可能性
理论(学习稳定性)
节的
动力学(音乐)
计算机科学
统计物理学
生物系统
资源(消歧)
异构网络
工作(物理)
复杂网络
生物网络
物理
自然(考古学)
责任
稳定性条件
数学
进化动力学
网络动力学
网络模型
作者
Arthur N. Montanari,Pietro Zanin,Adilson E. Motter
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2026-09-17
卷期号:393 (6817): 1241-1249
被引量:1
标识
DOI:10.1126/science.aeg3946
摘要
Previous studies of network dynamics have suggested that heterogeneity among nodes inhibits stability, which is 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.
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