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The higher-dimensional Erdős distinct-distances conjecture

OpenAI groups related papers into a “family”. OpenAI’s catalogue describes this one:

For every fixed d ≥ 3, any n ≥ 2 distinct points in ℝd determine at least \(c_dn^{2/d}\) distinct distances, with \(c_d\gt 0\) depending only on dimension. This matches the integer-grid order and resolves the higher-dimensional Erdős distinct-distances conjecture with a constant-factor bound.

The release has no Lean statement for this family, so there is no formal statement to compare with the result described above.

It bears on Erdős problem #1083, as listed by Thomas Bloom, erdosproblems.com.

The paper states

Theorem 1.1

In The higher-dimensional Erdős distinct-distances conjecture, 23 September 2026

Possible match to OpenAI’s description, selected from the papers’ main statements because it shares the most wording. No review confirming the selection is recorded.

For every integer d\ge3, there is a constant c_d>0 such that every finite set P\subset\mathbb R^d of n\ge2 distinct points satisfies

|\Delta(P)|\ge c_d n^{2/d}.
Reported proof verification
The release has no Lean statement for this family. The papers are available to read and assess.

Papers

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The higher-dimensional Erdős distinct-distances conjecture

23 September 2026, current edition.

Read it herePDF

For every fixed integer d ≥ 3, we prove that every set of n ≥ 2 distinct points in ℝd determines at least \(c_d n^{2/d}\) distinct distances, where \(c_d\gt 0\) depends only on d. This resolves the higher-dimensional Erdős distinct-distances conjecture positively.

Lean statements

The release has no Lean statement for this family. Its papers remain available to read, and contributors can propose a formal statement of a result. Suggest a change

Independent comparisons and proof-verification reports

Does the Lean express the advertised result?

The release contains no Lean statement for this family, so there is no formal statement to compare with OpenAI’s description.

What these papers cite in the release, and what cites them

These links come from the papers’ bibliographies. A citation records that one paper cites another; how each cited result is used has not been examined here.

Papers elsewhere in the release that this family’s papers cite

This family’s papers cite no paper elsewhere in the release.

Papers elsewhere in the release that cite this family’s papers

Follow-up work by others

  • The Justin Sun Prize, The Justin Sun Prize: problem bank and award records, 11 October 2026. Source

    JSP-000900 lists the release’s claim as Solved with independent mathematical review pending; Lean proof column: No.

  • Yao Xu, with AI assistance, cadamcat/distinct-distances-lean4: Lean 4 formalisation of the higher-dimensional Erdős distinct distances bound (JSP-000900), 10 October 2026. Source

    Independent Lean formalisation of the higher-dimensional distinct distances bound.

References outside the release

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Explain a result, compare statements or propose a correction

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What people have said

Commentary on this family by others, dated and credited. It is commentary, not a finding.

  • An unsigned public tier list, the OpenAI Math Tier List, classes it as a proof and rates its significance, if it holds up, as “Major math journal”. The page says that nothing on it is verified.

    Author not stated. Source

  • Thomas Bloom, Erdős problems in the OpenAI proofs, 8 October 2026. Source

    Bloom lists Erdős 1083 (distinct distances in higher dimensions), names Tidor, Yu and Zakharov, and says it is not formalised, heavily algebraic and 103 pages long.

  • mo271, ErdosProblems/1083: erdos_1083 is true (issue 6905), 7 October 2026. Source

    The release’s higher-dimensional distinct-distances manuscript gives at least c_d n^(2/d) distinct distances for d >= 3, which settles Erdős 1083.

Questions awaiting review

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Identify the theorem the catalogue describes

  • Family 166 The theorem shown was selected from shared wording with OpenAI’s description. Atlas records no review confirming that it is the theorem the description means. Open the form

State the result in Lean

  • Family 166 The release has no Lean statement for this family. Open the form