科尔摩戈罗夫模式和跳跃扩散模型的线性响应
Mickaël D Chekroun1,2, Niccolò Zagli3,4, Valerio Lucarini4
1Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095-1565, United States of America.
Reports on progress in physics. Physical Society (Great Britain)
|November 20, 2025
概括
我们将线性响应理论概括为复杂系统的混合跳转扩散模型. 这可以量化不确定性,并预测气候和其他领域的动态变化.
科学领域:
- 复杂系统动力学 复杂系统动力学
- 非线性随机过程 非线性随机过程
- 气候建模气候模型
背景情况:
- 线性响应理论 (LRT) 对于理解扰动下的系统动态至关重要.
- 混合跳转扩散模型,结合高斯和莱维噪声,对于参数化复杂系统中未解决的尺度至关重要.
- 现有的LRT框架经常与相互作用的噪声强迫和非线性动态的复杂性作斗争.
研究的目的:
- 为混合跳转扩散模型推广线性响应理论 (LRT).
- 为了推导出全面的响应公式,考虑波动的漂移和跳跃规律.
- 为量化不确定性和测量复杂系统中的动态变化提供统一的框架.
主要方法:
- 对于混合跳转扩散过程的科尔摩戈罗夫运算子和格林函数的概括.
- 导出新的波动-消散关系.
- 将系统响应分解为来自科尔摩戈罗夫运算机自身模式的贡献.
主要成果:
- 一个通用的LRT框架适用于与互动的高斯和莱维噪声的非线性动态.
- 用于量化参数化中的不确定性和评估动态变化的新公式.
- 在厄尔尼诺-南方振荡和能量平衡气候模型中证明了预测能力.
结论:
- 一般化的LRT为分析混合噪声的复杂系统提供了一个强大的工具.
- 该框架增强了气候建模,预测和对气候敏感性和临界点的理解.
- 潜在的应用范围包括流行病学,生物学,金融和定量社会科学.
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