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JOURNALS // Teoriya Veroyatnostei i ee Primeneniya // Archive

Teor. Veroyatnost. i Primenen., 2005 Volume 50, Issue 4, Pages 675–710 (Mi tvp125)

This article is cited in 17 papers

On a two-temperature problem for Klein–Gordon equation

T. V. Dudnikovaa, A. I. Komechb

a Electrostal' Polytechnic Institute
b M. V. Lomonosov Moscow State University, Faculty of Mechanics and Mathematics

Abstract: We consider the Klein–Gordon equation in $\mathbf{R}^n$, $n\geq 2$, with constant or variable coefficients. The initial datum is a random function with a finite mean density of the energy and satisfies a Rosenblatt- or Ibragimov–Linnik-type mixing condition. We also assume that the random function is close to different space-homogeneous processes as $x_n\to\pm\infty$, with the distributions $\mu_\pm$. We study the distribution $\mu_t$ of the random solution at time $t\in\mathbf{R}$. The main result is the convergence of $\mu_t$ to a Gaussian translation-invariant measure as $t\to\infty$ that means the central limit theorem for the Klein–Gordon equation. The proof is based on the Bernstein “room-corridor” method and oscillatory integral estimates. The application to the case of the Gibbs measures $\mu_\pm=g_\pm$ with two different temperatures $T_{\pm}$ is given. It is proved that limit mean energy current density formally is $-\infty\cdot(0,\dots,0,T_+-T_-)$ for the Gibbs measures, and it is finite and equals $-C(0,\dots,0,T_+-T_-)$ with some positive constant $C>0$ for the smoothed solution. This corresponds to the second law of thermodynamics.

Keywords: Klein–Gordon equation, Cauchy problem, random initial data, mixing condition, Fourier transform, weak convergence of measures, Gaussian measures, covariance functions and matrices, characteristic functional.

Received: 21.10.2003
Revised: 09.05.2005

DOI: 10.4213/tvp125


 English version:
Theory of Probability and its Applications, 2006, 50:4, 582–611

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