On the coordinatewise ordered configuration space, stochastically dominates when for every increasing real function . Equivalently, for every increasing event. The Holley condition is the sufficient cross-lattice inequality
Here join and meet are coordinatewise maximum and minimum. This condition implies by the Holley inequality; it is not asserted to be necessary. It can be checked on unnormalized weights, since their normalization constants cancel.
Use the weights
For the upper bound, take and . Since open-edge count is modular, the Bernoulli factors cancel in the Holley ratio, leaving
The last inequality uses and the fact that removing edges cannot reduce the number of components. Thus .
For the lower bound, let . Its odds satisfy
Set , the number of edges added to in the union. For and , the corresponding ratio is
Adding one edge either merges two components or leaves the count unchanged. Therefore adding edges reduces by at most , proving the exponent nonnegative. This also proves the hinted monotonicity of rather than assuming it. The Holley condition now proves both Bernoulli bounds for the random-cluster model:
The same argument holds with wired boundary conditions: identify the wired boundary vertices first and count components on that quotient graph. Taking finite-volume wired limits preserves every increasing cylinder-event inequality. Approximating by the decreasing events consequently gives
Let . For , the upper bound makes the wired percolation probability zero, so . If and , the lower bound makes it positive. Solving this strict inequality,
Taking infima proves
For , the lower bound and the trivial upper bound give the same conclusion. No assumption about percolation at the critical parameter is required.