Hamiltonian and Brownian systems with long-range interactions: V. Stochastic kinetic equations and theory of fluctuations

TL;DR

This paper develops a fluctuation theory for Brownian systems with long-range interactions, analyzing the behavior near critical points, and introduces stochastic models for chemotaxis and specific interaction potentials.

Contribution

It derives explicit fluctuation correlation functions for systems with long-range interactions and explores their behavior near phase transition points, extending mean field models to include noise effects.

Findings

Correlation functions decay exponentially in the stable regime.

Spatial correlations diverge at the critical point, indicating phase transition onset.

Velocity fluctuations remain finite at the critical point.

Abstract

We develop a theory of fluctuations for Brownian systems with weak long-range interactions. For these systems, there exists a critical point separating a homogeneous phase from an inhomogeneous phase. Starting from the stochastic Smoluchowski equation governing the evolution of the fluctuating density field, we determine the expression of the correlation function of the density fluctuations around a spatially homogeneous equilibrium distribution. In the stable regime, we find that the temporal correlation function of the Fourier components of the density fluctuations decays exponentially rapidly with the same rate as the one characterizing the damping of a perturbation governed by the mean field Smoluchowski equation (without noise). On the other hand, the amplitude of the spatial correlation function in Fourier space diverges at the critical point $T=T_{c}$ (or at the instability threshold $k=k_{m}$) implying that the mean field approximation breaks down close to the critical point and that the phase transition from the homogeneous phase to the inhomogeneous phase occurs sooner. By contrast, the correlations of the velocity fluctuations remain finite at the critical point (or at the instability threshold). We give explicit examples for the Brownian Mean Field (BMF) model and for Brownian particles interacting via the gravitational potential and via the attractive Yukawa potential. We also introduce a stochastic model of chemotaxis for bacterial populations generalizing the mean field Keller-Segel model by taking into account fluctuations.