Predictability of catastrophic events: Material rupture, earthquakes, turbulence, financial crashes, and human birth
By Didier Sornette. Proceedings of the National Academy of Sciences of the United States of America, 2001
312 citations recorded by the source corpus.
We propose that catastrophic events are “outliers” with statistically different properties than the rest of the population and result from mechanisms involving amplifying critical cascades. We describe a unifying approach for modeling and predicting these catastrophic events or “ruptures,” that is, sudden transitions from a quiescent state to a crisis. Such ruptures involve interactions between structures at many different scales. Applications and the potential for prediction are discussed in relation to the rupture of composite materials, great earthquakes, turbulence, and abrupt changes of weather regimes, financial crashes, and human parturition (birth). Future improvements will involve combining ideas and tools from statistical physics and artificial/computational intelligence, to identify and classify possible universal structures that occur at different scales, and to develop application-specific methodologies to use these structures for prediction of the “crises” known to arise in each application of interest. We live on a planet and in a society with intermittent dynamics rather than a state of equilibrium, and so there is a growing and urgent need to sensitize students and citizens to the importance and impacts of ruptures in their multiple forms.
Subfields: Geophysics, Oceanography
View Paper: https://www.semanticscholar.org/paper/2c1b986f4068ebc7a27ba948f0a4181b49f4ae17
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Citations in the corpus
- Critical Market Crashes (2003, unknown): “…by our co-workers and us as well as several others, academics and most-of-all practitioners (see Sornette and Johansen, 2001, and Johansen and Sornette, 2002, for a recent review and assessment and Zhou and Sornette, 2002a, b, c for nonparametric tests using a generalization of the so-called…”
- Prediction (2010, unknown): “, they are outliers or “dr agon-kings” [75, 137] occurring as a result of some additional amplifying mechanism; these outliers un like those in the SOC regime, have a degree of predictability [133], as we discuss below.”
- Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws (2007, background): “…size of species Epidemics Frequency of species Size distributions in ecosystems; predators Mass extinctions West and Deering (1995); Gardner (1978) Sornette (2002) Bak (1996) Baum and Silverman (2001) Bak (1996) Nekola and Brown (2007) Casti (1994) Bak (1996) MINDAT Gutenberg and Richter (1944)…”
- Dragon-kings: Mechanisms, statistical methods and empirical evidence (2012, methodology): “y at the potentially destructive ‘big-one’ (in the spirit of Johansen and Sornette, 1998a). This reasoning could Dragon-kings, black swans, and the prediction of crises 15 apply to many other fields. Sornette (2002; 2006), Dakos et al. (2008), Scheffer et al. (2009) and others have documented that t”
- Early warning signals also precede non-catastrophic transitions (2013, background): “In the case of ecosystems, but also more generally of complex systems (Sornette 2002, 2003, Peters and Pielke linear autoregressive model of first order (AR(1), xt 1 2 m 5 a1(xt 2 m) e, where a1 is the autoregressive coefficient of order 1, m the mean of the timeseries and e an error i.i.d term)…”