We investigate a one-dimensional chain of 2N harmonic oscillators in which neighboring sites have their energies redistributed randomly. The sites -N and N are in contact with thermal reservoirs at different temperature tau- and tau+. Kipnis et al. (J. Statist. Phys., 27:65-74 (1982).) proved that this model satisfies Fourier's law and that in the hydrodynamical scaling limit, when N ->infinity, the stationary state has a linear energy density profile (theta) over bar (u), u is an element of [- 1, 1]. We derive the large deviation function S(.( u)) for the probability of finding, in the stationary state, a profile theta(u) different from (theta) over bar (u). The function S(theta) has striking similarities to, but also large differences from, the corresponding one of the symmetric exclusion process. Like the latter it is nonlocal and satisfies a variational equation. Unlike the latter it is not convex and the Gaussian normal fluctuations are enhanced rather than suppressed compared to the local equilibrium state. We also briefly discuss more general models and find the features common in these two and other models whose S(theta) is known.
Large deviations for a stochastic model of heat flow / BERTINI MALGARINI, Lorenzo; Davide, Gabrielli; Joel L., Lebowitz. - In: JOURNAL OF STATISTICAL PHYSICS. - ISSN 0022-4715. - 121:5-6(2005), pp. 843-885. [10.1007/s10955-005-5527-2]
Large deviations for a stochastic model of heat flow
BERTINI MALGARINI, Lorenzo;
2005
Abstract
We investigate a one-dimensional chain of 2N harmonic oscillators in which neighboring sites have their energies redistributed randomly. The sites -N and N are in contact with thermal reservoirs at different temperature tau- and tau+. Kipnis et al. (J. Statist. Phys., 27:65-74 (1982).) proved that this model satisfies Fourier's law and that in the hydrodynamical scaling limit, when N ->infinity, the stationary state has a linear energy density profile (theta) over bar (u), u is an element of [- 1, 1]. We derive the large deviation function S(.( u)) for the probability of finding, in the stationary state, a profile theta(u) different from (theta) over bar (u). The function S(theta) has striking similarities to, but also large differences from, the corresponding one of the symmetric exclusion process. Like the latter it is nonlocal and satisfies a variational equation. Unlike the latter it is not convex and the Gaussian normal fluctuations are enhanced rather than suppressed compared to the local equilibrium state. We also briefly discuss more general models and find the features common in these two and other models whose S(theta) is known.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.