Pivotal, cluster and interface measures for critical planar percolation
arXiv:1008.1378
Abstract
This work is the first in a series of papers devoted to the construction and study of scaling limits of dynamical and near-critical planar percolation and related objects like invasion percolation and the Minimal Spanning Tree. We show here that the counting measure on the set of pivotal points of critical site percolation on the triangular grid, normalized appropriately, has a scaling limit, which is a function of the scaling limit of the percolation configuration. We also show that this limit measure is conformally covariant, with exponent 3/4. Similar results hold for the counting measure on macroscopic open clusters (the area measure), and for the counting measure on interfaces (length measure). Since the aforementioned processes are very much governed by pivotal sites, the construction and properties of the "local time"-like pivotal measure are key results in this project. Another application is that the existence of the limit length measure on the interface is a key step towards constructing the so-called natural time-parametrization of the SLE(6) curve. The proofs make extensive use of coupling arguments, based on the separation of interfaces phenomenon. This is a very useful tool in planar statistical physics, on which we included a self-contained Appendix. Simple corollaries of our methods include ratio limit theorems for arm probabilities and the rotational invariance of the two-point function.
99 pages, 18 figures. Minor changes, very close to published version
References in corpus (6)
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Cited by in corpus (6)
- On the scaling limits of planar percolation
- Brownian Gibbs property for Airy line ensembles
- Towards Conformal Invariance and a Geometric Representation of the 2D Ising Magnetization Field
- Brownian Web in the Scaling Limit of Supercritical Oriented Percolation in Dimension 1+1
- Frozen percolation in two dimensions
- Exit time tails from pairwise decorrelation in hidden Markov chains, with applications to dynamical percolation