Laplacian dynamics slows down on temporal networks
Interactions among units in networks often occur in a specific sequential order to affect dynamics processes on networks. Networks composed of time-dependent contacts between nodes are collectively called the temporal networks, which are an intensively studied topic nowadays. We theoretically examine the Laplacian spectrum of temporal networks to be compared with that of the corresponding aggregate networks. We show that the Laplacian eigenvalues are smaller (closer to zero) for temporal than aggregate networks for different scenarios of temporal network realizations derived from the same aggregate network. Therefore, diffusive dynamics is slower in temporal than aggregate networks. This work has been done in collaboration with Konstantin Klemm and Victor M. Eguíluz.