Abstract
We study long-range Bernoulli percolation on in which each two vertices and are connected by an edge with probability . It is a theorem of Noam Berger (CMP, 2002) that if then there is no infinite cluster at the critical parameter . We give a new, quantitative proof of this theorem establishing the power-law upper bound for every , where is the cluster of the origin. We believe that this is the first rigorous power-law upper bound for a Bernoulli percolation model that is neither planar nor expected to exhibit mean-field critical behaviour. As part of the proof, we establish a universal inequality implying that the maximum size of a cluster in percolation on any finite graph is of the same order as its mean with high probability. We apply this inequality to derive a new rigorous hyperscaling inequality relating the cluster-volume exponent and two-point function exponent .
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