English

Gaussian Fields on a hypercube from Long Range Random Walks

Probability 2025-10-22 v1

Abstract

We consider a class of Gaussian Free Fields denoted by (gx)xVN(g_x)_{x \in {\cal V}_N}, where VN={0,1}N {\cal V}_N = \{0,1\}^N and NZ+N\in \mathbb{Z}_+. These fields are related to a general class of NN-dimensional random walks on the hypercube, which are killed at a certain rate. The covariance structure of the Gaussian free field is determined by the Green function of these random walks. There exists a coupling such that the Gaussian free fields GN:=(gx)xVN{\cal G}_N := \big (g_{x}\big )_{x \in {\cal V}_N} form a Markov chain where NN is time. If the NN entries of the random walk are exchangeable, then the random variables in the Gaussian field can be coupled with spin glass models. A natural choice is to take the increments of the random walk to be from a de Finetti sequence with elements {0,1}\{0,1\}. The random walk is then well defined on V{\cal V}_\infty. The Green function and a strong representation for (gx)(g_x) are characterized by a point process which involves the de Finetti measure of the increments of the random walk. A limit theorem as NN\to \infty is found for level set sums of the Gaussian free field. In the limit Gaussian process the covariance function is a mixture of a bivariate normal density, with the correlation mixed by a distribution on [1,1][-1,1]. We also study a complex Gaussian field which is the transform of the Gaussian process limit.

Keywords

Cite

@article{arxiv.2510.18167,
  title  = {Gaussian Fields on a hypercube from Long Range Random Walks},
  author = {Robert Griffiths},
  journal= {arXiv preprint arXiv:2510.18167},
  year   = {2025}
}
R2 v1 2026-07-01T06:56:46.044Z