Generation of chaos in the cumulant hierarchy of the stochastic Kac model

TL;DR

This paper investigates how quickly chaos, in terms of particle velocity independence, develops in the stochastic Kac model by analyzing the rapid convergence of cumulants to their stationary values within a collision time scale.

Contribution

It demonstrates that finite order cumulants in the stochastic Kac model converge faster than the overall distribution, providing a novel application of the cumulant hierarchy method in kinetic theory.

Findings

Cumulants converge to stationary values within order one collisions.

Spectral gap results imply convergence to uniform distribution in order N collisions.

First application of cumulant hierarchy to microscopic kinetic models.

Abstract

We study the time-evolution of cumulants of velocities and kinetic energies in the stochastic Kac model for velocity exchange of $N$ particles, with the aim of quantifying how fast these degrees of freedom become chaotic in a time scale in which the collision rate for each particle is order one. Chaos here is understood in the sense of the original Sto\ss zahlansatz, as an almost complete independence of the particle velocities which we measure by the magnitude of their cumulants up to a finite, but arbitrary order. Known spectral gap results imply that typical initial densities converge to uniform distribution on the constant energy sphere at a time which has order of $N$ expected collisions. We prove that the finite order cumulants converge to their small stationary values much faster, already at a time scale of order one collisions. The proof relies on stability analysis of the closed, but nonlinear, hierarchy of energy cumulants around the fixed point formed by their values in the stationary spherical distribution. It provides the first example of an application of the cumulant hierarchy method to control the properties of a microscopic model related to kinetic theory.