Disorder-promoted stability
Abstract
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.
Versions
Related
- Strong disorder and very strong disorder are equivalent for directed polymers
- Structure and Associations of Potentially Traumatic Events and Post-Traumatic Stress Disorder Symptoms in Clinical Populations from Kenya and Uganda
- The transition between order to disorder in the Seppäläinen-Johansson model
- Disorder on the hyperbolic square lattice I: Anderson delocalization and absolutely continuous spectrum
- Spectral Criterion for Disorder-Free Localization of Quantum Walks on Hypercube: QBN Approach
BibTeX
@misc{montanari2026disorderpromoted,
title = {{Disorder-promoted stability}},
author = {Arthur N. Montanari and Pietro Zanin and Adilson E. Motter},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.25226},
eprint = {2609.25226},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.25226},
}
RIS
TY - UNPB
TI - Disorder-promoted stability
AU - Arthur N. Montanari
AU - Pietro Zanin
AU - Adilson E. Motter
PY - 2026
DA - 2026/09/21
PB - arXiv
DO - 10.48550/arxiv.2609.25226
UR - https://arxiv.org/abs/2609.25226
AB - 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.
ER -