Spontaneous recovery in dynamical networks

Majdandzic, Antonio; Podobnik, Boris; Buldyrev, Sergey V.; Kenett, Dror Y.; Havlin, Shlomo; Stanley, H. Eugene

doi:10.1038/nphys2819

Cited by 285 publications

(333 citation statements)

References 27 publications

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“…Subsequently, an explosive phenomenon was found in the dynamics of cascading failures in interdependent networks [16][17][18], in contrast to the secondorder continuous phase transition found in isolated networks. More recently, such explosive phase transitions have been reported in various systems, such as explosive synchronization due to a positive correlation between the degrees of nodes and the natural frequencies of the oscillators [19][20][21] or an adaptive mechanism [22], discontinuous percolation transition due to an inducing effect [23], spontaneous recovery [24], and explosive epidemic outbreak due to cooperative coinfections of multiple diseases * Electronic address: chenhshf@ahu.edu.cn † Electronic address: hzhlj@ustc.edu.cn ‡ Electronic address: Juergen.Kurths@pik-potsdam.de [25][26][27].…”

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confidence: 99%

First-order phase transition in a majority-vote model with inertia

et al. 2017

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We generalize the original majority-vote model by incorporating an inertia into the microscopic dynamics of the spin flipping, where the spin-flip probability of any individual depends not only on the states of its neighbors, but also on its own state. Surprisingly, the order-disorder phase transition is changed from a usual continuous type to a discontinuous or an explosive one when the inertia is above an appropriate level. A central feature of such an explosive transition is a strong hysteresis behavior as noise intensity goes forward and backward. Within the hysteresis region, a disordered phase and two symmetric ordered phases are coexisting and transition rates between these phases are numerically calculated by a rare-event sampling method. A mean-field theory is developed to analytically reveal the property of this phase transition. Recently, explosive or discontinuous transitions in complex networks have received growing attention since the discovery of an abrupt percolation transition in random networks [8,9] and scale-free networks [10,11]. Later studies affirmed that this transition is actually continuous but with an unusual finite size scaling [12][13][14], yet many related models show truly discontinuous and anomalous transitions (cf.[15] for a recent review). Striking different from continuous phase transitions, in an explosive transition an infinitesimal increase of the control parameter can give rise to a considerable macroscopic effect. Subsequently, an explosive phenomenon was found in the dynamics of cascading failures in interdependent networks [16][17][18], in contrast to the secondorder continuous phase transition found in isolated networks. More recently, such explosive phase transitions have been reported in various systems, such as explosive synchronization due to a positive correlation between the degrees of nodes and the natural frequencies of the oscillators [19][20][21] [25][26][27].In this paper we report an explosive order-disorder phase transition in a generalized majority-vote (MV) model by incorporating the effect of individuals' inertia (called inertial MV model ). The MV model is one of the simplest nonequilibrium generalizations of the Ising model that displays a continuous order-disorder phase transition at a critical value of noise [28]. It has been extensively studied in the context of complex networks, including random graphs [29,30], small world networks [31][32][33], and scale-free networks [34,35]. However, the continuous nature of the order-disorder phase transition is not affected by the topology of the underlying networks [36]. In our model, we have included a substantial change to make it more realistic, namely the state update of each node depends not only on the states of its neighboring nodes, but also on its own state. In fact, in a social or biological context individuals have a tendency for beliefs to endure once formed. In a recent experimental study, behavioral inertia was found to be essential for collective turning of starling flocks [37]. We refer this m...

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confidence: 99%

First-order phase transition in a majority-vote model with inertia

et al. 2017

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“…In economics, some key applications include new stress test tools, such as those presented by Li et al [51] and Levy-Carciente et al [61]. Furthermore, these developed tools can be used to introduce intervention strategies in order to manage and mitigate once a cascade of failures is set off in the system (see for example [68]). …”

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confidence: 99%

Cascading Failures in Interdependent Economic Networks

Havlin

Kenett

2015

Springer Proceedings in Complexity

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Throughout the past decade, there has been a significant advance in understanding the structure and function of networks, and mathematical models of networks are now widely used to describe a broad range of complex systems, such as socio-economic systems. However, the significant majority of methods have dealt almost exclusively with individual networks treated as isolated systems. In reality an individual network is often just one component in a much larger complex multi-level network (network of networks, NON). The NON framework provides critical new insights into the structure and function of real-world complex systems. One such insight is that NON system is significantly more vulnerable to shocks and damages, which has lead to the development of the theory of cascading failures in interdependent networks. Here we provide an overview of this theory, and one example of its application to economic systems. IntroductionThe growth of technology, globalization, and urbanization has caused world-wide human social and economic activities to become increasingly interdependent [1][2][3][4][5][6][7][8][9][10][11][12][13]. From the recent financial crisis it is clear that components of this complex system have become increasingly susceptible to collapse. Current models have been unable to predict instability, provide scenarios for future stability, or control or even mitigate systemic failure. Thus, there is a need of new ways of quantifying complex system vulnerabilities as well as new strategies for mitigating systemic damage and increasing system resiliency [14,15]. Achieving this would also provide new insight into such key issues as financial contagion [16,17] and systemic risk [18][19][20] and would provide a way of maintaining economic and financial stability in the future.

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“…It is evident that removal of a C-link in a stem network does not necessarily tear a path between attached nodes because of B-links. The recent research [5] assumed that elements in the dynamic network can fail independently of other elements (internal failure) or due to external causes ( if it has a substantially damaged neighborhood ). The study also emphasized a value of spontaneous recovery for the dynamic networks.…”

Section: Vulnerability Of Mts Modelmentioning

confidence: 99%

Comprehensive Mega Network(CMN) Platform: Korea MTS Governance for CIS Case Study

Ashurova¹,

Myeong²,

Tikhomirov³

et al. 2016

Proceedings of the 2016 Conference on Information Technologies in Science, Management, Social Sphere and Medicine

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Abstract-Medical tourism is one of the fastest growing sectors and has a serious economic potential for Korean economy through expansion of Korean medical tourism service (MTS) network for CIS region. Existing explorations are focusing on specific areas such as economic, medical, marketing and other aspects of the medical tourism. A few academic studies devoted to governance aspects of this complex sector. The paper suggesting a comprehensive mega network is modeling framework for investigating governance process in the field of MTS delivery.

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Spontaneous recovery in dynamical networks

Cited by 285 publications

References 27 publications

First-order phase transition in a majority-vote model with inertia

First-order phase transition in a majority-vote model with inertia

Cascading Failures in Interdependent Economic Networks

Comprehensive Mega Network(CMN) Platform: Korea MTS Governance for CIS Case Study

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