OpenAI reports a power improvement for Heilbronn triangles

There are fixed constants η,c>0 such that, for every sufficiently large n, n points can be placed in the unit square with every triangle of area at least c n^{-2+η}.

Sources for this record

What was already known

The previous lower-bound improvement was logarithmic over n^{-2}, and the nearly n^{-2} upper-bound formulation remained open.

AI involvement AI-led

OpenAI credits itself as manuscript author and states that its internal frontier model produced the results in this release. Individual human input is not detailed enough to establish task-only autonomy.

OpenAI is named as author on the manuscript, and its release attributes the results to an internal frontier model. The individual human input is not detailed enough to establish autonomy.

Importance Major

Disproves the nearly n^{-2} upper-bound formulation of Heilbronn’s triangle problem.

Limitations

The linked Lean scope proves a power improvement only along an unbounded sequence of sizes n, not the manuscript’s every-sufficiently-large-n assertion. That narrower result already refutes the proposed almost-n^{-2} upper bound.

Technical verification Partial

OpenAI reports a Lean check of a narrower theorem, case, or component; the selected claim extends beyond that scope.

Formal checking

The pinned OpenAI Lean scope note verifies only this narrower statement, not the full selected claim.

Checker
OpenAI-reported Lean 4 / Comparator
Scope
There is an unbounded sequence of n with point sets in the unit square whose smallest triangle area is at least n^{-2+η} for one fixed η>0.
Basis
Reported by the linked checker
Evidence source

Checking a formal statement does not establish that it matches the original problem.

Human understanding Few

Few is the default when evidence for a higher level is insufficient. No named person is documented as explaining the central argument for this assessed contribution.

Correction and publication history

2026-10-18 · publication

Primary manuscript, attribution, prior-work, and precise partial or mismatched Lean-scope review for non-notifying local inclusion.

Read this published revision