Near-critical spanning forests and renormalization
St\'ephane Benoist, Laure Dumaz, Wendelin Werner

TL;DR
This paper investigates the scaling limits of two-dimensional spanning forests, relating them to a renormalization flow modeled by a Markov process, and proves convergence to a stationary distribution connected to SLE$_2$.
Contribution
It establishes a rigorous connection between the scaling limit of critical spanning forests and a stationary distribution of a renormalization Markov process, extending prior SLE convergence results.
Findings
Convergence of the Markov process to a stationary distribution representing the scaling limit.
Relation of the scaling limit to a stationary distribution of a coalescent-type Markov process.
Rigorous implementation of a formal renormalization framework for critical models.
Abstract
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…
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Taxonomy
TopicsStochastic processes and statistical mechanics · Theoretical and Computational Physics · Complex Network Analysis Techniques
