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Particle Interactions Mediated by Dynamical Networks: Assessment of Macroscopic Descriptions
Authors:J.?Barré,J.?A.?Carrillo,P.?Degond  author-information"  >  author-information__contact u-icon-before"  >  mailto:pdegond@imperial.ac.uk"   title="  pdegond@imperial.ac.uk"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author  author-information__orcid u-icon-before icon--orcid u-icon-no-repeat"  >  http://orcid.org/---"   itemprop="  url"   title="  View OrcID profile"   target="  _blank"   rel="  noopener"   data-track="  click"   data-track-action="  OrcID"   data-track-label="  "  >View author&#  s OrcID profile,D.?Peurichard,E.?Zatorska
Affiliation:1.Laboratoire MAPMO, CNRS, UMR 7349, Fédération Denis Poisson, FR 2964,Université d’Orléans,Orléans Cedex 2,France;2.Institut Universitaire de France,Paris,France;3.Department of Mathematics,Imperial College London,London,UK;4.Faculty of Mathematics,University of Vienna,Vienna,Austria
Abstract:We provide a numerical study of the macroscopic model of Barré et al. (Multiscale Model Simul, 2017, to appear) derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodeling process is very fast, the macroscopic model takes the form of a single aggregation–diffusion equation for the density of particles. The theoretical study of the macroscopic model gives precise criteria for the phase transitions of the steady states, and in the one-dimensional case, we show numerically that the stationary solutions of the microscopic model undergo the same phase transitions and bifurcation types as the macroscopic model. In the two-dimensional case, we show that the numerical simulations of the macroscopic model are in excellent agreement with the predicted theoretical values. This study provides a partial validation of the formal derivation of the macroscopic model from a microscopic formulation and shows that the former is a consistent approximation of an underlying particle dynamics, making it a powerful tool for the modeling of dynamical networks at a large scale.
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