The higher-dimensional Erdős distinct-distances conjecture
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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.
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
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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
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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
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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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.
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 166The 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 166The release has no Lean statement for this family.Open the form
Why this passage is shown
Theorem 1.1
In The higher-dimensional Erdős distinct-distances conjecture, 23 September 2026
How it was found
Its words were compared with the words of OpenAI’s catalogue description.
Words they share
constant, distinct, integer, points
Review
Atlas records no review confirming that this is the theorem OpenAI’s description refers to.