Evidence map›Paper›PMID 29367810›Full record

ArticleJournal of nonlinear science2018

Particle Interactions Mediated by Dynamical Networks: Assessment of Macroscopic Descriptions.

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

Abstract read
In one paragraph

Article in Journal of nonlinear science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

J Barré1Laboratoire MAPMO, CNRS, UMR 7349, Fédération Denis Poisson, FR 2964, Université d'Orléans, B.P. 6759, 45067 Orléans Cedex 2, France.
J A Carrillo3Department of Mathematics, Imperial College London, London, SW7 2AZ UK.
P Degond3Department of Mathematics, Imperial College London, London, SW7 2AZ UK.ORCID 0000-0002-4886-6968
D Peurichard4Faculty of Mathematics, University of Vienna, Oskar-Morgenstern Platz 1, 1090 Vienna, Austria.
E Zatorska3Department of Mathematics, Imperial College London, London, SW7 2AZ UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Aggregation–diffusion equationBifurcationsCross-linksDiffusion approximationDynamical networksFourier analysisKinetic equationMean-field limitMicroscopic modelPhase transitions

Identifiers

PMID29367810
PMCPMC5756578

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.