Predictability and suppression of extreme events in a chaotic system.

Published

Journal Article

In many complex systems, large events are believed to follow power-law, scale-free probability distributions so that the extreme, catastrophic events are unpredictable. Here, we study coupled chaotic oscillators that display extreme events. The mechanism responsible for the rare, largest events makes them distinct, and their distribution deviates from a power law. On the basis of this mechanism identification, we show that it is possible to forecast in real time an impending extreme event. Once forecasted, we also show that extreme events can be suppressed by applying tiny perturbations to the system.

Full Text

Duke Authors

Cited Authors

  • Cavalcante, HLDDS; Oriá, M; Sornette, D; Ott, E; Gauthier, DJ

Published Date

  • November 4, 2013

Published In

Volume / Issue

  • 111 / 19

Start / End Page

  • 198701 -

PubMed ID

  • 24266492

Pubmed Central ID

  • 24266492

Electronic International Standard Serial Number (EISSN)

  • 1079-7114

International Standard Serial Number (ISSN)

  • 0031-9007

Digital Object Identifier (DOI)

  • 10.1103/physrevlett.111.198701

Language

  • eng