The random pseudo-metric on a graph defined via the zero-set of the Gaussian free field on its metric graph
Titus Lupu, Wendelin Werner

TL;DR
This paper explores a new pseudo-metric derived from the Gaussian free field on metric graphs, relating it to reflected GFF, explicit distributions, and potential scaling limits connected to conformal invariance and CLE(4) loops.
Contribution
It introduces and analyzes a novel pseudo-metric based on the GFF's local time at zero on metric graphs, extending classical Brownian motion results.
Findings
Derived a pathwise transformation relating GFF and reflected GFF via the pseudo-metric.
Explicitly computed the distribution of the pseudo-distance between boundary points.
Connected the pseudo-metric's properties to network resistance and potential conformal invariance in scaling limits.
Abstract
We further investigate properties of the Gaussian free field (GFF) on the metric graph associated to a discrete weighted graph (where the edges of the latter are replaced by continuous line-segments of appropriate length) that has been introduced by the first author. On such a metric graph, the GFF is a random continuous function that generalises one-dimensional Brownian bridges so that one-dimensional techniques can be used. In the present paper, we define and study the pseudo-metric defined on the metric graph (and therefore also on the discrete graph itself), where the length of a path on the metric graph is defined to be the local time at level zero accumulated by the Gaussian free field along this path. We first derive a pathwise transformation that relates the GFF on the metric graph with the reflected GFF on the metric graph via the pseudo-distance defined by the latter. This…
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.
