More unit distances in arbitrary norms
Josef Greilhuber, Carl Schildkraut, Jonathan Tidor
TL;DR
The paper advances the unit distance problem in arbitrary norms on $\mathbb{R}^d$ by showing a universal lower bound $U_{\|\cdot\|}(n) \ge \big(\tfrac{d}{2}-o(1)\big) n \log_2 n$ for every norm, matching the best known upper bound up to $o(1)$ and extending the $d$-dimensional construction via generalized arithmetic progressions and dimension-theoretic tools. It develops a comprehensive framework in which a 2D warm-up is generalized to all dimensions, using shadow boundaries, carefully chosen point sets, and GAP-based counting to guarantee many unit distances. In addition, for $d\ge 3$ and a comeagre set of norms, the unit distance graph contains $K_{d,m}$ for all $m$, established via a local model and Brouwer degree stability, illustrating robust structural richness in typical norms. Altogether, the work tightens asymptotics for arbitrary norms and reveals strong bipartite-complete structures in typical higher-dimensional norms, contributing a blend of combinatorial, topological, and convex-geometry methods.
Abstract
For $d\geq 2$ and any norm on $\mathbb R^d$, we prove that there exists a set of $n$ points that spans at least $(\tfrac d2-o(1))n\log_2n$ unit distances under this norm for every $n$. This matches the upper bound recently proved by Alon, Bucić, and Sauermann for typical norms (i.e., norms lying in a comeagre set). We also show that for $d\geq 3$ and a typical norm on $\mathbb R^d$, the unit distance graph of this norm contains a copy of $K_{d,m}$ for all $m$.
