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https://hdl.handle.net/20.500.14279/9066
Title: | Hamiltonian dynamics of preferential attachment | Authors: | Zuev, Konstantin Papadopoulos, Fragkiskos Krioukov, Dmitri V |
metadata.dc.contributor.other: | Παπαδόπουλος, Φραγκίσκος | Major Field of Science: | Engineering and Technology | Field Category: | Computer and Information Sciences;Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Complex networks;Exponential random graphs;Hamiltonian dynamics;Preferential attachment | Issue Date: | 27-Jan-2016 | Source: | Journal of Physics A: Mathematical and Theoretical, 2016, vol. 49, no. 10, | Volume: | 49 | Issue: | 10 | Journal: | Journal of Physics A: Mathematical and Theoretical | Abstract: | Prediction and control of network dynamics are grand-challenge problems in network science. The lack of understanding of fundamental laws driving the dynamics of networks is among the reasons why many practical problems of great significance remain unsolved for decades. Here we study the dynamics of networks evolving according to preferential attachment (PA), known to approximate well the large-scale growth dynamics of a variety of real networks. We show that this dynamics is Hamiltonian, thus casting the study of complex networks dynamics to the powerful canonical formalism, in which the time evolution of a dynamical system is described by Hamilton's equations. We derive the explicit form of the Hamiltonian that governs network growth in PA. This Hamiltonian turns out to be nearly identical to graph energy in the configuration model, which shows that the ensemble of random graphs generated by PA is nearly identical to the ensemble of random graphs with scale-free degree distributions. In other words, PA generates nothing but random graphs with power-law degree distribution. The extension of the developed canonical formalism for network analysis to richer geometric network models with non-degenerate groups of symmetries may eventually lead to a system of equations describing network dynamics at small scales. | URI: | https://hdl.handle.net/20.500.14279/9066 | ISSN: | 17518113 | DOI: | 10.1088/1751-8113/49/10/105001 | Rights: | © Institute of Physics Publishing | Type: | Article | Affiliation : | Cyprus University of Technology Northeastern University |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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