Error term in the Cohen-Lenstra heuristic via random matrix approach

Fuente: arXiv
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Autores principales: Xu, Yue, Zhu, Xiuwu
Formato: Preprint
Publicado: 2023
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author Xu, Yue
Zhu, Xiuwu
author_facet Xu, Yue
Zhu, Xiuwu
contents The Cohen-Lenstra heuristic predicts the distribution of ideal class groups over number fields. Random matrix models provide a natural framework for explaining this heuristic, and recent results demonstrate the effectiveness of these tools. In this paper, we extend the analysis of the random matrix model to examine the error term in the Cohen-Lenstra heuristic. Additionally, we derive the asymptotic distribution of the corank of random matrices over finite fields, which can be modeled as a special class of Markov chains.
format Preprint
id arxiv_https___arxiv_org_abs_2308_02232
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Error term in the Cohen-Lenstra heuristic via random matrix approach
Xu, Yue
Zhu, Xiuwu
Probability
Number Theory
The Cohen-Lenstra heuristic predicts the distribution of ideal class groups over number fields. Random matrix models provide a natural framework for explaining this heuristic, and recent results demonstrate the effectiveness of these tools. In this paper, we extend the analysis of the random matrix model to examine the error term in the Cohen-Lenstra heuristic. Additionally, we derive the asymptotic distribution of the corank of random matrices over finite fields, which can be modeled as a special class of Markov chains.
title Error term in the Cohen-Lenstra heuristic via random matrix approach
topic Probability
Number Theory
url https://arxiv.org/abs/2308.02232