发表机构
University of Copenhagen（哥本哈根大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究探讨高维复杂系统中维度、惯性与噪声对预警信号可检测性的影响，发现预警信号的存在依赖系统几何与随机强迫，未检测到预警信号不代表临界转变未临近。
AI 中文摘要
方差和自相关性增大等预警信号（EWS）被广泛用于预测与鞍结分岔相关的临界转变，但现实系统常为高维多尺度，可能改变EWS的经典行为。本文研究维度、惯性和红噪声如何影响临界点前EWS的可检测性：当观测未对齐临界方向时，正交方向的稳定动力学可掩盖EWS直至分岔附近；二阶阻尼动力学修改自相关结构，可增强或减弱临界减速的特征；还研究色噪声对EWS的影响。结果表明，EWS的存在及强度并非临界系统的普遍属性，而是高度依赖系统几何与随机强迫，意味着未检测到EWS未必排除临界转变临近的可能。
英文摘要
Early warning signals (EWS), such as increasing variance and autocorrelation, are widely used to anticipate critical transitions associated with saddle-node bifurcations. However, real-world systems are often high-dimensional and multiscale, potentially altering the classical behavior of EWS. Here, we investigate how dimensionality, inertia, and red noise influence the detectability of EWS prior to tipping points. We show that when observations are not aligned with the critical direction, stable dynamics in orthogonal directions can mask EWS until very near the bifurcation. We further demonstrate that second-order dynamics with damping modify the autocorrelation structure and may either enhance or reduce signatures of critical slowing down. Finally, we study how colored noise influences EWS. Our results show that the presence and strength of EWS are not universal properties of tipping systems but depend critically on system geometry and stochastic forcing, implying that the absence of detectable EWS does not necessarily rule out an approaching critical transition.
Comments16 pages, 5 figures
