Asymptotic velocity distribution of a driven one dimensional binary granular Maxwell gas

TL;DR

This paper analyzes the steady-state velocity distributions of a driven inelastic Maxwell gas with two particle types, revealing how tail behaviors depend on driving mechanisms and noise characteristics.

Contribution

It provides an exact characterization of velocity statistics and asymptotic tail behaviors for a two-species driven granular gas, highlighting differences based on driving dissipation.

Findings

Velocity distributions have similar tails despite different driving.

Non-universal tail features depend on noise distribution for dissipative driving.

Exponential tails occur under diffusive driving with fast-decaying noise.

Abstract

We consider the steady states of a driven inelastic Maxwell gas consisting of two types of particles with scalar velocities. Motivated by experiments on bilayers where only one layer is driven, we focus on the case when only one of the two types of particles are driven externally, with the other species receiving energy only through inter-particle collision. The velocity $v$ of a particle that is driven is modified to $-r_w v+\eta$, where $r_w$ parameterises the dissipation upon the driving and the noise $\eta$ is taken from a fixed distribution. We characterize the statistics for small velocities by computing exactly the mean energies of the two species, based on the simplifying feature that the correlation functions are seen to form a closed set of equations. The asymptotic behaviour of the velocity distribution for large speeds is determined for both components through a combination of exact analysis for a range of parameters or obtained numerically to a high degree of accuracy from an analysis of the large moments of velocity. We show that the tails of the velocity distribution for both types of particles have similar behaviour, even though they are driven differently. For dissipative driving ($r_w<1$), the tails of the steady state velocity distribution show non-universal features and depend strongly on the noise distribution. On the other hand, the tails of the velocity distribution are exponential for diffusive driving ($r_w=1$) when the noise distribution decays faster than exponential.