N ov 2 00 1 ORNSTEIN - ZERNIKE THEORY FOR THE FINITE RANGE ISING MODELS ABOVE

Rigorous nonperturbative Ornstein-Zernike theory for Ising ferromagnets

– We rigorously derive the Ornstein-Zernike asymptotics of the pair-correlation functions for finite-range Ising ferromagnets in any dimensions and at any temperature above critical. The celebrated heuristic argument by Ornstein and Zernike [1] implies that the asymptotic form of the truncated two-point density correlation function of simple fluids away from the critical region is given by G(~r...

ORNSTEIN-ZERNIKE THEORY FOR FINITE RANGE ISING MODELS ABOVE Tc

We derive a precise Ornstein-Zernike asymptotic formula for the decay of the two-point function 〈σ0σx〉β in the general context of finite range Ising type models on Z. The proof relies in an essential way on the a-priori knowledge of the strict exponential decay of the two-point function and, by the sharp characterization of phase transition due to Aizenman, Barsky and Fernández, goes through in...

Ornstein-zernike Theory for the Finite Range Ising

A pr 2 00 3 Random path representation and sharp correlations asymptotics at high - temperatures

We recently introduced a robust approach to the derivation of sharp asymptotic formula for correlation functions of statistical mechanics models in the high-temperature regime. We describe its application to the nonperturbative proof of Ornstein-Zernike asymptotics of 2-point functions for self-avoiding walks, Bernoulli percolation and ferromagnetic Ising models. We then extend the proof, in th...

J an 1 99 8 A self - consistent Ornstein - Zernike approximation for the Random Field Ising model

We extend the self-consistent Ornstein-Zernike approximation (SCOZA), first formulated in the context of liquid-state theory, to the study of the random field Ising model. Within the replica formalism, we treat the quenched random field as an annealed spin variable, thereby avoiding the usual average over the random field distribution. This allows to study the influence of the distribution on t...