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Review Article

Explosive phenomena in complex networks

, , &
Pages 123-223 | Received 17 Dec 2018, Accepted 15 May 2019, Published online: 27 Aug 2019
 

Abstract

The emergence of large-scale connectivity and synchronization are crucial to the structure, function and failure of many complex socio-technical networks. Thus, there is great interest in analyzing phase transitions to large-scale connectivity and to global synchronization, including how to enhance or delay the onset. These phenomena are traditionally studied as second-order phase transitions where, at the critical threshold, the order parameter increases rapidly but continuously. In 2009, an extremely abrupt transition was found for a network growth process where links compete for addition in an attempt to delay percolation. This observation of ‘explosive percolation’ was ultimately revealed to be a continuous transition in the thermodynamic limit, yet with very atypical finite-size scaling, and it started a surge of work on explosive phenomena and their consequences. Many related models are now shown to yield discontinuous percolation transitions and even hybrid transitions. Explosive percolation enables many other features such as multiple giant components, modular structures, discrete scale invariance and non-self-averaging, relating to properties found in many real phenomena such as explosive epidemics, electric breakdowns and the emergence of molecular life. Models of explosive synchronization provide an analytic framework for the dynamics of abrupt transitions and reveal the interplay between the distribution in natural frequencies and the network structure, with applications ranging from epileptic seizures to waking from anesthesia. Here we review the vast literature on explosive phenomena in networked systems and synthesize the fundamental connections between models and survey the application areas. We attempt to classify explosive phenomena based on underlying mechanisms and to provide a coherent overview and perspective for future research to address the many vital questions that remained unanswered.

Acknowledgments

We benefited from critical feedback from G. Bianconi, B. Ziff, B. Khang, S. Gómez, C. Granell, M. Timme, Y. Fender, and L. Fender.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with a minor spelling change in the reference list. This change does not impact the academic content of the article.

Additional information

Funding

We gratefully acknowledge support from funding agencies and the reviewers of this manuscript. In particular RMD acknowledges support from the U.S. Army Research Office MURI Award No. W911NF-13-1-0340 and Cooperative Agreement No. W911NF-09-2-0053, and DARPA Award No. W911NF-17-1-0077. JGG acknowledges support from MINECO through project No. FIS2017-87519-P, and from the Departamento de Industria e Innovación del Gobierno de Aragón y Fondo Social Europeo (FENOL group E-19). AA acknowledges support by Ministerio de Economía y Competitividad (grant FIS2015-71582-C2-1, PGC2018-094754-B-C21), Generalitat de Catalunya (grant 2017SGR-896), and Universitat Rovira i Virgili (grant 2017PFR-URV-B2-41), ICREA Academia and the James S. McDonnell Foundation (grant # 220020325).

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