Ward, JA, Gleeson, JP, Melnik, S et al. (2 more authors) (2012) Accuracy of mean-field theory for dynamics on real-world networks. Physical Review E, 85 (2). 026106-1. ISSN 1539-3755
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2012, American Physical Society. This is an author produced version of a paper published in Physical Review E. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 12 Aug 2016 14:19 |
Last Modified: | 17 Jan 2018 01:40 |
Published Version: | http://dx.doi.org/10.1103/PhysRevE.85.026106 |
Status: | Published |
Publisher: | American Physical Society |
Identification Number: | 10.1103/PhysRevE.85.026106 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:96409 |