Abstract

We study the response to perturbations in the thermodynamic limit of a network of coupled identical agents undergoing a stochastic evolution which, in general, describes non-equilibrium conditions. All systems are nudged towards the common centre of mass. We derive Kramers–Kronig relations and sum rules for the linear susceptibilities obtained through mean field Fokker–Planck equations and then propose corrections relevant for the macroscopic case, which incorporates in a self-consistent way the effect of the mutual interaction between the systems. Such an interaction creates a memory effect. We are able to derive conditions determining the occurrence of phase transitions specifically due to system-to-system interactions. Such phase transitions exist in the thermodynamic limit and are associated with the divergence of the linear response but are not accompanied by the divergence in the integrated autocorrelation time for a suitably defined observable. We clarify that such endogenous phase transitions are fundamentally different from other pathologies in the linear response that can be framed in the context of critical transitions. Finally, we show how our results can elucidate the properties of the Desai–Zwanzig model and of the Bonilla–Casado–Morillo model, which feature paradigmatic equilibrium and non-equilibrium phase transitions, respectively.

Highlights

  • Multi-agent systems are used routinely to model phenomena in the natural sciences, social sciences, and engineering

  • The results presented in [64,65] can be applied to the McKean–Vlasov equation in the absence of phase transitions to justify rigorously linear response theory and to establish fluctuation–dissipation results

  • The main objective of this paper is to perform a systematic study of linear response theory for mean field partial differential equations (PDEs) exhibiting phase transitions

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Summary

Introduction

Multi-agent systems are used routinely to model phenomena in the natural sciences, social sciences, and engineering. One of the main objectives of this paper is to investigate phase transitions for weakly interacting diffusions by looking at the response of the (infinite dimensional) mean field dynamics to weak external perturbations. The mathematical theory of linear response for deterministic systems was developed by Ruelle in the context of Axiom A chaotic systems [47,48] He provided explicit response formulae and showed that, in the case of dissipative systems, the classical fluctuation–dissipation theorem does not hold, and, as a result, natural and forced fluctuations are intimately different [49]. The main objective of this paper is to perform a systematic study of linear response theory for mean field partial differential equations (PDEs) exhibiting phase transitions.

Linear response formulae: mean field and macroscopic results
Dispersion relations far from criticalities
Criticalities
Equilibrium phase transitions: gradient systems
Examples
Conclusion
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