Erdős unit distance exponent
Description of constant
For a finite set $P \subset \mathbb{R}^2$ of $n$ points, let \(u(P) := \lvert \\{ \\{x,y\\} \subset P : \lvert x-y \rvert = 1 \\} \rvert\) denote the number of unordered pairs of points in $P$ at unit distance, and let $u(n) := \max_{\lvert P\rvert = n} u(P)$ denote the maximum number of unit distances among any set of $n$ points in the plane. The Erdős unit distance exponent is \(C_{84} := \limsup_{n \to \infty} \frac{\log u(n)}{\log n}.\) Equivalently, $C_{84}$ is the infimum of all $\alpha$ for which $u(n) \ll_\alpha n^\alpha$ as $n \to \infty$.
The problem was introduced by Erdős in 1946 [E1946], who conjectured that $u(n) = n^{1+o(1)}$, i.e. $C_{84} = 1$. This conjecture was disproved in May 2026 by an OpenAI internal model [O2026], with a human-verified writeup given in [ABGLSSTWW2026]; an explicit improved lower bound was obtained shortly afterwards by Sawin [S2026].
Known upper bounds
| Bound | Reference | Comments |
|---|---|---|
| $3/2$ | [E1946] | Erdős’ original argument, based on the observation that the unit-distance graph contains no $K_{2,3}$. |
| $4/3 = 1.333\dots$ | [SST1984] | Spencer, Szemerédi and Trotter; via the Szemerédi–Trotter incidence theorem. |
Known lower bounds
| Bound | Reference | Comments |
|---|---|---|
| $1$ | [E1946] | A $\sqrt{n} \times \sqrt{n}$ portion of the integer lattice gives $u(n) \gg n^{1 + c/\log\log n}$, hence $\limsup \log u(n)/\log n \geq 1$. Conjectured by Erdős to be sharp. |
| $> 1$ (inexplicit) | [O2026], [ABGLSSTWW2026] | An OpenAI internal reasoning model produced a (one-shot) construction giving $u(n) \gg n^{1+\varepsilon}$ for some $\varepsilon > 0$, disproving Erdős’ conjecture. The construction is number-theoretic, using algebraic number fields of large degree and small discriminant via a Golod–Shafarevich argument. A particular parameter choice in [ABGLSSTWW2026] yields the explicit value $\varepsilon \approx 6.24 \cdot 10^{-38}$. |
| $1.014$ | [S2026] | Sawin, by optimizing the Golod–Shafarevich step and the choice of number field. |
Additional comments and links
- The unit distance problem is one of the most well-known problems of Erdős in combinatorial geometry. The bound $u(n) \ll n^{4/3}$ of [SST1984] has not been improved in its exponent; subsequent work has only sharpened the implicit constant (see e.g. [AS2020]).
- The OpenAI announcement [O2026] is the first widely publicized example of an autonomous AI system producing a one-shot disproof of a long-standing open conjecture in mathematics.
- The same techniques apply to the related problem of constructing point sets with many distinct pairs at any fixed algebraic distance; see [ABGLSSTWW2026] for discussion.
- A closely related quantity is the distinct distance exponent $\liminf \log d(n)/\log n$, where $d(n)$ is the minimum number of distinct distances determined by $n$ points in the plane; this was shown to equal $1$ (up to a $\sqrt{\log n}$ factor) by Guth and Katz (2015).
References
- [E1946] Erdős, Paul. On sets of distances of $n$ points. American Mathematical Monthly 53 (1946), 248–250. DOI: 10.2307/2305092.
- [SST1984] Spencer, Joel; Szemerédi, Endre; Trotter, William T. Unit distances in the Euclidean plane. In: Graph Theory and Combinatorics (Cambridge, 1983), pp. 293–303, Academic Press, London, 1984.
- [AS2020] Ágoston, Péter; Pálvölgyi, Dömötör. An improved constant factor for the unit distance problem. arXiv:2006.06285 (2020).
- [O2026] OpenAI. An OpenAI model has disproved a central conjecture in discrete geometry. Blog post, 20 May 2026. openai.com/index/model-disproves-discrete-geometry-conjecture.
- [ABGLSSTWW2026] Alon, Noga; Bloom, Thomas F.; Gowers, W. T.; Litt, Daniel; Sawin, Will; Shankar, Arul; Tsimerman, Jacob; Wang, Victor; Wood, Melanie Matchett. Remarks on the disproof of the unit distance conjecture. arXiv:2605.20695 (2026).
- [S2026] Sawin, Will. An explicit lower bound for the unit distance problem. arXiv:2605.20579 (2026).
Contribution notes
Prepared with assistance from Claude Opus 4.7, which retrieved abstracts of the May 2026 preprints and the OpenAI announcement. All references should be independently verified before citation.