Locality approach to the bootstrap percolation paradox

Fuente: arXiv
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Main Authors: Hartarsky, Ivailo, Teixeira, Augusto
Format: Preprint
Published: 2024
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author Hartarsky, Ivailo
Teixeira, Augusto
author_facet Hartarsky, Ivailo
Teixeira, Augusto
contents We revisit the Bootstrap Percolation model, leveraging recent mathematical advances linking it with its local counterpart. This new perspective resolves, for the first time, historic discrepancies between Monte Carlo simulations and theoretical results: previously, those predictions disagreed even in the first-order asymptotics of the model. In contrast, our framework achieves excellent agreement between numerics and theory, which now match up to the third-order expansion, as the infection probability approaches zero. Our algorithm allows us to generate novel predictions for the model.
format Preprint
id arxiv_https___arxiv_org_abs_2410_01619
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Locality approach to the bootstrap percolation paradox
Hartarsky, Ivailo
Teixeira, Augusto
Statistical Mechanics
Probability
We revisit the Bootstrap Percolation model, leveraging recent mathematical advances linking it with its local counterpart. This new perspective resolves, for the first time, historic discrepancies between Monte Carlo simulations and theoretical results: previously, those predictions disagreed even in the first-order asymptotics of the model. In contrast, our framework achieves excellent agreement between numerics and theory, which now match up to the third-order expansion, as the infection probability approaches zero. Our algorithm allows us to generate novel predictions for the model.
title Locality approach to the bootstrap percolation paradox
topic Statistical Mechanics
Probability
url https://arxiv.org/abs/2410.01619