Disorder-promoted stability
Abstract
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.
Fields of Study & Subjects
Neural Networks and Reservoir Computing
Advanced Graph Neural Networks
Neural dynamics and brain function
Publication details
- Journal / source
- Science
- Publisher
- American Association for the Advancement of Science (AAAS)
- Volume
- 393
- Issue
- 6817
- Pages
- 1241–1249
- Publication date
- 17 September 2026
- Language
- EN