Early warning signs for saddle-escape transitions in complex networks
arXiv:1401.7125 · doi:10.1038/srep13190
Abstract
Many real world systems are at risk of undergoing critical transitions, leading to sudden qualitative and sometimes irreversible regime shifts. The development of early warning signals is recognized as a major challenge. Recent progress builds on a mathematical framework in which a real-world system is described by a low-dimensional equation system with a small number of key variables, where the critical transition often corresponds to a bifurcation. Here we show that in high-dimensional systems, containing many variables, we frequently encounter an additional non-bifurcative saddle-type mechanism leading to critical transitions. This generic class of transitions has been missed in the search for early-warnings up to now. In fact, the saddle-type mechanism also applies to low-dimensional systems with saddle-dynamics. Near a saddle a system moves slowly and the state may be perceived as stable over substantial time periods. We develop an early warning sign for the saddle-type transition. We illustrate our results in two network models and epidemiological data. This work thus establishes a connection from critical transitions to networks and an early warning sign for a new type of critical transition. In complex models and big data we anticipate that saddle-transitions will be encountered frequently in the future.
revised version
References in corpus (1)
Cited by in corpus (10)
- Robustness and resilience of complex networks
- An adaptive voter model on simplicial complexes
- Early-Warning Signs for Pattern-Formation in Stochastic Partial Differential Equations
- Network topology near criticality in adaptive epidemics
- Time-series-analysis-based detection of critical transitions in real-world non-autonomous systems
- Stability analysis of multiplayer games on adaptive simplicial complexes
- Heterogeneous Population Dynamics and Scaling Laws near Epidemic Outbreaks
- Tangled Nature: A model of emergent structure and temporal mode among co-evolving agents
- Analysis and Predictability for Tipping Points with Leading-Order Nonlinear Terms
- Scaling Laws and Warning Signs for Bifurcations of SPDEs