在外模型中,多模式相关性和流的
Gregory Falkovich1,2, Yotam Kadish1, Natalia Vladimirova2,3
1Weizmann Institute of Science, Rehovot 76100, Israel.
Physical review. E
|August 16, 2023
概括
多模式相关性为流研究提供了一个新的镜头,揭示了隐藏的状态. 这种方法应用于外模型,显示高阶相关性与模式数增长,类似于纠.
科学领域:
- * 流体动力学 流体动力学
- * 统计物理学的统计物理.
背景情况:
- * 传统的流研究往往侧重于单模式统计.
- *理解复杂的动荡状态需要分析多种模式之间的相互作用.
研究的目的:
- * 引入多模式相关性作为一种新的方法来表征流.
- * 在接近热平衡的外模型中研究这些相关性的行为.
主要方法:
- *将多模式相关性分析应用于流的外模型.
- *分析推导和数字确认累积增长的缩放规律.
- * 用相对来比较多模分布与高斯近似.
主要成果:
- * 随着模式数量的增加,单模统计方法接近高斯式.
- * 能量流 (三种模式的累积) 保持不变.
- * 较高阶的多模累积物表现出随着顺序的增长,遵循一个衍生的缩放定律.
- * 完全分布和高斯分布之间的相对与模式的数量以对数方式增长.
结论:
- *多模相关性为特征流提供了一种新的,强大的方法.
- *这种方法可以使动荡状态被分为普遍性类别.
- *这些发现表明,流与关键现象中的纠变等概念之间存在潜在的联系.
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