Long range voter models and dynamical fractional Brownian motion

Fuente: arXiv
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Main Author: Drogin, Reuben
Format: Preprint
Published: 2023
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author Drogin, Reuben
author_facet Drogin, Reuben
contents We study the voter model on Z with long-range interactions, as proposed by Hammond and Sheffield. We show a spacetime rescaling converges to a fractional Gaussian free field, which can be viewed as a one-parameter family of fractional Brownian motions. As a consequence, we obtain that long-range voter models rescale to fractional Gaussian noise. The argument uses the Lindeberg swapping technique and heat kernel estimates for random walks with jump distributions in the domain of attraction of a stable law.
format Preprint
id arxiv_https___arxiv_org_abs_2311_03662
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Long range voter models and dynamical fractional Brownian motion
Drogin, Reuben
Probability
We study the voter model on Z with long-range interactions, as proposed by Hammond and Sheffield. We show a spacetime rescaling converges to a fractional Gaussian free field, which can be viewed as a one-parameter family of fractional Brownian motions. As a consequence, we obtain that long-range voter models rescale to fractional Gaussian noise. The argument uses the Lindeberg swapping technique and heat kernel estimates for random walks with jump distributions in the domain of attraction of a stable law.
title Long range voter models and dynamical fractional Brownian motion
topic Probability
url https://arxiv.org/abs/2311.03662