Fitting SDE models to nonlinear Kac-Zwanzig heat bath models

R. Kupferman*, A. M. Stuart

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

We study a class of "particle in a heat bath" models, which are a generalization of the well-known Kac-Zwanzig class of models, but where the coupling between the distinguished particle and the n heat bath particles is through nonlinear springs. The heat bath particles have random initial data drawn from an equilibrium Gibbs density. The primary objective is to approximate the forces exerted by the heat bath - which we do not want to resolve - by a stochastic process. By means of the central limit theorem for Gaussian processes, and heuristics based on linear response theory, we demonstrate conditions under which it is natural to expect that the trajectories of the distinguished particle can be weakly approximated, as n → ∞ by the solution of a Markovian SDE. The quality of this approximation is verified by numerical calculations with parameters chosen according to the linear response theory. Alternatively, the parameters of the effective equation can be chosen using time series analysis. This is done and agreement with linear response theory is shown to be good.

Original languageAmerican English
Pages (from-to)279-316
Number of pages38
JournalPhysica D: Nonlinear Phenomena
Volume199
Issue number3-4
DOIs
StatePublished - 15 Dec 2004

Bibliographical note

Funding Information:
We are grateful to D. Brillinger, A. Chorin, S. Evans, Y. Farjoun, R. Mannella, J. Neu, Y. Peres, P. Tupper and P. Wiberg for helpful discussions. RK was supported by the Israel Science Foundation founded by the Israel Academy of Sciences and Humanities, by the Alon Fellowship, and by the Applied Mathematical Sciences subprogram of the Office of Energy Research of the US Department of Energy under contract DE-AC03-76-SF00098. A.M.S. was supported by the EPSRC, UK.

Keywords

  • Hamiltonian systems
  • Heat bath
  • Nonlinear oscillators
  • Stochastic differential equations

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