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The universality of physical images at relative timescales on multiplex networks

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  • Chang, Xin
  • Cai, Chao-Ran
  • Zhang, Ji-Qiang
  • Yang, Wen-Li

Abstract

The duration of the accumulation rate (physical image) is a key factor in analysis of counterintuitive phenomena involving relative timescales on multiplex networks. Typically, the relative timescales are represented by multiplying any layer by the same factor. However, researchers often overlook the changes in the relative timescales caused by local parameters, resulting in incomplete analysis of phenomena. This paper examines the survival time of stifler individuals in the information-epidemic model on multiplex networks. The relative timescales can be affected by the survival time (only one parameter), reversing the monotonically increasing phenomenon into a monotonically decreasing one, that is, a counterintuitive phenomenon under incomplete analysis. Additionally, the relative timescales can influence the epidemic threshold, which is different from the previous studies. Our work suggests that considering the physical image of relative timescales is crucial when analyzing multiplex networks, even when only one parameter is altered.

Suggested Citation

  • Chang, Xin & Cai, Chao-Ran & Zhang, Ji-Qiang & Yang, Wen-Li, 2024. "The universality of physical images at relative timescales on multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
  • Handle: RePEc:eee:chsofr:v:182:y:2024:i:c:s0960077924003321
    DOI: 10.1016/j.chaos.2024.114780
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    References listed on IDEAS

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    1. You, Xuemei & Zhang, Man & Ma, Yinghong & Tan, Jipeng & Liu, Zhiyuan, 2023. "Impact of higher-order interactions and individual emotional heterogeneity on information-disease coupled dynamics in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    2. Ma, Jinlong & Wang, Peng, 2024. "Impact of community networks with higher-order interaction on epidemic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    3. Iacopo Iacopini & Giovanni Petri & Alain Barrat & Vito Latora, 2019. "Simplicial models of social contagion," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    4. Liu, Run-Ran & Chu, Changchang & Meng, Fanyuan, 2023. "Higher-order interdependent percolation on hypergraphs," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    5. Wan, Jinming & Ichinose, Genki & Small, Michael & Sayama, Hiroki & Moreno, Yamir & Cheng, Changqing, 2022. "Multilayer networks with higher-order interaction reveal the impact of collective behavior on epidemic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    6. Li, Wenyao & Cai, Meng & Zhong, Xiaoni & Liu, Yanbing & Lin, Tao & Wang, Wei, 2023. "Coevolution of epidemic and infodemic on higher-order networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    7. Guilherme Ferraz de Arruda & Lucas G. S. Jeub & Angélica S. Mata & Francisco A. Rodrigues & Yamir Moreno, 2022. "From subcritical behavior to a correlation-induced transition in rumor models," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
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