Complex Network Modelling with Power-law Activating Patterns and Its Evolutionary Dynamics
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866915152061792256 |
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| author | Zeng, Ziyan Feng, Minyu Liu, Pengfei Kurths, Jurgen |
| author_facet | Zeng, Ziyan Feng, Minyu Liu, Pengfei Kurths, Jurgen |
| contents | Complex network theory provides a unifying framework for the study of structured dynamic systems. The current literature emphasizes a widely reported phenomenon of intermittent interaction among network vertices. In this paper, we introduce a complex network model that considers the stochastic switching of individuals between activated and quiescent states at power-law rates and the corresponding evolutionary dynamics. By using the Markov chain and renewal theory, we discover a homogeneous stationary distribution of activated sizes in the network with power-law activating patterns and infer some statistical characteristics. To better understand the effect of power-law activating patterns, we study the two-person-two-strategy evolutionary game dynamics, demonstrate the absorbability of strategies, and obtain the critical cooperation conditions for prisoner's dilemmas in homogeneous networks without mutation. The evolutionary dynamics in real networks are also discussed. Our results provide a new perspective to analyze and understand social physics in time-evolving network systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_09768 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Complex Network Modelling with Power-law Activating Patterns and Its Evolutionary Dynamics Zeng, Ziyan Feng, Minyu Liu, Pengfei Kurths, Jurgen Social and Information Networks Physics and Society Complex network theory provides a unifying framework for the study of structured dynamic systems. The current literature emphasizes a widely reported phenomenon of intermittent interaction among network vertices. In this paper, we introduce a complex network model that considers the stochastic switching of individuals between activated and quiescent states at power-law rates and the corresponding evolutionary dynamics. By using the Markov chain and renewal theory, we discover a homogeneous stationary distribution of activated sizes in the network with power-law activating patterns and infer some statistical characteristics. To better understand the effect of power-law activating patterns, we study the two-person-two-strategy evolutionary game dynamics, demonstrate the absorbability of strategies, and obtain the critical cooperation conditions for prisoner's dilemmas in homogeneous networks without mutation. The evolutionary dynamics in real networks are also discussed. Our results provide a new perspective to analyze and understand social physics in time-evolving network systems. |
| title | Complex Network Modelling with Power-law Activating Patterns and Its Evolutionary Dynamics |
| topic | Social and Information Networks Physics and Society |
| url | https://arxiv.org/abs/2502.09768 |