Percolation-based precursors of transitions in extended systems
arXiv:1601.01978 · doi:10.1038/srep29552
Abstract
Abrupt transitions are ubiquitous in the dynamics of complex systems. Finding precursors, i.e. early indicators of their arrival, is fundamental in many areas of science ranging from electrical engineering to climate. However, obtaining warnings of an approaching transition well in advance remains an elusive task. Here we show that a functional network, constructed from spatial correlations of the system's time series, experiences a percolation transition way before the actual system reaches a bifurcation point due to the collective phenomena leading to the global change. Concepts from percolation theory are then used to introduce early warning precursors that anticipate the system's tipping point. We illustrate the generality and versatility of our percolation-based framework with model systems experiencing different types of bifurcations and with Sea Surface Temperature time series associated to El Nino phenomenon.
15 pages, 8 figures, to appear in Scientific Reports
References in corpus (5)
Cited by in corpus (10)
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- Evaluation of the Real-time El Niño Forecasts by the Climate Network Approach between 2011 and Present
- Pseudo-Darwinian evolution of physical flows in complex networks
- Network percolation provides early warnings of abrupt changes in coupled oscillatory systems: An explanatory analysis
- Uncovering temporal regularity in atmospheric dynamics through Hilbert phase analysis