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Sofoclis Zambirinis1, Fragkiskos Papadopoulos1

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We introduce a new model for temporal random hyperbolic graphs with persistent connections and disconnections. This model offers more control over network dynamics and analysis of temporal network properties.

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Area of Science:

  • Network Science
  • Complex Systems
  • Graph Theory

Background:

  • Temporal networks capture dynamic interactions over time.
  • Existing models may not fully represent persistent link dynamics.
  • Random hyperbolic graphs offer a framework for complex network analysis.

Purpose of the Study:

  • To extend the random hyperbolic graph model to incorporate persistent connection and disconnection probabilities.
  • To analyze the analytical challenges and key properties of the extended model.
  • To provide a more flexible tool for studying temporal network dynamics.

Main Methods:

  • Extension of a recent temporal random hyperbolic graph model.
  • Inclusion of distinct probabilities (ω1 and ω2) for connection and disconnection persistence.
  • Analytical treatment involving Appell F1 series to derive network properties.

Main Results:

  • Analysis of contact and intercontact duration distributions.
  • Calculation of the expected time-aggregated degree.
  • Demonstration of flexible tuning of temporal network properties via ω1 and ω2.

Conclusions:

  • The extended model offers enhanced control over temporal network dynamics.
  • Provides deeper insights into the analysis of temporal networks.
  • Contributes to a more generalized representation of real-world dynamic systems.