Abstract

Let f be a stationary isotropic non-degenerate Gaussian field on R2. Assume that f=q∗W where q∈L2(R2)∩C2(R2) and W is the L2 white noise on R2. We extend a result by Stephen Muirhead and Hugo Vanneuville by showing that, assuming that q∗q is pointwise non-negative and has fast enough decay, the set {f≥−l} percolates with probability one when l>0 and with probability zero if l≤0. We also prove exponential decay of crossing probabilities and uniqueness of the unbounded cluster. To this end, we study a Gaussian field g defined on the torus and establish a superconcentration formula for the threshold T(g) which is the minimal value such that {g≥−T(g)} contains a non-contractible loop. This formula follows from a Gaussian Talagrand type inequality.

Highlights

  • Let f be a stationary isotropic non-degenerate Gaussian field on R2

  • We aimed to provide a proof inspired more by the KKL inequality than randomized algorithms and presented in the native language of smooth Gaussian fields, in order to bring out the underlying mechanism

  • Let f be a Gaussian field on R2 of the form q ∗ W where W is the L2 white noise on R2 and q satisfies the (Strong) version of Conditions 1.1 and 1.5, as well as Conditions 1.3 1.4 and the (Weak) Condition 1.2

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Summary

Introduction

1.1 On previous results in Gaussian field percolation and the contributions of the present work. Otherwise, by stationarity, f would satisfy a non-trivial differential equation of the form λf + μ∂vf = 0 which would contradict the decay in pointwise correlations It was shown by Pitt in [24] that the (Weak) Condition 1.5 is equivalent to a certain form of the FKG inequality (see Lemma 4.5 below). Let f be a Gaussian field on R2 of the form q ∗ W where W is the L2 white noise on R2 and q satisfies the (Strong) version of Conditions 1.1 and 1.5, as well as Conditions 1.3 and 1.4, and the (Weak) Condition 1.2.

The key formula
The concentration formula for TA
A Gaussian Talagrand inequality
Perfect Morse functions and the derivative of TA
The discrete white noise approximation
General approximation arguments
Percolation estimates
The conclusion
Orthogonal expansions and the Cameron-Martin space
Supremum bounds
An approximation result

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