Graph spectral characterization of the XY model on complex networks

Paul Expert, Sarah De Nigris, Taro Takaguchi, Renaud Lambiotte

Research output: Contribution to journalArticlepeer-review

40 Downloads (Pure)

Abstract

There is recent evidence that the XY spin model on complex networks can display three different macroscopic states in response to the topology of the network underpinning the interactions of the spins. In this work we present a way to characterize the macroscopic states of the XY spin model based on the spectral decomposition of time series using topological information about the underlying networks. We use three different classes of networks to generate time series of the spins for the three possible macroscopic states. We then use the temporal Graph Signal Transform technique to decompose the time series of the spins on the eigenbasis of the Laplacian. From this decomposition, we produce spatial power spectra, which summarize the activation of structural modes by the nonlinear dynamics, and thus coherent patterns of activity of the spins. These signatures of the macroscopic states are independent of the underlying network class and can thus be used as robust signatures for the macroscopic states. This work opens avenues to analyze and characterize dynamics on complex networks using temporal Graph Signal Analysis.

Original languageEnglish
Article number012312
JournalPhysical Review E
Volume96
Issue number1
DOIs
Publication statusPublished - 11 Jul 2017

Fingerprint

Dive into the research topics of 'Graph spectral characterization of the XY model on complex networks'. Together they form a unique fingerprint.

Cite this