Litcius/Paper detail

Network structural origin of instabilities in large complex systems

Chao Duan, Takashi Nishikawa, Deniz Eroglu, Adilson E. Motter

2022Science Advances32 citationsDOIOpen Access PDF

Abstract

A central issue in the study of large complex network systems, such as power grids, financial networks, and ecological systems, is to understand their response to dynamical perturbations. Recent studies recognize that many real networks show nonnormality and that nonnormality can give rise to reactivity-the capacity of a linearly stable system to amplify its response to perturbations, oftentimes exciting nonlinear instabilities. Here, we identify network structural properties underlying the pervasiveness of nonnormality and reactivity in real directed networks, which we establish using the most extensive dataset of such networks studied in this context to date. The identified properties are imbalances between incoming and outgoing network links and paths at each node. On the basis of this characterization, we develop a theory that quantitatively predicts nonnormality and reactivity and explains the observed pervasiveness. We suggest that these results can be used to design, upgrade, control, and manage networks to avoid or promote network instabilities.

Topics & Concepts

Context (archaeology)Computer scienceUpgradeNode (physics)Nonlinear systemSet (abstract data type)Complex networkBiological networkNetwork structureStability (learning theory)Reactivity (psychology)EconometricsData miningDistributed computingMathematicsBiologyMachine learningPhysicsComputational biologyMedicineQuantum mechanicsProgramming languageOperating systemPaleontologyPathologyWorld Wide WebAlternative medicineComplex Network Analysis TechniquesNonlinear Dynamics and Pattern FormationEcosystem dynamics and resilience