Furstenberg Sets in Finite Fields: Explaining and Improving the Ellenberg–Erman Proof

IF 0.6 3区 数学 Q4 COMPUTER SCIENCE, THEORY & METHODS
Manik Dhar, Zeev Dvir, Ben Lund
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引用次数: 3

Abstract

A (km)-Furstenberg set is a subset \(S \subset {\mathbb {F}}_q^n\) with the property that each k-dimensional subspace of \({\mathbb {F}}_q^n\) can be translated so that it intersects S in at least m points. Ellenberg and Erman (Algebra Number Theory 10(7), 1415–1436 (2016)) proved that (km)-Furstenberg sets must have size at least \(C_{n,k}m^{n/k}\), where \(C_{n,k}\) is a constant depending only n and k. In this paper, we adopt the same proof strategy as Ellenberg and Erman, but use more elementary techniques than their scheme-theoretic method. By modifying certain parts of the argument, we obtain an improved bound on \(C_{n,k}\), and our improved bound is nearly optimal for an algebraic generalization the main combinatorial result. We also extend our analysis to give lower bounds for sets that have large intersection with shifts of a specific family of higher-degree co-dimension \(n-k\) varieties, instead of just co-dimension \(n-k\) subspaces.

有限域中的Furstenberg集:对Ellenberg-Erman证明的解释和改进
A (k, m)-Furstenberg集合是一个子集\(S \subset {\mathbb {F}}_q^n\),其性质是\({\mathbb {F}}_q^n\)的每个k维子空间都可以平移,使其与S相交至少m个点。Ellenberg和Erman(代数数论10(7),1415-1436(2016))证明(k, m)-Furstenberg集合必须至少具有\(C_{n,k}m^{n/k}\)的大小,其中\(C_{n,k}\)是仅依赖于n和k的常数。在本文中,我们采用了与Ellenberg和Erman相同的证明策略,但使用了比他们的方案理论方法更初级的技术。通过修改参数的某些部分,我们得到了\(C_{n,k}\)上的改进界,并且改进界对于主要组合结果的代数推广是几乎最优的。我们还扩展了我们的分析,给出了与特定高次协维\(n-k\)变体族的位移有大交集的集合的下界,而不仅仅是协维\(n-k\)子空间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Discrete & Computational Geometry
Discrete & Computational Geometry 数学-计算机:理论方法
CiteScore
1.80
自引率
12.50%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Discrete & Computational Geometry (DCG) is an international journal of mathematics and computer science, covering a broad range of topics in which geometry plays a fundamental role. It publishes papers on such topics as configurations and arrangements, spatial subdivision, packing, covering, and tiling, geometric complexity, polytopes, point location, geometric probability, geometric range searching, combinatorial and computational topology, probabilistic techniques in computational geometry, geometric graphs, geometry of numbers, and motion planning.
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