Shadow and percolation II: discrete and continuous landscapes with correlations
David Vernotte
TL;DR
This work studies shadow percolation for planar Gaussian landscapes by introducing the slope field $\alpha^f$ to identify lit and shadow regions. The authors develop finite-range approximations and a two-scale renormalization framework to transfer local crossing events into global percolation structure, handling both continuous landscapes with correlations and discrete, correlated fields. They establish a nontrivial phase transition: for continuous fields with sufficiently fast decay ($\beta>\frac{5}{2}$) there exists $\ell_1>0$ such that $\{\alpha^f\le\ell\}$ contains a unique unbounded component while $\{\alpha^f\ge\ell\}$ has no unbounded component for every $\ell>\ell_1$, and a parallel discrete result shows corresponding transitions for $\alpha^X$. The methods combine Gaussian-field approximation, renormalization, and gluing arguments to overcome lack of standard percolation properties, offering insights into phase transitions in correlated planar random fields with geometric illumination interpretations.
Abstract
In this paper we consider a discrete or continuous landscape with correlations and we consider a source of light (a sun) at infinity emitting parallel rays of light making a slope l with the horizontal plane. Depending on the value of l some portions of the landscape may be lit by the sun or be in the shadow. Under some assumptions, we show that if l is big enough then there exists a giant component of light. However, if l>0 is small enough and if we are in discrete case, then there exists a giant component of shadow. We relate this problem to the study of the percolation properties of a new random planar field.
