Exponential mixing in the supercritical regime
Prove that, for every admissible single-site measure and every inverse temperature $\beta>\beta_c$, the unique infinite-volume random cluster measure satisfies an exponential mixing estimate between events supported in $\Lambda_n$ and events supported outside $\Lambda_{2n}$, uniformly in $n$, with an error bounded by $e^{-cn}$ for some $c>0$.
References
A natural question is whether this can be upgraded to quantitative mixing estimates. In particular, we believe that the following exponential mixing property holds. For every $\beta>\beta_c$, there exists $c>0$ such that, for every $n\geq 1$, \begin{equation}\label{eq:exp_mixing} \sup_{\substack{A\in \sigma(\Lambda_n) \ B\in \sigma(\Lambda_{2n}c)} \big|\Psi_\beta[A\cap B] - \Psi_\beta[A]\Psi_\beta[B]\big| \leq e{-cn}, \end{equation} where $\sigma(\Lambda)$ denotes the $\sigma$-algebra generated by $(\omega_e){e\in \overline{E}(\Lambda)}$ and $(\mathsf{a}_x){x\in\Lambda}$, and where $\Psi_\beta$ denotes the (conjecturally) unique infinite volume measure at parameter $\beta$.
eq:exp_mixing:
It remains to be checked whether one can make it work for this specific application.