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Dragon-kings death in nonlinear wave interactions

Author

Listed:
  • Santos, Moises S.
  • Szezech, José D.
  • Batista, Antonio M.
  • Iarosz, Kelly C.
  • Caldas, Iberê L.
  • Viana, Ricardo L.

Abstract

Extreme events are by definition rare and exhibit unusual values of relevant observables. In literature, it is possible to find many studies about the predictability and suppression of extreme events. In this work, we show the existence of dragon-kings extreme events in nonlinear three-wave interactions. Dragon-king extreme events, identified by phase transitions, tipping points and catastrophes, affects fluctuating systems. We show that these events can be avoided by adding a perturbing small amplitude wave to the system.

Suggested Citation

  • Santos, Moises S. & Szezech, José D. & Batista, Antonio M. & Iarosz, Kelly C. & Caldas, Iberê L. & Viana, Ricardo L., 2019. "Dragon-kings death in nonlinear wave interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    • Handle: RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119313287
    DOI: 10.1016/j.physa.2019.122296
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    References listed on IDEAS

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    1. Didier SORNETTE, 2009. "Dragon-Kings, Black Swans and the Prediction of Crises," Swiss Finance Institute Research Paper Series 09-36, Swiss Finance Institute.
    2. Bogachev, Mikhail I. & Bunde, Armin, 2011. "On the predictability of extreme events in records with linear and nonlinear long-range memory: Efficiency and noise robustness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2240-2250.
    3. A. Johansen & D. Sornette, 1998. "Stock market crashes are outliers," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 1(2), pages 141-143, January.
    4. Cao, Guangxi & Zhang, Minjia, 2015. "Extreme values in the Chinese and American stock markets based on detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 25-35.
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    Cited by:

    1. Kaveh, Hojjat & Salarieh, Hassan, 2020. "A new approach to extreme event prediction and mitigation via Markov-model-based chaos control," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).

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