An almost sure large deviation principle for the Hopfield model
classification
❄️ cond-mat
keywords
functionalmostcasedeviationhopfieldlargemodeloverlap
read the original abstract
We prove a large deviation principle for the finite dimensional marginals of the Gibbs distribution of the macroscopic `overlap'-parameters in the Hopfield model in the case where the number of random patterns, $M$, as a function of the system size $N$ satisfies $\limsup M(N)/N=0$. In this case the rate function (or free energy as a function of the overlap parameters) is independent of the disorder for almost all realization of the patterns and given by an explicit variational formula.
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