Temporal networks: Slowing down diffusion by long lasting interactions

Naoki Masuda, Konstantin Klemm, Víctor M. Eguíluz

研究成果: Article査読

73 被引用数 (Scopus)

抄録

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.

本文言語English
論文番号188701
ジャーナルPhysical Review Letters
111
18
DOI
出版ステータスPublished - 2013 10 29
外部発表はい

ASJC Scopus subject areas

  • 物理学および天文学(全般)

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