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The hot spots conjecture for simply connected planar domains

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

Proves a strict form of Burdzy’s simply connected hot spots conjecture. On every smooth bounded simply connected planar domain, each nonzero eigenfunction for the first positive Neumann eigenvalue has no interior critical point, so all global extrema lie on the boundary. Eigenvalue multiplicity is allowed. (OpenAI’s Lean note)

Lean is a language for mathematical statements and proofs that a computer can verify. The assessments below ask whether those statements express the result OpenAI describes here.

Both independent assessments find that the Lean statements express or imply the whole result described above. Read the assessments

What the papers state

The paper states

Theorem 1.1

In Strict hot spots and absence of interior critical points on smooth simply connected planar domains, 24 September 2026

Possible match to OpenAI’s description, selected from shared wording. No review confirming the selection is recorded.

For every 0\ne u\in\V,

\grad u(x)\ne0\qquad(x\in\Omega).

In particular,

\min_{y\in\partial\Omega}u(y)<u(x)<\max_{y\in\partial\Omega}u(y) \qquad(x\in\Omega).

No Lean statement in the release is paired with this theorem.

The release does not say which paper theorem its catalogue describes. The statement above shares the most wording with the description; the atlas has not reviewed that choice. Identifying it is listed under Questions awaiting review.

Reported proof verification
One Lean statement in the release; three independent groups report that Comparator accepted runs for this file at the version shown here.

Papers

Each paper opens as a reading page in the browser, with the PDF beside it. The statements each paper opens with are on its reading page.

One Lean statement in this family

Lean is a language for mathematical statements and proofs that a computer can verify. The Lean statement below is shown beside its possible paper counterpart, with the reason they were linked.

For a configured theorem, the Comparator program tests whether OpenAI’s separate proof proves the exact Lean statement using only the allowed axioms. Some statement files instead configure definitions for comparison by name and type. Acceptance does not establish that a formal statement means the same thing as the paper’s theorem.

HotSpots

The paper states

No paper theorem is paired with this Lean statement.

no paper statement matches the Lean text clearly enough to pair, so the closest candidates are listed below.

Statements it shares words with:

  • Proposition 2.5 in Strict hot spots and absence of interior critical points on smooth simply connected planar domains, 24 September 2026.
  • Theorem 1.1 in Strict hot spots and absence of interior critical points on smooth simply connected planar domains, 24 September 2026.
  • Proposition 4.4 (Multiplier identity) in Strict hot spots and absence of interior critical points on smooth simply connected planar domains, 24 September 2026.
  • Proposition 5.5 in Strict hot spots and absence of interior critical points on smooth simply connected planar domains, 24 September 2026.
  • Proposition 3.1 in Strict hot spots and absence of interior critical points on smooth simply connected planar domains, 24 September 2026.
  • Theorem 5.1 in Strict hot spots and absence of interior critical points on smooth simply connected planar domains, 24 September 2026.

The Lean statement

No paper theorem is paired with it.

Strict hot spots and absence of interior critical points

HotSpots.lean, the release lists it as a supporting statement.

theorem main_theorem (Ω : Set Plane) (hΩ : AdmissibleDomain Ω)    (u : Plane → ℝ) (hu : InFirstNeumannEigenspace Ω u)    (hne : ∃ x ∈ Ω, u x ≠ 0) : MainConclusion Ω u := by  sorry

This file states the theorem with sorry, a placeholder, in place of its proof. OpenAI supplies a separate proof file. Comparator tests whether that proof proves the statement here.

three independent groups report that Comparator accepted runs for this Lean statement file: cert-machine; MathVet; Neal McBurnett, openai-math-lean-tooling. Who ran the proof-verification program

  • cert-machine records it as “CERTIFIED”.
  • MathVet records it as “comparator-sandboxed-pass”.
  • Neal McBurnett, openai-math-lean-tooling records it as “accepted”.

Read the complete Lean statement

Independent comparisons and proof-verification reports

Does the Lean express the advertised result?

MathVet and cert-machine agree on how much of the advertised result the Lean statements express.

MathVet and Carlos Toledo’s cert-machine independently assessed whether this family’s Lean statements express the whole result OpenAI describes in its catalogue. These are assessments of the family as a whole, not of each paper theorem separately.

MathVet finds that the Lean statements express or imply the whole advertised result (their term: “full”).

Their note: main_theorem: on every nonempty bounded open simply connected planar domain with smooth boundary, every nonzero u in the first positive Neumann eigenspace (smooth up to the boundary, mean zero, weak eigen-equation against all H¹ test pairs with eigenvalue = inf of the mean-zero Rayleigh quotient) has ∇u ≠ 0 at every interior point and inf_∂Ω u < u(x) < sup_∂Ω u inside, i.e. no interior critical point and strict hot spots; eigenvalue multiplicity is allowed because the statement is for any element of the eigenspace.

Definitions the group asks readers to compare with the paper: firstPositiveNeumannValue Ω := sInf (rayleighValues Ω) with hand-built HasH1Gradient and SmoothBoundary (local defining functions ρ with nonzero gradient); InFirstNeumannEigenspace requires ContDiffOn ℝ ∞ u (closure Ω)

“full”, in their words: The challenge statements imply the headline claim after unpacking definitions or one routine step.

Their method: An independent, model-assisted, pre-referee reading of each family’s challenge statements against its headline claim under a published rubric (PROTOCOL.md), with its own Comparator runs per challenge.

cert-machine finds that the Lean statements express or imply the whole advertised result (their term: “MATCHES”).

“MATCHES”, in their words: The challenge statements state the headline as OpenAI wrote it.

Their method: Every Comparator challenge re-run on Linux with nanoda switched on, decided by a preregistered rule.

OpenAI’s own note on what its Lean covers

The strict hot-spots conjecture asks whether extrema of a first nonconstant Neumann eigenfunction occur only on the boundary. The formalization proves the stronger interior statement on every nonempty smooth bounded simply connected planar domain: every nonzero eigenfunction in the first positive Neumann eigenspace has nonvanishing gradient throughout the interior. Consequently all global maxima and minima lie on the boundary. The conclusion applies to every eigenfunction even when the eigenvalue is multiple.

AI-drafted comparisons, with no recorded human review

  • Strict hot spots and absence of interior critical points HotSpots

    Unreviewed AI draft: states a paper’s theorem as the paper does. States the main theorem: first nonconstant Neumann eigenfunctions on smooth bounded simply connected planar domains have no interior critical points, so their extrema lie on the boundary.

Who ran the proof-verification program?

These groups report running Comparator with the release’s Lean statement files. For a configured theorem, it verifies OpenAI’s separate proof against the exact statement; some files instead configure definitions for comparison by name and type. Each row is the named group’s report. Atlas has not repeated the runs.

These reports do not list the software versions, proof-verification programs, axioms, time or memory in separate fields. Any such details in a report’s prose are reproduced below.

Strict hot spots and absence of interior critical points HotSpots

Three reports, all at the release’s recorded version.

Reported byTheir wordTheir accountDateOriginal report
cert-machine“CERTIFIED”Re-run through Comparator with the independent nanoda kernel switched on: Lean’s kernel and nanoda both accept OpenAI’s solution.10 October 2026Original report
MathVet“comparator-sandboxed-pass”Re-run through Comparator in a sandboxed virtual machine: accepted.8 October 2026Original report
Neal McBurnett, openai-math-lean-tooling“accepted”Re-run through Comparator with Lean’s kernel: accepted (the check took 416 s; peak memory 6.9 GiB).11 October 2026Original report

Other proofs and exact calculations

These reports examine claims in the papers using HOL Light, a different proof assistant, independently of the release’s Lean proofs. Read each report for the exact claim it covers.

  • The J₁ power series has derivative J₀ − J₁/x on (1, 2), and that derivative vanishes somewhere in (1.8411, 1.8412)

    HOL Light card 369

    Reported by
    Ben Knill, openai-math-hol-cards
    Method
    Proof of a selected step in HOL Light
    Their verdict
    “PASS” The report records a proof of a supporting fact.
    What it covers
    Illustration; not that this is the first zero, nor that the series are “the” Bessel functions
    Original report
    Their report

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

No paper elsewhere in the release cites this family’s papers.

Follow-up work by others

  • Jizhou Guo, Follow-ups to the OpenAI mathematics release (papers, sources and Lean ancillary files), 10 October 2026. Source

    First Neumann eigenfunctions of convex planar domains attain extrema on the boundary, deduced from the release’s smooth-domain hot spots paper (10 October).

References outside the release

Each paper’s outside references are listed with it on its reading page, where each citation is placed. Every outside work cited in the release: References outside the release

Explain a result, compare statements or propose a correction

Atlas has no contributed explanation for this family yet. You can offer one with a GitHub account. You receive named credit and disclose any AI assistance.

Each button opens a GitHub form with this page and its source version filled in. Opening the form does not reserve the work.

Offer to write an explanationCompare the Lean statement with the paperSuggest a source attributionSuggest a change

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 “Career-defining publication”. The page says that nothing on it is verified.

    Author not stated. Source

Questions awaiting review

Each item identifies a statement, definition or report that needs further review. Its link opens a GitHub form with the source version already recorded.

Read the Lean statement against the paper

  • An AI agent drafted an assessment of which part of the paper this Lean statement expresses. No named human review is recorded. Open the form

Identify the theorem the catalogue describes

  • Family 369 No single paper statement clearly matches OpenAI’s description by wording, and no review identifying the intended theorem is recorded. Open the form

Address a question raised in an independent assessment

Compare the proposed paper and Lean matches

  • Family 369 Atlas records no review of whether each linked Lean statement and paper theorem mean the same thing. Open the form