TY - JOUR
T1 - Accuracy of mean-field theory for dynamics on real-world networks
AU - Gleeson, James P.
AU - Melnik, Sergey
AU - Ward, Jonathan A.
AU - Porter, Mason A.
AU - Mucha, Peter J.
PY - 2012/2/7
Y1 - 2012/2/7
N2 - Mean-field analysis is an important tool for understanding dynamics on complex networks. However, surprisingly little attention has been paid to the question of whether mean-field predictions are accurate, and this is particularly true for real-world networks with clustering and modular structure. In this paper, we compare mean-field predictions to numerical simulation results for dynamical processes running on 21 real-world networks and demonstrate that the accuracy of such theory depends not only on the mean degree of the networks but also on the mean first-neighbor degree. We show that mean-field theory can give (unexpectedly) accurate results for certain dynamics on disassortative real-world networks even when the mean degree is as low as 4.
AB - Mean-field analysis is an important tool for understanding dynamics on complex networks. However, surprisingly little attention has been paid to the question of whether mean-field predictions are accurate, and this is particularly true for real-world networks with clustering and modular structure. In this paper, we compare mean-field predictions to numerical simulation results for dynamical processes running on 21 real-world networks and demonstrate that the accuracy of such theory depends not only on the mean degree of the networks but also on the mean first-neighbor degree. We show that mean-field theory can give (unexpectedly) accurate results for certain dynamics on disassortative real-world networks even when the mean degree is as low as 4.
UR - http://www.scopus.com/inward/record.url?scp=84857511011&partnerID=8YFLogxK
U2 - 10.1103/PhysRevE.85.026106
DO - 10.1103/PhysRevE.85.026106
M3 - Article
AN - SCOPUS:84857511011
SN - 1539-3755
VL - 85
JO - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
JF - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
IS - 2
M1 - 026106
ER -