GENERATING GALTON-WATSON TREES USING RANDOM WALKS AND PERCOLATION FOR THE GAUSSIAN FREE FIELD

• 成果类型: Article
• 署名作者: Drewitz, Alexander; Gallo, Gioele; Prevost, Alexis
• 署名单位: University of Cologne; University of Geneva
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• DOI: 10.1214/23-AAP2022
• 发表日期: 2024
• 页码: 2844-2884
• 关键词: level-set percolation; random interlacements; clusters; systems

摘要

The study of Gaussian free field level sets on supercritical Galton- Watson trees has been initiated by Ab & auml;cherli and Sznitman in 2018. By means of entirely different tools, we continue this investigation and generalize their main result on the positivity of the associated percolation critical parameter h* to the setting of arbitrary supercritical offspring distribution and random conductances. In our setting, this establishes a rigorous proof of the physics literature mantra that positive correlations facilitate percolation when compared to the independent case. Our proof proceeds by constructing the Galton-Watson tree through an exploration via finite random walk trajectories. This exploration of the tree progressively unveils an infinite connected component in the random interlacements set on the tree, which is stable under small quenched noise. Using a Dynkin-type isomorphism theorem, we then infer the strict positivity of the critical parameter h*. As a byproduct, we obtain transience results for the above-mentioned sets.