The Mattila-Sjölin problem for the k-distance over a finite field

preprint2026arXivOpen access

Abstract

Let Fqd\mathbb{F}_q^d be a dd-dimensional vector space over a finite field Fq\mathbb{F}_q with qq elements. For x∈Fqdx\in \mathbb{F}_q^d, let ∥x∥=x12+⋯+xd2\|x\| = x_1^2+\dots+x_d^2. By abuse of terminology, we shall call ∥⋅∥\|\cdot\| a norm on Fqd\mathbb{F}_q^d. For a subset E⊂FqdE\subset \mathbb{F}_q^d, let Δ(E)Δ(E) be the distance set on EE defined as Δ(E):={∥x−y∥:x,y∈E}Δ(E):=\{\|x-y\| : x, y \in E \}. The Mattila-Sjölin problem seeks the smallest exponent α>0α>0 such that Δ(E)=FqΔ(E) =\mathbb{F}_q for all subsets E⊂FqdE \subset \mathbb{F}_q^d with ∣E∣≥Cqα|E| \geq Cq^α. In this article, we consider this problem for a variant of this norm, which generates a smaller distance set than the norm ∥⋅∥.\|\cdot\|. Namely, we replace the norm ∥⋅∥\|\cdot\| by the so-called kk-norm (1≤k≤d)(1 \leq k \leq d), which can be viewed as a kind of deformation of ∥⋅∥\|\cdot\|. To derive our result on the Mattila-Sjölin problem for the kk-norm, we use a combinatorial method to analyze various summations arising from the discrete Fourier machinery. Even though our distance set is smaller than the one in the Mattila-Sjölin problem, for some kk we still obtain the same result as that of Iosevich and Rudnev (2007), which deals with the Mattila-Sjölin problem. Furthermore, our result is sharp in all odd dimensions.

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