Gibbs Measures Over Locally Tree-Like Graphs and Percolative Entropy Over Infinite Regular Trees

Consider a statistical physical model on the d-regular infinite tree \(T_{d}\) described by a set of interactions \(\Phi \). Let \(\{G_{n}\}\) be a sequence of finite graphs with vertex sets \(V_n\) that locally converge to \(T_{d}\). From \(\Phi \) one can construct a sequence of corresponding models on the graphs \(G_n\). Let \(\{\mu _n\}\) be the resulting Gibbs measures. Here we assume that \(\{\mu _{n}\}\) converges to some limiting Gibbs measure \(\mu \) on \(T_{d}\) in the local weak\(^*\) sense, and study the consequences of this convergence for the specific entropies \(|V_n|^{-1}H(\mu _n)\). We show that the limit supremum of \(|V_n|^{-1}H(\mu _n)\) is bounded above by the percolative entropy \(H_{\textit{perc}}(\mu )\), a function of \(\mu \) itself, and that \(|V_n|^{-1}H(\mu _n)\) actually converges to \(H_{\textit{perc}}(\mu )\) in case \(\Phi \) exhibits strong spatial mixing on \(T_d\). When it is known to exist, the limit of \(|V_n|^{-1}H(\mu _n)\) is most commonly shown to be given by the Bethe ansatz. Percolative entropy gives a different formula, and we do not know how to connect it to the Bethe ansatz directly. We discuss a few examples of well-known models for which the latter result holds in the high temperature regime.