Temporal networks: Slowing down diffusion by long lasting interactions

Naoki Masuda, Konstantin Klemm, Víctor M. Eguíluz

Research output: Contribution to journalArticlepeer-review

84 Citations (Scopus)

Abstract

Interactions among units in complex systems occur in a specific sequential order, thus affecting the flow of information, the propagation of diseases, and general dynamical processes. We investigate the Laplacian spectrum of temporal networks and compare it with that of the corresponding aggregate network. First, we show that the spectrum of the ensemble average of a temporal network has identical eigenmodes but smaller eigenvalues than the aggregate networks. In large networks without edge condensation, the expected temporal dynamics is a time-rescaled version of the aggregate dynamics. Even for single sequential realizations, diffusive dynamics is slower in temporal networks. These discrepancies are due to the noncommutability of interactions. We illustrate our analytical findings using a simple temporal motif, larger network models, and real temporal networks. Published by American Physical Society.

Original languageEnglish
Article number188701
JournalPhysical Review Letters
Volume111
Issue number18
DOIs
Publication statusPublished - Oct 29 2013

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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