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arXiv 2001.05428math.NT
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伽罗瓦扩张族中Frobenius元素的分布

Distribution of Frobenius elements in families of Galois extensions

Daniel Fiorilli, Florent Jouve

AI总结:

该研究通过伽罗瓦群表示与分歧理论不变量刻画伽罗瓦扩张族中Frobenius元素的精细分布,改进了GRH下Chebotarev密度定理误差项的波动上界,推广了相关经典结果并解决了公开问题。

摘要:

给定数域的伽罗瓦扩张$L/K$,我们通过有限伽罗瓦群表示与分歧理论中的不变量,刻画Frobenius元素的精细分布性质。我们构造了显式的扩张族,在其中计算这些不变量,并推导出对可能不对称性的细致理解与精确描述。我们建立了Chebotarev密度定理中误差项的通用波动上界,在广义黎曼假设(GRH)下,该上界优于Murty-Murty-Saradha与Bellaïche对Lagarias-Odlyzko界和Serre界的改进结果,且我们认为该界是最优的(在单零点假设下,其精度与Montgomery关于等差数列中素数的猜想相当)。在GRH以及某一高度内零点重数的假设下,我们证明在某些族中这些波动由一个常数低阶项主导。作为我们思路的应用,我们改进并推广了K. Murty与J. Bellaïche的结果,同时回答了N. Ng的一个问题。特别地,当$L/\boldsymbol{\rm Q}$是伽罗瓦且超可解扩张时,我们证明了K. Murty关于给定Frobenius集合中最小范数的非分歧素理想的一个强形式猜想。我们使用的工具包括基于极限分布的Rubinstein-Sarnak方法,以及代数、解析、表示论、概率与组合技术的结合。

英文摘要:

Given a Galois extension $L/K$ of number fields, we describe fine distribution properties of Frobenius elements via invariants from representations of finite Galois groups and ramification theory. We exhibit explicit families of extensions in which we evaluate these invariants, and deduce a detailed understanding and a precise description of the possible asymmetries. We establish a general bound on the generic fluctuations of the error term in the Chebotarev density theorem which under GRH is sharper than the Murty-Murty-Saradha and Bellaïche refinements of the Lagarias-Odlyzko and Serre bounds, and which we believe is best possible (assuming simplicity, it is of the quality of Montgomery's conjecture on primes in arithmetic progressions). Under GRH and a hypothesis on the multiplicities of zeros up to a certain height, we show that in certain families these fluctuations are dominated by a constant lower order term. As an application of our ideas we refine and generalize results of K. Murty and of J. Bellaïche and we answer a question of N. Ng. In particular, in the case where $L/\mathbb Q$ is Galois and supersolvable, we prove a strong form of a conjecture of K. Murty on the unramified prime ideal of least norm in a given Frobenius set. The tools we use include the Rubinstein-Sarnak machinery based on limiting distributions and a blend of algebraic, analytic, representation theoretic, probabilistic and combinatorial techniques.

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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