Multiscale coupling and the maximum of $\mathcal{P}(\phi)_2$ models on the torus
Nikolay Barashkov, Trishen S. Gunaratnam, Michael Hofstetter

TL;DR
This paper constructs a multiscale coupling between the $ obreak ext{P}( ext{phi})_2$ measure and the Gaussian free field on the torus, enabling analysis of the field's maximum and its convergence to a Gumbel distribution.
Contribution
It introduces a novel coupling method linking $ ext{P}( ext{phi})_2$ measures with Gaussian free fields across scales using the Polchinski renormalisation group and stochastic control techniques.
Findings
Established a multiscale coupling between $ ext{P}( ext{phi})_2$ and Gaussian free field.
Proved the maximum of the $ ext{P}( ext{phi})_2$ field converges to a Gumbel distribution.
Applied regularity estimates to analyze the field's maximum behavior.
Abstract
We establish a coupling between the measure and the Gaussian free field on the two-dimensional unit torus at all spatial scales, quantified by probabilistic regularity estimates on the difference field. Our result includes the well-studied measure. The proof uses an exact correspondence between the Polchinski renormalisation group approach, which is used to define the coupling, and the Bou\'e-Dupuis stochastic control representation for . More precisely, we show that the difference field is obtained from a specific minimiser of the variational problem. This allows to transfer regularity estimates for the small-scales of minimisers, obtained using discrete harmonic analysis tools, to the difference field. As an application of the coupling, we prove that the maximum of the field on the discretised torus with…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and statistical mechanics · Theoretical and Computational Physics · Advanced Mathematical Modeling in Engineering
