Abstract

In this article we study a system of $N$ particles, each of them being defined by the couple of a position (in $\mathbb{R}^d$) and a so-called orientation which is an element of a compact Riemannian manifold. This orientation can be seen as a generalisation of the velocity in Vicsek-type models such as [Degond et al. 2017; Degond, Motsch 2008]. We will assume that the orientation of each particle follows a jump process whereas its position evolves deterministically between two jumps. The law of the jump depends on the position of the particle and the orientations of its neighbours. In the limit $N\to\infty$, we first prove a propagation of chaos result which can be seen as an adaptation of the classical result on McKean-Vlasov systems [Sznitman 1991] to Piecewise Deterministic Markov Processes (PDMP). As in [Jourdain, M\'el\'eard 1998], we then prove that under a proper rescaling with respect to $N$ of the interaction radius between the agents (moderate interaction), the law of the limiting mean-field system satisfies a BGK equation with localised interactions which has been studied as a model of collective behaviour in [Degond et al. 2018]. Finally, in the spatially homogeneous case, we give an alternative approach based on martingale arguments.

Highlights

  • In many systems of interacting agents, a wide range of self-organised collective behaviours can be observed

  • We extend the method of coupling of [53] to the piecewise deterministic setting and we prove a propagation of chaos property for a geometrically enriched system of Piecewise Deterministic Markov Process (PDMP)

  • Reporting (5.4), (5.5) and (5.6) in the representation formula (5.2), we obtain that the weak limitt is deterministic and satisfies weakly the space homogeneous BGK equation with initial condition ν0 ∈ P(M ): t

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Summary

Introduction

In many systems of interacting agents, a wide range of self-organised collective behaviours can be observed. It includes the flock of birds [34], sperm motion [21], opinion dynamics [19] etc. These systems are composed of many interacting agents and the interacting mechanisms which lead to the observed phenomena are not always known or tractable. To study such complex systems a common procedure consists in writing kinetic or fluids models, i.e. a model for the evolution of an observable macroscopic. The present work aims to be a contribution to the rigorous derivation of kinetic models of collective behaviour such as [14] from an IBM

Models for collective dynamics: prototype and extensions
Abstract framework and main results
Individual Based Model
First estimates
A compactness result
An alternative approach in the spatially homogeneous case
Mean-field limit
Conclusion
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