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arXiv 2308.02232math.PRmath.NT
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通过随机矩阵方法研究Cohen-Lenstra启发式中的误差项

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

Yue Xu, Xiuwu Zhu

AI总结:

本文利用随机矩阵方法分析Cohen-Lenstra启发式的误差项,并推导有限域上随机矩阵余秩的渐近分布,将其建模为特殊马尔可夫链。

摘要:

Cohen-Lenstra启发式预测了数域上理想类群的分布。随机矩阵模型为解释这一启发式提供了自然框架,近期结果证明了这些工具的有效性。本文扩展了对随机矩阵模型的分析,以考察Cohen-Lenstra启发式中的误差项。此外,我们推导了有限域上随机矩阵的余秩(corank)的渐近分布,该过程可以建模为一类特殊的马尔可夫链。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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