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Particle Interactions Mediated by Dynamical Networks: Assessment of Macroscopic Descriptions

Overview of attention for article published in Journal of Nonlinear Science, August 2017
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Title
Particle Interactions Mediated by Dynamical Networks: Assessment of Macroscopic Descriptions
Published in
Journal of Nonlinear Science, August 2017
DOI 10.1007/s00332-017-9408-z
Pubmed ID
Authors

J. Barré, J. A. Carrillo, P. Degond, D. Peurichard, E. Zatorska

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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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 42%
Researcher 2 17%
Student > Doctoral Student 1 8%
Unknown 4 33%
Readers by discipline Count As %
Mathematics 4 33%
Engineering 2 17%
Physics and Astronomy 2 17%
Earth and Planetary Sciences 1 8%
Unknown 3 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 December 2017.
All research outputs
#18,510,888
of 22,931,367 outputs
Outputs from Journal of Nonlinear Science
#164
of 336 outputs
Outputs of similar age
#243,899
of 318,459 outputs
Outputs of similar age from Journal of Nonlinear Science
#3
of 7 outputs
Altmetric has tracked 22,931,367 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 336 research outputs from this source. They receive a mean Attention Score of 1.7. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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