97-232 Timo Seppalainen
Entropy for Translation-Invariant Random-Cluster Measures (108K, AMS-TeX) Apr 20, 97
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Abstract. We study translation-invariant random-cluster measures with techniques from large deviation theory and convex analysis. In particular, we prove a large deviation principle with rate function given by a specific entropy, and a DLR variational principle that characterizes translation-invariant random-cluster measures as the solutions of the variational equation for free energy. Consequences of these theorems include results about edge and cluster densities of translation-invariant random-cluster measures.

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