Optimizing Explicit Unit-Distance Lower-Bound Certificates

2026-06-02Artificial Intelligence

Artificial IntelligenceComputational GeometryNeural and Evolutionary Computing
AI summary

The authors discuss recent advances following the 2026 disproof of Erdős's unit-distance conjecture, which showed that you can have more than a tiny bit over n unit distances among n points on a plane. Sawin gave a quantitative improvement proving the number exceeds n to the power 1.014. The authors created a way to better choose certain number-related parameters using integer optimization techniques and developed a Python tool to verify and improve these choices. Their improved calculations push the exponent slightly higher to about 1.0152, giving a stronger lower bound on the maximum unit distances possible. All results depend on applying Sawin’s criteria exactly as stated.

Erdős unit-distance conjectureunit distancesplanar pointsinteger optimizationnonlinear integer programmingparameter selectionnumber theoryPython verificationevolution strategyquantitative bound
Authors
Michael T. M. Emmerich
Abstract
The 2026 disproof of Erdős's unit-distance conjecture and Sawin's subsequent explicit quantitative refinement show that the maximum number $u(n)$ of unit distances among $n$ planar points can exceed $n^{1+\varepsilon}$ for a fixed positive $\varepsilon$. Sawin's explicit bound gives more than $n^{1.014}$ unit distances for arbitrarily large $n$ and exposes finite parameters whose choice is not fully optimized. This report formulates the finite parameter-selection task as a variant of a nonlinear integer programming problem and proposes an open-source Python verification pipeline, first validated by reproducing Sawin's published parameter choice and then applied to computationally improved certificates. The main computational contribution is an integer optimization and checking procedure for the sets of primes $T$ and $S_Q$, the integer multiplicities $k(p)$, and a rationally encoded real parameter $R$. The optimization pipelines are intentionally lightweight and replicable on standard hardware: we propose a deterministic greedy construction heuristic, a Tailored Integer Evolution Strategy with repair operators for number-theoretic feasibility, and a two-parent discrete-recombination variant. Four certificate levels are compared: Sawin's published example with $δ=0.0141144286784982\ldots$, a greedy optimization certificate with $δ=0.0151718056372133\ldots$, a Tailored Integer Evolution Strategy certificate with rational $R=6672416/100000$ and $δ=0.0152616610684193\ldots$, and a Tailored Integer Evolution Strategy with discrete recombination, again with $R=6672416/100000$, giving $δ=0.0152628688170072\ldots$. Consequently, subject to Sawin's explicit criterion being applied exactly as cited, the best current certificate supports the cautious clean statement $u(n)>n^{1.0152}$ for arbitrarily large $n$.