Published August 1, 2012 | Version v1
Journal article

Mixing rates of particle systems with energy exchange

  • 1. Department of Mathematics, University of Toronto, Toronto, ON (Canada)
  • 2. Budapest University of Technology and Economics, Mathematical Institute, Egry J. u. 1, 1111 Budapest (Hungary)

Description

A fundamental problem of non-equilibrium statistical mechanics is the derivation of macroscopic transport equations in the hydrodynamic limit. The rigorous study of such limits requires detailed information about rates of convergence to equilibrium for finite sized systems. In this paper, we consider the finite lattice {1, 2, …, N}, with an energy xi ∈ (0, ∞) associated with each site. The energies evolve according to a Markov jump process with nearest neighbour interaction such that the total energy is preserved. We prove that for an entire class of such models the spectral gap of the generator of the Markov process scales as O(N-2). Furthermore, we provide a complete classification of reversible stationary distributions of product type. We demonstrate that our results apply to models similar to the billiard lattice model considered in Gaspard and Gilbert (2009 J. Stat. Mech.: Theory Exp. 2009 24), and hence provide a first step in the derivation of a macroscopic heat equation for a microscopic stochastic evolution of mechanical origin. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/0951-7715/25/8/2349

Additional details

Identifiers

Publishing Information

Journal Title
Nonlinearity (Print)
Journal Volume
25
Journal Issue
8
Journal Page Range
p. 2349-2376
ISSN
0951-7715

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
46002448
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
ENERGY TRANSFER; EQUILIBRIUM; HYDRODYNAMICS; MARKOV PROCESS; MATHEMATICAL MODELS; MATHEMATICAL SOLUTIONS; STATISTICAL MECHANICS; TRANSPORT THEORY
Descriptors DEC
FLUID MECHANICS; MECHANICS; STOCHASTIC PROCESSES