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Autore principale: Pan, Kewei
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2505.07907
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author Pan, Kewei
author_facet Pan, Kewei
contents In this article, we aim to define a Boolean entropy notion parallel to the framework of free entropy proposed by Voiculescu. Motivated by the work of Lenczewski and the work of Cébron & Gillers, we mainly investigated two random matrix models (the Gaussian Symmetric Block model and the Conditioned GUE model), in which asymptotic Boolean independence appears. We showed a large deviation principle for both models. As a result, the two rate functions coincide up to scaling and are minimized by the Rademacher distribution. Therefore, we refer to the logarithmic integral in the rate function as Boolean entropy. Finally, we proved this logarithmic integral is maximized by the Rademacher distribution and monotone along the Boolean Central Limit Theorem.
format Preprint
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publishDate 2025
record_format arxiv
spellingShingle An entropy for Boolean independence
Pan, Kewei
Probability
In this article, we aim to define a Boolean entropy notion parallel to the framework of free entropy proposed by Voiculescu. Motivated by the work of Lenczewski and the work of Cébron & Gillers, we mainly investigated two random matrix models (the Gaussian Symmetric Block model and the Conditioned GUE model), in which asymptotic Boolean independence appears. We showed a large deviation principle for both models. As a result, the two rate functions coincide up to scaling and are minimized by the Rademacher distribution. Therefore, we refer to the logarithmic integral in the rate function as Boolean entropy. Finally, we proved this logarithmic integral is maximized by the Rademacher distribution and monotone along the Boolean Central Limit Theorem.
title An entropy for Boolean independence
topic Probability
url https://arxiv.org/abs/2505.07907