AI 中文总结
本研究推翻“节点异质性抑制稳定性”的旧论，证明在高维动力学或非互易作用下，非厄米性使无序成为增强复杂系统稳定性的普遍资源。
AI 中文摘要
以往关于网络动力学的研究表明，节点间的异质性会抑制稳定性，这与自然界和工程系统中普遍存在的固有异质性现象相矛盾。在此，我们证明这一结论源于为数学可处理性而引入的模型简化，当节点动力学为高维并产生非厄米雅可比矩阵时，该结论不再成立。在包括神经、电网和材料网络在内的此类系统中，节点异质性反而能增强稳定性，即使参数随机无序也是如此。非厄米性也是网络异质性稳定效应的基础，这种效应甚至可通过非互易相互作用在一维节点动力学中出现，如生态网络所示。我们的框架揭示，无序并非负担，而是稳定复杂系统的一般性资源。
英文摘要
Previous studies of network dynamics have suggested that heterogeneity among nodes inhibits stability, at odds with the ubiquity of inherently heterogeneous natural and engineered systems. Here, we show that this conclusion arises from model reductions introduced for mathematical tractability and breaks down when nodal dynamics are higher-dimensional, yielding non-Hermitian Jacobians. In such systems, including neural, power-grid, and material networks, nodal heterogeneity can instead enhance stability, even when parameters are randomly disordered. Non-Hermiticity also underlies the stabilizing effects of network heterogeneity, which can arise even in one-dimensional nodal dynamics through nonreciprocal interactions, as shown for ecological networks. Our framework reveals disorder not as a liability but as a general resource for stabilizing complex systems.
Journal refScience 393, 6817:1241-1249 (2026)
