Growth, collapse and self-organized criticality in complex networks

Wang, Yafeng; Fan, Huawei; Lin, Weijie; Lai, Ying–Cheng; Wang, Xingang

doi:10.1038/srep24445

Cited by 15 publications

(13 citation statements)

References 81 publications

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“…The studies are conducted using SOC model to analyze the growth dynamics of these systems and effect of human interventions in the system. For example, the effect of introducing a new species into an ecosystem [20], external threats to the system, attack from outside targeting a random member or targeting a special member of the system, etc.…”

Section: Self-organized Criticalitymentioning

confidence: 99%

Introduction to Complex Systems, Sustainability and Innovation

Thomas¹,

Prasad²,

Mathew³

2016

Complex Systems, Sustainability and Innovation

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The technological innovations have always proved the impossible possible. Humans have all the time obliterated barriers and set records with astounding regularity. However, there are issues springing up in terms of complexity and sustainability in this context, which we were ignoring for long. Today, in every walk of life, we encounter complex systems, whether it is the Internet, communication systems, electrical power grids, or the financial markets. Due to its unpredictable behavior, any creative change in a complex system poses a threat of systemic risks. This is because an innovation is always introducing something new, introducing a change, possibly to solve an existing problem, the effect of which is nonlinear. Failure to predict the future states of the system due to the nonlinear nature makes any system unsustainable. This necessitates the need for any development to be sustainable by meeting the needs of people today without destroying the potential of future generations to meet their needs. This chapter, which studies systems that are complex due to intricateness in their connectivity, gives insights into their ways of emergence and the nonlinear cause and effects pattern the complex systems use to follow, effectively paving way for sustainable innovation.

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Section: Self-organized Criticalitymentioning

confidence: 99%

Introduction to Complex Systems, Sustainability and Innovation

Thomas¹,

Prasad²,

Mathew³

2016

Complex Systems, Sustainability and Innovation

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“…En tal tesitura, un aspecto que conviene destacar es que la introducción de nuevos enlaces se efectúa preferencialmente, al igual que hicieron [Wan+16] en su modelo de osciladores (mapas caóticos acoplados) críticamente auto-organizados.…”

Section: Descripción Integrada: Ejemplo De Aplicación De Los Resultadunclassified

“…En el caso de los humanos, la sincronización se ha abordado desde la escala micro hasta la macro. Los estudios se interesan por las interacciones que se establecen entre dos o tres personas, hasta las que existen entre ciudades, localizadas [Wan+16]. Su red es un sistema abierto al que se añaden nodos en cada instante de tiempo.…”

Section: Sincronización En Redes Adaptativas Críticamente Autoorganizunclassified

“…Por ello, "[d]esarrollar un marco teórico integral para comprender, a nivel cuantitativo, la dinámica fundamental de la sostenibilidad en sistemas complejos sujetos a crecimiento continuo es un problema desafiante y abierto en el presente." [Wan+16]. Este trabajo de tesis pretende ser un paso que avance en esa dirección.…”

Section: Sincronización En Redes Adaptativas Críticamente Autoorganizunclassified

“…124 Capítulo 6. Análisis y discusión de resultados Es destacable que, en general, los colapsos reducen la cantidad de enlaces a unas pocas unidades, al igual que sucede en el modelo de [Wan+16]. Se considera que la causa de estas drásticas reducciones radica en la adición de enlaces de manera preferencial y en el reducido valor del umbral U utilizado.…”

Section: Estudio De La Dinámica De Una Sintonización Particular Del Munclassified

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Modelos de redes adaptativas críticamente auto-organizadas : aplicación al estudio de modelos de población

Avendaño¹

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general 6. Análisis y discusión de resultados 6.1. Análisis y discusión de resultados del compendio de publicaciones . 6.1.1. Modelos de crecimiento sujetos a una restricción de las diferencias entre un nodo y sus primeros vecinos: Inducción de dinámicas críticamente auto-organizadas . . . . . . . . . . . . 6.1.2. Nuevos rasgos topológicos en redes reales y en modelos de crecimiento sujetos a una restricción de las diferencias entre un nodo y sus primeros vecinos: Estudio de la asortatividad de vecindario y la asortatividad de dos-pasos . . . . . . . . . . 6.1.3. La sincronización de redes de osciladores de Kuramoto en un escenario de dinámicas adaptativas críticamente auto-organizadas 113 6.2. Descripción integrada: Ejemplo de aplicación de los resultados de las publicaciones al desarrollo de modelos de población .

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Sandpile cascades on oscillator networks: The BTW model meets Kuramoto

Mikaberidze

D’Souza

2022

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Cascading failures abound in complex systems and the Bak–Tang–Weisenfeld (BTW) sandpile model provides a theoretical underpinning for their analysis. Yet, it does not account for the possibility of nodes having oscillatory dynamics, such as in power grids and brain networks. Here, we consider a network of Kuramoto oscillators upon which the BTW model is unfolding, enabling us to study how the feedback between the oscillatory and cascading dynamics can lead to new emergent behaviors. We assume that the more out-of-sync a node is with its neighbors, the more vulnerable it is and lower its load-carrying capacity accordingly. Also, when a node topples and sheds load, its oscillatory phase is reset at random. This leads to novel cyclic behavior at an emergent, long timescale. The system spends the bulk of its time in a synchronized state where load builds up with minimal cascades. Yet, eventually, the system reaches a tipping point where a large cascade triggers a “cascade of larger cascades,” which can be classified as a dragon king event. The system then undergoes a short transient back to the synchronous, buildup phase. The coupling between capacity and synchronization gives rise to endogenous cascade seeds in addition to the standard exogenous ones, and we show their respective roles. We establish the phenomena from numerical studies and develop the accompanying mean-field theory to locate the tipping point, calculate the load in the system, determine the frequency of the long-time oscillations, and find the distribution of cascade sizes during the buildup phase.

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Growth, collapse and self-organized criticality in complex networks

Cited by 15 publications

References 81 publications

Introduction to Complex Systems, Sustainability and Innovation

Introduction to Complex Systems, Sustainability and Innovation

Modelos de redes adaptativas críticamente auto-organizadas : aplicación al estudio de modelos de población

Sandpile cascades on oscillator networks: The BTW model meets Kuramoto

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