Decoupling the i.i.d. field and the randomisation field in the Curie-Weiss model

TL;DR

This paper presents a novel analytical approach to understanding the phase diagram of the Curie-Weiss model by decoupling the i.i.d. field and the randomisation field using De Finetti representation and Laplace inversion, revealing deep connections with Gaussian processes.

Contribution

It introduces a new method combining De Finetti representation and Laplace inversion to analyze the Curie-Weiss model's phase diagram and extends to other statistical mechanical models.

Findings

Unified explanation of phase transitions in the Curie-Weiss model

Extension of the approach to all spin laws including Bernoulli spins

Identification of a modified Brownian Sheet underlying the Gaussian limits

Abstract

Using the De Finetti representation of the Curie-Weiss model, the uniform coupling of Bernoulli random variables and the Laplace inversion formula (almost surely), we show that the full phase diagram of the Curie-Weiss model can be explained by a competition between the De Finetti randomisation and an approximate Gaussian process indexed by a complex variable that is equal to the inverse Laplace transform on a complex line of a Brownian Bridge. A more refined process type of rescaling shows that this is a modification of the Brownian Sheet that is at the core of all Gaussian random variables in the limits obtained in the model. This almost sure Laplace inversion approach allows moreover to treat all types of spin laws in the same vein as the Curie-Weiss Bernoulli spins. This gives a natural explanation of several results that already appeared in the literature in the subcritical and critical case in addition to produce new analogous results in the super-critical case. The functional approach here defined can moreover be extended to a wide class of statistical mechanical models that includes the Ising model in any dimension.