NEAR-CRITICAL SPANNING FORESTS AND RENORMALIZATION

• 成果类型: Article
• 署名作者: Benoist, Stephane; Dumaz, Laure; Werner, Wendelin
• 署名单位: Massachusetts Institute of Technology (MIT); Universite PSL; Universite Paris-Dauphine; Centre National de la Recherche Scientifique (CNRS); Swiss Federal Institutes of Technology Domain; ETH Zurich
• 刊物名称: ANNALS OF PROBABILITY
• ISSN/ISSBN: 0091-1798
• DOI: 10.1214/19-AOP1413
• 发表日期: 2020
• 页码: 1980-2013
• 关键词: erased random-walk; discrete complex-analysis; SCALING LIMITS

摘要

We study random two-dimensional spanning forests in the plane that can be viewed both in the discrete case and in their appropriately taken scaling limits as a uniformly chosen spanning tree with some Poissonian deletion of edges or points. We show how to relate these scaling limits to a stationary distribution of a natural coalescent-type Markov process on a state space of abstract graphs with real-valued edge weights. This Markov process can be interpreted as a renormalization flow. This provides a model for which one can rigorously implement the formalism proposed by the third author in order to relate the law of the scaling limit of a critical model to a stationary distribution of such a renormalization/Markov process. When starting from any two-dimensional lattice with constant edge weights, the Markov process does indeed converge in law to this stationary distribution that corresponds to a scaling limit of UST with Poissonian deletions. The results of this paper heavily build on the convergence in distribution of branches of the UST to SLE2 (a result by Lawler, Schramm and Werner) as well as on the convergence of the suitably renormalized length of the loop-erased random walk to the natural parametrization of the SLE2 (a recent result by Lawler and Viklund).