Dynamic topologies of activity-driven temporal networks with memory

Hyewon Kim, Meesoon Ha, and Hawoong Jeong
Phys. Rev. E 97, 062148 – Published 27 June 2018

Abstract

We propose dynamic scaling in temporal networks with heterogeneous activities and memory and provide a comprehensive picture for the dynamic topologies of such networks, in terms of the modified activity-driven network model [H. Kim et al., Eur. Phys. J. B 88, 315 (2015)]. Particularly, we focus on the interplay of the time resolution and memory in dynamic topologies. Through the random-walk (RW) process, we investigate diffusion properties and topological changes as the time resolution increases. Our results with memory are compared to those of the memoryless case. Based on the temporal percolation concept, we derive scaling exponents in the dynamics of the largest cluster and the coverage of the RW process in time-varying networks. We find that the time resolution in the time-accumulated network determines the effective size of the network, while memory affects relevant scaling properties at the crossover from the dynamic regime to the static one. The origin of memory-dependent scaling behaviors is the dynamics of the largest cluster, which depends on temporal degree distributions. Finally, we conjecture of the extended finite-size scaling ansatz for dynamic topologies and the fundamental property of temporal networks, which are numerically confirmed.

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  • Received 21 November 2017
  • Revised 10 March 2018

DOI:https://doi.org/10.1103/PhysRevE.97.062148

©2018 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsNetworks

Authors & Affiliations

Hyewon Kim1, Meesoon Ha2,*, and Hawoong Jeong1,3,†

  • 1Department of Physics, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
  • 2Department of Physics Education, Chosun University, Gwangju 61452, Korea
  • 3Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea

  • *msha@chosun.ac.kr
  • hjeong@kaist.edu

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Issue

Vol. 97, Iss. 6 — June 2018

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