Imperial College London

DrPaulExpert

Faculty of MedicineSchool of Public Health

Honorary Research Associate
 
 
 
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Contact

 

paul.expert08

 
 
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Location

 

Reynolds BuildingCharing Cross Campus

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Summary

 

Publications

Citation

BibTex format

@article{Expert:2017:10.1103/PhysRevE.96.012312,
author = {Expert, P and de, Nigris S and Takaguchi, T and Lambiotte, R},
doi = {10.1103/PhysRevE.96.012312},
journal = {Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics},
title = {Graph spectral characterisation of the XY model on complex networks},
url = {http://dx.doi.org/10.1103/PhysRevE.96.012312},
volume = {96},
year = {2017}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - 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.
AU - Expert,P
AU - de,Nigris S
AU - Takaguchi,T
AU - Lambiotte,R
DO - 10.1103/PhysRevE.96.012312
PY - 2017///
SN - 1063-651X
TI - Graph spectral characterisation of the XY model on complex networks
T2 - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
UR - http://dx.doi.org/10.1103/PhysRevE.96.012312
UR - http://hdl.handle.net/10044/1/49039
VL - 96
ER -