Journal of Applied Probability · 2023 · 19 citations · 22 references
Natural SciencesMathematicsPhysicsDynamical SystemsProbability TheoryStochastic ProcessesLaw Of Large NumbersLimit TheoremsMarkov ProcessesStatistical MechanicsStochastic Differential EquationsStochastic NetworksFokker - Planck EquationFokker-planck EquationsFokker-planck TheoryInteracting Particle SystemsMean-field DynamicsMean-field ModelsRandom GraphsVlasov Equation
Abstract We consider a class of weakly interacting particle systems of mean-field type. The interactions between the particles are encoded in a graph sequence, i.e. two particles are interacting if and only if they are connected in the underlying graph. We establish a law of large numbers for the empirical measure of the system that holds whenever the graph sequence is convergent to a graphon. The limit is the solution of a non-linear Fokker–Planck equation weighted by the (possibly random) graphon limit. In contrast with the existing literature, our analysis focuses on both deterministic and random graphons: no regularity assumptions are made on the graph limit and we are able to include general graph sequences such as exchangeable random graphs. Finally, we identify the sequences of graphs, both random and deterministic, for which the associated empirical measure converges to the classical McKean–Vlasov mean-field limit.
22
Synchronization in complex networks
Àlex Arenas, Albert Dı́az-Guilera, Jürgen Kurths et al. · Physics Reports · 2008 · 3.7K citations · Full text
The Kuramoto model in complex networks
Francisco A. Rodrigues, Thomas Peron, Peng Ji et al. · Physics Reports · 2015 · 1K citations · Full text
Fan Chung, Ronald Graham, R. Wilson · COMBINATORICA · 1989 · 486 citations
Graph limits and exchangeable random graphs
Persi Diaconis, Svante Janson · ArXiv.org · 2007 · 288 citations · Full text
Approximating the Cut-Norm via Grothendieck's Inequality
Noga Alon, Assaf Naor · SIAM Journal on Computing · 2006 · 226 citations