Multipopulation spin models: A view from large deviations theoretic window

This paper studies large deviations properties of vectors of empirical means and measures generated as follows. Consider a sequence X 1 , X 2 ,..., X n of independent and identically distributed random variables partitioned into d-subgroups with sizes n 1 ,..., nd. Further, consider a d-dimensional vector mn whose coordinates are made up of the empirical means of the subgroups. We prove the following. (1) The sequence of vector of empirical means mn satisfies large deviations principle with rate n and rate function I, when the sequence X 1 , X 2 ,..., X n is RJ valued, with l ≥ 1. (2) Similar large deviations results hold for the corresponding sequence of vector of empirical measures Ln if Xi's, i = 1, 2,..., n, take on finitely many values. (3) The rate functions for the above large deviations principles are convex combinations of the corresponding rate functions arising from the large deviations principles of the coordinates of mn and Ln. The probability distributions used in the convex combinations are given by α = (α 1 ,..., αd) = lim n-→∞ (1/n)(n 1 ,..., nd). These results are consequently used to derive variational formula for the thermodynamic limit for the pressure of multipopulation Curie-Weiss (I. Gallo and P. Contucci (2008), and I. Gallo (2009)) and mean-field Pott's models, via a version of Varadhan's integral lemma for an equicontinuous family of functions. These multipopulation models serve as a paradigm for decision-making context where social interaction and other socioeconomic attributes of individuals play a crucial role.