷积时间过可观测的泛化的朗格温方程
1Indian Institute of Science, Freie Universität Berlin, Fachbereich Physik, 144195 Berlin, Germany and Centre for Condensed Matter Theory, Department of Physics, Bangalore 560012, India.
对于过的数据,我们得出了一个新的通用朗格温方程 (GLE). 这种方法精确地将复杂的系统分解成不同的缓慢和快速变量,帮助分析实验和模拟数据.
科学领域:
- 统计力学 统计力学
- 计算物理 计算物理
- 物理化学 物理化学
背景情况:
- 一般化的朗格温方程 (GLE) 是描述具有记忆效应的系统的一个基本工具.
- 实验数据和模拟通常涉及光滑或需要分解到不同的时间尺度.
- 现有的方法可能难以准确地分离动态组件或考虑固有的数据平滑.
研究的目的:
- 导出适用于卷积时间过可观测的通用朗格温方程 (GLE).
- 开发一个灵活的框架来分析具有任意卷积过器 (低通,高通等) 的系统. ) 的情况.
- 提供一种方法来准确地将数据分解为服从Liouville动态的缓慢和快速变量.
主要方法:
- 在相位空间中精确投射以导出波器GLE.
- 将一般卷积过器应用于任意的相空间可观测物.
- 过数据的 GLE 参数的积分公式的推导.
主要成果:
- 衍生过器GLE保留了普通GLE的形式,但具有修改的电位,质量和内存摩擦内核.
- 该方法允许通过低通选系统地导出粗粒度模型.
- 证明了数据的精确分解成缓慢和快速的变量,使得非平衡元件的分析.
结论:
- 过投影方法为分析复杂的动态和实验数据提供了一种多功能方法.
- 它为处理短暂或季节性组件提供了不平衡方法的准确替代方案.
- 马科维数据的低通过特别诱导了过器GLE中的指数级衰变的内存内核.
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