- Editors' Suggestion
- Letter
- Open Access
Dragon kings in self-organized criticality systems
Phys. Rev. Research 5, L042013 – Published 19 October, 2023
DOI: https://doi.org/10.1103/PhysRevResearch.5.L042013
Abstract
The spontaneous emergence of scale invariance, called self-organized criticality (SOC), is often attributed to a second-order absorbing-state phase transition (ASPT). Many real-world systems display SOC, yet with extreme events overrepresented, called dragon kings (DKs) and causing significant disruption. We show analytically that the trade-off between driving impulse and dissipation rate can create DKs in a second-order ASPT. This establishes that DKs exist in SOC systems, reveals a taxonomy of DKs, and shows that larger dissipation and smoother driving lower risk of extreme events.
Physics Subject Headings (PhySH)
Article Text
References (51)
- I. Dobson, B. A. Carreras, V. E. Lynch, and D. E. Newman, Complex systems analysis of series of blackouts: Cascading failure, critical points, and self-organization, Chaos 17, 026103 (2007).
- C. D. Brummitt, R. M. D'Souza, and E. A. Leicht, Suppressing cascades of load in interdependent networks, Proc. Natl. Acad. Sci. USA 109, E680 (2012).
- J. P. Gleeson, J. A. Ward, K. P. O'Sullivan, and W. T. Lee, Competition-induced criticality in a model of meme popularity, Phys. Rev. Lett. 112, 048701 (2014).
- A. Dmitriev and V. Dmitriev, Identification of self-organized critical state on Twitter based on the retweets' time series analysis, Complexity 2021, 1 (2021).
- N. Nishizuka, A. Asai, H. Takasaki, H. Kurokawa, and K. Shibata, The power-law distribution of flare kernels and fractal current sheets in a solar flare, Astrophys. J. 694, L74 (2009).
- M. J. Aschwanden, N. B. Crosby, M. Dimitropoulou, M. K. Georgoulis, S. Hergarten, J. McAteer, A. V. Milovanov, S. Mineshige, L. Morales, N. Nishizuka et al., 25 years of self-organized criticality: Solar and astrophysics, Space Sci. Rev. 198, 47 (2016).
- J. M. Beggs and D. Plenz, Neuronal avalanches in neocortical circuits, J. Neurosci. 23, 11167 (2003).
- A. J. Fontenele, N. A. P. de Vasconcelos, T. Feliciano, L. A. A. Aguiar, C. Soares-Cunha, B. Coimbra, L. Dalla Porta, S. Ribeiro, A. J. Rodrigues, N. Sousa, P. V. Carelli, and M. Copelli, Criticality between cortical states, Phys. Rev. Lett. 122, 208101 (2019).
- G. Kartvelishvili, J. Khoury, and A. Sharma, The self-organized critical multiverse, J. Cosmol. Astropart. Phys. (2021) 028.
- P. Bak, C. Tang, and K. Wiesenfeld, Self-organized criticality: An explanation of the noise, Phys. Rev. Lett. 59, 381 (1987).
- R. Dickman, A. Vespignani, and S. Zapperi, Self-organized criticality as an absorbing-state phase transition, Phys. Rev. E 57, 5095 (1998).
- G. Pruessner, Self-Organised Criticality: Theory, Models and Characterisation (Cambridge University Press, Cambridge, UK, 2012).
- S. Zapperi, Crackling Noise: Statistical Physics of Avalanche Phenomena (Oxford University Press, New York, 2022).
- D. Sornette, Dragon-kings, black swans and the prediction of crises, Int. J. Terraspace Sci. Eng. 2, 1 (2009).
- D. Sornette and G. Ouillon, Dragon-kings: Mechanisms, statistical methods and empirical evidence, Eur. Phys. J.: Spec. Top. 205, 1 (2012).
- V. Filimonov and D. Sornette, Power law scaling and “dragon-kings” in distributions of intraday financial drawdowns, Chaos, Solitons Fractals 74, 27 (2015).
- S. Wheatley, B. Sovacool, and D. Sornette, Of disasters and dragon kings: A statistical analysis of nuclear power incidents and accidents, Risk Anal. 37, 99 (2017).
- V. F. Pisarenko and D. Sornette, Robust statistical tests of dragon-kings beyond power law distributions, Eur. Phys. J.: Spec. Top. 205, 95 (2012).
- A. B. Bochdansky, M. A. Clouse, and G. J. Herndl, Dragon kings of the deep sea: marine particles deviate markedly from the common number-size spectrum, Sci. Rep. 6, 22633 (2016).
- L. de Arcangelis, Are dragon-king neuronal avalanches dungeons for self-organized brain activity? Eur. Phys. J.: Spec. Top. 205, 243 (2012).
- A. Mishra, S. Saha, M. Vigneshwaran, P. Pal, T. Kapitaniak, and S. K. Dana, Dragon-king-like extreme events in coupled bursting neurons, Phys. Rev. E 97, 062311 (2018).
- D. Premraj, K. Suresh, S. A. Pawar, L. Kabiraj, A. Prasad, and R. Sujith, Dragon-king extreme events as precursors for catastrophic transition, Europhys. Lett. 134, 34006 (2021).
- M. K. Sachs, M. R. Yoder, D. L. Turcotte, J. B. Rundle, and B. D. Malamud, Black swans, power laws, and dragon-kings: Earthquakes, volcanic eruptions, landslides, wildfires, floods, and SOC models, Eur. Phys. J.: Spec. Top. 205, 167 (2012).
- P. Grassberger, On a self-organized critical forest-fire model, J. Phys. A: Math. Gen. 26, 2081 (1993).
- J. M. Carlson, J. S. Langer, and B. E. Shaw, Dynamics of earthquake faults, Rev. Mod. Phys. 66, 657 (1994).
- S. Zapperi, K. B. Lauritsen, and H. E. Stanley, Self-organized branching processes: Mean-field theory for avalanches, Phys. Rev. Lett. 75, 4071 (1995).
- Luis A. Nunes Amaral and K. B. Lauritsen, Self-organized criticality in a rice-pile model, Phys. Rev. E 54, R4512 (1996).
- A. Watanabe, S. Mizutaka, and K. Yakubo, Fractal and small-world networks formed by self-organized critical dynamics, J. Phys. Soc. Jpn. 84, 114003 (2015).
- Y. Lin, K. Burghardt, M. Rohden, P.-A. Noël, and R. M. D'Souza, Self-organization of dragon king failures, Phys. Rev. E 98, 022127 (2018).
- O. Kinouchi, L. Brochini, A. A. Costa, J. G. F. Campos, and M. Copelli, Stochastic oscillations and dragon king avalanches in self-organized quasi-critical systems, Sci. Rep. 9, 3874 (2019).
- H. L. D. de S. Cavalcante, M. Oriá, D. Sornette, E. Ott, and D. J. Gauthier, Predictability and suppression of extreme events in a chaotic system, Phys. Rev. Lett. 111, 198701 (2013).
- S. L. A. de Queiroz and M. Bahiana, Finite driving rates in interface models of Barkhausen noise, Phys. Rev. E 64, 066127 (2001).
- T. Hwa and M. Kardar, Avalanches, hydrodynamics, and discharge events in models of sandpiles, Phys. Rev. A 45, 7002 (1992).
- P. Pradhan, Time-dependent properties of sandpiles, Front. Phys. 9, 641233 (2021).
- A. Vespignani and S. Zapperi, How self-organized criticality works: A unified mean-field picture, Phys. Rev. E 57, 6345 (1998).
- R. Dickman, M. A. Muñoz, A. Vespignani, and S. Zapperi, Paths to self-organized criticality, Braz. J. Phys. 30, 27 (2000).
- R. Cafiero, V. Loreto, L. Pietronero, A. Vespignani, and S. Zapperi, Local rigidity and self-organized criticality for avalanches, Europhys. Lett. 29, 111 (1995).
- J. A. Bonachela and M. A. Muñoz, Self-organization without conservation: true or just apparent scale-invariance? J. Stat. Mech. (2009) P09009.
- P.-A. Noël, C. D. Brummitt, and R. M. D'Souza, Controlling self-organizing dynamics on networks using models that self-organize, Phys. Rev. Lett. 111, 078701 (2013).
- S. di Santo, R. Burioni, A. Vezzani, and M. A. Muñoz, Self-organized bistability associated with first-order phase transitions, Phys. Rev. Lett. 116, 240601 (2016).
- V. Buendía, S. di Santo, P. Villegas, R. Burioni, and M. A. Muñoz, Self-organized bistability and its possible relevance for brain dynamics, Phys. Rev. Res. 2, 013318 (2020).
- L. Gil and D. Sornette, Landau-ginzburg theory of self-organized criticality, Phys. Rev. Lett. 76, 3991 (1996).
- G. Mikaberidze and R. M. D'Souza, Sandpile cascades on oscillator networks: The BTW model meets Kuramoto, Chaos 32, 053121 (2022).
- R. A. White and K. A. Dahmen, Driving rate effects on crackling noise, Phys. Rev. Lett. 91, 085702 (2003).
- R. K. Pathria, Statistical Mechanics (Elsevier, New York, 2016).
- Note that driving can be independent of perturbation. In the self-organized branching process [26], the driving increments the branching probability while perturbation is introduced by activating a single site.
- I. Eliazar, Black swans and dragon kings: A unified model, Europhys. Lett. 119, 60007 (2017).
- J. Janczura and R. Weron, Black swans or dragon-kings? A simple test for deviations from the power law, Eur. Phys. J.: Spec. Top. 205, 79 (2012).
- J. L. Cardy and P. Grassberger, Epidemic models and percolation, J. Phys. A: Math. Gen. 18, L267 (1985).
- Notice that the driving impulse is for both models of [29]. Thus the second-order DKs disappear in the thermodynamic limit unless also scales with (inoculation model). Yet, for the first-order DKs (complex contagion model), the peak remains sharply pronounced in the thermodynamic limit since it does not require the system to become strongly supercritical.
- G. Ódor, S. Deng, B. Hartmann, and J. Kelling, Synchronization dynamics on the EU and US power grids, Phys. Rev. E 106, 034311 (2022).