Stochastic Localization with Non-Gaussian Tilts and Applications to Tensor Ising Models

Fuente: arXiv
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Main Authors: Mikulincer, Dan, Piana, Arianna
Format: Preprint
Published: 2024
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author Mikulincer, Dan
Piana, Arianna
author_facet Mikulincer, Dan
Piana, Arianna
contents We present generalizations and modifications of Eldan's Stochastic Localization process, extending it to incorporate non-Gaussian tilts, making it useful for a broader class of measures. As an application, we introduce new processes that enable the decomposition and analysis of non-quadratic potentials on the Boolean hypercube, with a specific focus on quartic polynomials. Using this framework, we derive new spectral gap estimates for tensor Ising models under Glauber dynamics, resulting in rapid mixing.
format Preprint
id arxiv_https___arxiv_org_abs_2412_12720
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Stochastic Localization with Non-Gaussian Tilts and Applications to Tensor Ising Models
Mikulincer, Dan
Piana, Arianna
Probability
Mathematical Physics
Functional Analysis
We present generalizations and modifications of Eldan's Stochastic Localization process, extending it to incorporate non-Gaussian tilts, making it useful for a broader class of measures. As an application, we introduce new processes that enable the decomposition and analysis of non-quadratic potentials on the Boolean hypercube, with a specific focus on quartic polynomials. Using this framework, we derive new spectral gap estimates for tensor Ising models under Glauber dynamics, resulting in rapid mixing.
title Stochastic Localization with Non-Gaussian Tilts and Applications to Tensor Ising Models
topic Probability
Mathematical Physics
Functional Analysis
url https://arxiv.org/abs/2412.12720