Percolation for 2D classical Heisenberg model and exit sets of vector valued GFF
Juhan Aru, Christophe Garban, Avelio Sep\'ulveda

TL;DR
This paper investigates the geometry of exit sets associated with 2D vector-valued GFFs, their percolation properties, and implications for spin models, providing new rigorous results and counterexamples in statistical physics.
Contribution
It introduces a detailed geometric analysis of exit sets for vector-valued GFFs, linking them to percolation and spin model behavior, and offers rigorous proofs and counterexamples related to the massiveness of spin models.
Findings
Exit sets are almost surely degenerate for N≥2.
High β transverse fluctuations are described by a 2D vector GFF.
Constructed environments show XY model can be massive despite high conductances.
Abstract
Our motivation in this paper is twofold. First, we study the geometry of a class of exploration sets, called exit sets, which are naturally associated with a 2D vector-valued GFF : . We prove that, somewhat surprisingly, these sets are a.s. degenerate as long as , while they are conjectured to be macroscopic and fractal when . This analysis allows us, when , to understand the percolation properties of the level sets of and leads us to our second main motivation in this work: if one projects a spin model (classical Heisenberg model is ) down to a spin model, we end up with a spin in a quenched disorder given by random conductances on . Using the exit sets of the -vector-valued GFF, we obtain a local and geometric description of this random disorder in the limit $\beta\to…
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Taxonomy
TopicsTheoretical and Computational Physics · Markov Chains and Monte Carlo Methods · Quantum many-body systems
