Plectis Atlas
Search

↑ and ↓ move, Enter opens, Esc closes.

Lean statement

Nodal counterexamples in dimensions three and four

Lean is a language for mathematical statements and proofs that a computer can verify. This page shows one statement file from OpenAI’s release, possible paper matches and independent reports. The code-like names below identify the definitions or theorems selected by the proof-verification settings.

Theorems selected for verification: OAI.YauCounterexamples.sphere_three OAI.YauCounterexamples.sphere_two_torus_two

Lean statement file: SmoothYau.leanShow on the mapFamily 350. OpenAI lists this as a main result in its Lean catalogue.

The Lean statement

The lines of the Lean statement that state the theorem, then the definitions in the file that it uses.

theorem sphere_three (gRound : SmoothMetric (Euclidean 3) (Sphere 3))    (hRound : IsRound gRound) :    ∀ N : Set (SmoothMetric (Euclidean 3) (Sphere 3)),      IsSmoothNeighborhood gRound N →      ∃ g ∈ N, HasUnboundedNodalRatio g 3 := by  sorrytheorem sphere_two_torus_two :    ∃ g : SmoothMetric FourModel FourManifold,      HasUnboundedNodalRatio g 4 := by  sorry

A Lean statement states the theorem and leaves its proof as sorry on purpose. OpenAI’s proof is in a separate solution module, and a program called Comparator checks that proof against this statement.

Definitions needed to read it

Local definitions the statement names, followed through the definitions they name in turn. The match is by name in the source text, so a name reached only through notation can be missed; the full file is below.

  • abbreviation OAI.YauCounterexamples.Euclidean line 12

    abbrev Euclidean (n : ℕ) := EuclideanSpace ℝ (Fin n)
  • abbreviation OAI.YauCounterexamples.Sphere line 13

    abbrev Sphere (n : ℕ) := Metric.sphere (0 : Euclidean (n + 1)) 1
  • abbreviation OAI.YauCounterexamples.FourManifold line 14

    abbrev FourManifold := Sphere 2 × (Circle × Circle)
  • abbreviation OAI.YauCounterexamples.FourModel line 15

    abbrev FourModel := Euclidean 2 × (Euclidean 1 × Euclidean 1)
  • abbreviation OAI.YauCounterexamples.SmoothMetric line 39

    abbrev SmoothMetric (E : Type*) [NormedAddCommGroup E] [NormedSpace ℝ E]    (M : Type*) [TopologicalSpace M] [ChartedSpace E M] [IsManifold 𝓘(ℝ, E) ∞ M] :=  ContMDiffRiemannianMetric 𝓘(ℝ, E) ∞ E (fun x : M => TangentSpace 𝓘(ℝ, E) x)
  • abbreviation OAI.YauCounterexamples.CoordIndex line 43

    abbrev CoordIndex (E : Type*) [NormedAddCommGroup E] [NormedSpace ℝ E]    [FiniteDimensional ℝ E] := Fin (Module.finrank ℝ E)
  • definition OAI.YauCounterexamples.coordinateVector line 47

    def coordinateVector (p : M) (y : E) (i : CoordIndex E) :    TangentSpace 𝓘(ℝ, E) ((chartAt E p).symm y) :=  mfderiv 𝓘(ℝ, E) 𝓘(ℝ, E) (chartAt E p).symm y (Module.finBasis ℝ E i)
  • definition OAI.YauCounterexamples.metricCoefficients line 52

    def metricCoefficients (g : SmoothMetric E M) (p : M) (y : E) :    Matrix (CoordIndex E) (CoordIndex E) ℝ :=  fun i j => g.inner ((chartAt E p).symm y)    (coordinateVector p y i) (coordinateVector p y j)
  • definition OAI.YauCounterexamples.laplaceBeltrami line 60

    def laplaceBeltrami (g : SmoothMetric E M) (u : M → ℝ) (x : M) : ℝ :=  let c := chartAt E x  let a := metricCoefficients g x  let density := fun y => Real.sqrt (Matrix.det (a y))  let u' := u ∘ c.symm  (density (c x))⁻¹ * ∑ i, fderiv ℝ    (fun y => density y * ∑ j, (a y)⁻¹ i j *      fderiv ℝ u' y (Module.finBasis ℝ E j))    (c x) (Module.finBasis ℝ E i)
  • structure OAI.YauCounterexamples.CoordinateTest line 71

    structure CoordinateTest (E : Type*) [NormedAddCommGroup E] [NormedSpace ℝ E]    [FiniteDimensional ℝ E] (M : Type*) [TopologicalSpace M] [ChartedSpace E M] where  center : M  compactSet : Set E  isCompact : IsCompact compactSet  inTarget : compactSet ⊆ (chartAt E center).target  order : ℕ  row : CoordIndex E  column : CoordIndex E
  • definition OAI.YauCounterexamples.IsSmoothNeighborhood line 83

    def IsSmoothNeighborhood (g₀ : SmoothMetric E M) (N : Set (SmoothMetric E M)) : Prop :=  ∃ tests : List (CoordinateTest E M), ∃ ε : ℝ, 0 < ε ∧    ∀ g : SmoothMetric E M,      (∀ t ∈ tests, ∀ y ∈ t.compactSet,        ‖iteratedFDeriv ℝ t.order          (fun z => metricCoefficients g t.center z t.row t.column -            metricCoefficients g₀ t.center z t.row t.column) y‖ < ε) → g ∈ N
  • definition OAI.YauCounterexamples.nodalMeasure line 93

    def nodalMeasure [T3Space M] (g : SmoothMetric E M) (d : ℝ) (u : M → ℝ) : ℝ≥0∞ :=  letI : RiemannianBundle (fun x : M => TangentSpace 𝓘(ℝ, E) x) :=    ⟨g.toRiemannianMetric⟩  letI : IsContinuousRiemannianBundle E (fun x : M => TangentSpace 𝓘(ℝ, E) x) :=    ⟨⟨g.inner, g.contMDiff.continuous, fun _ _ _ => rfl⟩⟩  letI : EMetricSpace M := EMetricSpace.ofRiemannianMetric 𝓘(ℝ, E) M  letI : MeasurableSpace M := borel M  letI : BorelSpace M := ⟨rfl⟩  Measure.hausdorffMeasure d {x | u x = 0}
  • definition OAI.YauCounterexamples.HasUnboundedNodalRatio line 104

    def HasUnboundedNodalRatio [T3Space M] (g : SmoothMetric E M) (d : ℕ) : Prop :=  ∃ (u : ℕ → M → ℝ) (eigenvalue : ℕ → ℝ),    (∀ j, ContMDiff 𝓘(ℝ, E) 𝓘(ℝ, ℝ) ∞ (u j) ∧ u j ≠ 0 ∧ 0 < eigenvalue j ∧      (∀ x, -laplaceBeltrami g (u j) x = eigenvalue j * u j x) ∧      nodalMeasure g (d - 1 : ℕ) (u j) ≠ (∞ : ℝ≥0∞)) ∧    Tendsto eigenvalue atTop atTop ∧    Tendsto (fun j => (nodalMeasure g (d - 1 : ℕ) (u j)).toReal / Real.sqrt (eigenvalue j))      atTop atTop
  • definition OAI.YauCounterexamples.IsRound line 117

    def IsRound (g : SmoothMetric (Euclidean 3) (Sphere 3)) : Prop :=  ∀ (x : Sphere 3) (v w : TangentSpace 𝓘(ℝ, Euclidean 3) x),    g.inner x v w = inner ℝ      (mfderiv 𝓘(ℝ, Euclidean 3) 𝓘(ℝ, Euclidean 4)        (fun y : Sphere 3 => (y : Euclidean 4)) x v)      (mfderiv 𝓘(ℝ, Euclidean 3) 𝓘(ℝ, Euclidean 4)        (fun y : Sphere 3 => (y : Euclidean 4)) x w)

No confident match with a paper statement

No paper theorem is paired with this Lean statement.

Why none: no paper statement matches the Lean text clearly enough to pair, so the closest candidates are listed below.

Statements in Smooth counterexamples to Yau’s nodal upper bound in dimensions three and four come first because the release’s name for this Lean statement shares words with that paper’s title.

Other possible paper matches, closest wording first

  • Theorem 1.1 of Smooth counterexamples to Yau’s nodal upper bound in dimensions three and four. Words of the Lean statement, its names split into words, that also appear in the theorem: topology, round, sqrt, riemannian, neighborhood, positive and three more. Found in the paper’s title, which its main theorem states: three, four and nodal. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: contains and lambda.
  • Proposition 2.6 of Smooth counterexamples to Yau’s nodal upper bound in dimensions three and four. Words of the Lean statement, its names split into words, that also appear in the theorem: two, ambient, points, exactly, distance, coordinate and seven more.
  • Theorem 1.1 of Sharp nodal length on smooth surfaces. Words of the Lean statement, its names split into words, that also appear in the theorem: laplace, hausdorff, distance, measure, sqrt, riemannian and three more. Found in the paper’s title, which its main theorem states: nodal and smooth. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: eigenfunction and lambda.
  • Proposition 4.4 of Smooth counterexamples to Yau’s nodal upper bound in dimensions three and four. Words of the Lean statement, its names split into words, that also appear in the theorem: unit, exactly, continuous, round, 1/2, riemannian and six more. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: upper, property and lambda.
  • Proposition 2.2 of Smooth counterexamples to Yau’s nodal upper bound in dimensions three and four. Words of the Lean statement, its names split into words, that also appear in the theorem: three, manifold, dimensional, compact, coordinate, one and five more.

How Atlas selects possible matches: it compares words in the Lean statement with every statement in the family. It also splits Lean names into words. The release’s label and note receive less weight; a main theorem wins a close match. If the Lean wording yields no clear match, Atlas uses the catalogue description. This selects passages to compare; it does not establish that they mean the same thing.

Reported Comparator runs

two independent groups report that Comparator accepted runs for this Lean statement file: Carlos Toledo’s cert-machine; MathVet. Each group reports its own Comparator run for this statement file. Atlas has not repeated the runs.

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

Carlos Toledo’s cert-machine

How they ran it, in their words

Every Comparator challenge re-run on Linux with nanoda switched on, decided by a preregistered rule; every family’s challenge statements read against OpenAI’s headline, clause by clause. Decider: Comparator (leanprover/comparator d03acab1 = tag v4.34.0, built with the release’s toolchain v4.34.1), lean4export 076e8e57, landrun 811cfff5, nanoda_lib 3a240721 — on GitHub’s Linux runners (.github/workflows/openai-math-kernel.yml), one j…

  • Accepted Their term: “CERTIFIED”.

    Re-run through Comparator with the independent nanoda kernel switched on: Lean’s kernel and nanoda both accept OpenAI’s solution.

    Reported 10 October 2026, at the release version shown here. Original verification report

MathVet

How they ran it, in their words

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. Its protocol describes a planned error-rate study; this import does not establish that the study has been completed.

  • Accepted Their term: “comparator-sandboxed-pass”.

    Re-run through Comparator in a sandboxed virtual machine: accepted.

    Reported 8 October 2026, at the release version shown here. Original verification report

What an accepted Comparator run would establish

If Comparator is run under this configuration and accepts, the solution proves the configured theorem using only the allowed axioms, and the Lean kernel accepts every step.

This configuration lists no definition holes, so every definition the statement uses is compared as it is written in this file.

Allowed axioms: propext, Quot.sound, Classical.choice

Acceptance leaves open whether the Lean statement means the same thing as the paper’s theorem, whether the paper’s other claims are correct, and whether the result is new. Those questions require comparing the definitions and statements, reviewing the paper’s arguments, and reading the earlier literature.

Do family 350’s Lean statements express the advertised result?

These assessments compare all the family’s Lean statements with the whole result OpenAI describes in its catalogue. They do not assess this statement alone. Each group uses its own published rules.

Neither group finds that the Lean statements express or imply the whole advertised result. They describe what the statements express in different terms.

  • MathVet

    Finds part of it stated, or a narrower or weaker statement Their term: “partial”.

    Only a special case is stated, or a co-equal headline claim has no challenge statement. Their record

    Their note: NodalLength.Main is the headline: on every compact connected smooth Riemannian surface there is C with H¹(nodal set) ≤ C√λ for every nonzero smooth eigenfunction with -Δu = λu, λ > 0; sphere_three (every C^∞ neighbourhood of the round S³ metric contains a metric with unbounded nodal ratio) and sphere_two_torus_two give dimensions 3 and 4. For dimension five, YauCounterexample (S⁴×S¹) only gives H⁴(nodal)/√λ → ∞, not the summary's power-law growth λ^(1/2+ε₀), so that claim is only stated in a weaker form.

    Definitions the group asks readers to compare with the paper: Laplace-Beltrami and nodal measures are hand-written: laplaceBeltrami (det(g)^(-1/2) ∂_i(det(g)^(1/2) g^{ij} ∂_j u) in the centre chart of each point), nodalMeasure = d-dimensional Hausdorff measure for EMetricSpace.ofRiemannianMetric; NodalLength uses a MetricSpace M instance tied to the Riemannian structure only through [IsRiemannianManifold] ; IsSmoothNeighborhood g₀ N (finitely many compact-chart C^k seminorm tests with one ε) as the C^∞ topology on metrics; IsRound as the pullback of the Euclidean inner product

  • Carlos Toledo’s cert-machine

    Finds part of it stated, or a narrower or weaker statement Their term: “NARROWER — UNDECLARED”.

    The challenge statements state less than the headline, and OpenAI’s Lean note does not say so. Their record

    Their note: The dimension-five power-law violation (nodal measure ≥ λ^{1/2+ε₀} along a sequence, for a fixed ε₀ > 0) is not stated; only nodal/√λ → ∞ is.

Read the complete assessments on the family page.

OpenAI’s own note on what this Lean statement covers

“The formalized results contradict Yau's proposed $O(\sqrt\lambda)$ upper bound for nodal measure in dimensions three and four. On $S^3$, every prescribed smooth neighborhood of the round metric contains one fixed smooth metric with an eigenfunction sequence of unbounded nodal-measure ratio. A second fixed metric on $S^2\times T^2$ has the same property. In both cases the eigenvalues tend to infinity and the intrinsic nodal measures are finite.”

An AI agent drafted an interpretation of that note, classifying this statement as “states a paper’s theorem as the paper does”. No human review of the draft is recorded.

Supporting material

The complete Lean statement file

149 lines, copied from release version fd4aeeb. A name defined in this file links to its line; pointing at the name shows its definition.

Declared in this fileOpenAI’s library at fd4aeebOther linked names open the current documentation for Mathlib, Lean’s mathematical library.

Links in the file: 71 to its own declarations, 97 to Mathlib’s documentation. 20 declared names also link to the same declaration in OpenAI’s library. OpenAI uses Mathlib version d13f23b. The linked documentation describes the current version, so names that have since changed may be missing there.

import Mathlibnamespace OAInoncomputable sectionnamespace YauCounterexamplessectionopen Set Filter Manifold Bundle MeasureTheoryopen scoped Topology ContDiff ENNRealabbrev Euclidean (n : ℕ) := EuclideanSpace ℝ (Fin n)abbrev Sphere (n : ℕ) := Metric.sphere (0 : Euclidean (n + 1)) 1abbrev FourManifold := Sphere 2 × (Circle × Circle)abbrev FourModel := Euclidean 2 × (Euclidean 1 × Euclidean 1)instance torusChartedSpace : ChartedSpace (Euclidean 1 × Euclidean 1) (Circle × Circle) :=  prodChartedSpace (Euclidean 1) Circle (Euclidean 1) Circleinstance torusIsManifold : IsManifold 𝓘(ℝ, Euclidean 1 × Euclidean 1) ∞ (Circle × Circle) := by  rw [modelWithCornersSelf_prod]  exact IsManifold.prod Circle Circleinstance fourChartedSpace : ChartedSpace FourModel FourManifold :=  prodChartedSpace (Euclidean 2) (Sphere 2) (Euclidean 1 × Euclidean 1) (Circle × Circle)instance fourIsManifold : IsManifold 𝓘(ℝ, FourModel) ∞ FourManifold := by  rw [show 𝓘(ℝ, FourModel) = 𝓘(ℝ, Euclidean 2).prod    𝓘(ℝ, Euclidean 1 × Euclidean 1) from modelWithCornersSelf_prod]  exact IsManifold.prod (Sphere 2) (Circle × Circle)section Definitionsvariable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]  [FiniteDimensional ℝ E]variable {M : Type*} [TopologicalSpace M] [ChartedSpace E M]  [IsManifold 𝓘(ℝ, E) ∞ M]/-- Ordinary smooth positive-definite Riemannian metrics, with the existing tangent topology. -/abbrev SmoothMetric (E : Type*) [NormedAddCommGroup E] [NormedSpace ℝ E]    (M : Type*) [TopologicalSpace M] [ChartedSpace E M] [IsManifold 𝓘(ℝ, E) ∞ M] :=  ContMDiffRiemannianMetric 𝓘(ℝ, E) ∞ E (fun x : M => TangentSpace 𝓘(ℝ, E) x)abbrev CoordIndex (E : Type*) [NormedAddCommGroup E] [NormedSpace ℝ E]    [FiniteDimensional ℝ E] := Fin (Module.finrank ℝ E)/-- A coordinate vector, pushed from a chart back into the tangent bundle. -/def coordinateVector (p : M) (y : E) (i : CoordIndex E) :    TangentSpace 𝓘(ℝ, E) ((chartAt E p).symm y) :=  mfderiv 𝓘(ℝ, E) 𝓘(ℝ, E) (chartAt E p).symm y (Module.finBasis ℝ E i)/-- Metric coefficients in a chart. Only values in the chart target are used. -/def metricCoefficients (g : SmoothMetric E M) (p : M) (y : E) :    Matrix (CoordIndex E) (CoordIndex E) ℝ :=  fun i j => g.inner ((chartAt E p).symm y)    (coordinateVector p y i) (coordinateVector p y j)/-- The local coordinate formula det(g)^(-1/2) d_i(det(g)^(1/2) g^{ij} d_j u).The chart at the evaluation point is used, so all derivatives are taken inits open target. -/def laplaceBeltrami (g : SmoothMetric E M) (u : M → ℝ) (x : M) : ℝ :=  let c := chartAt E x  let a := metricCoefficients g x  let density := fun y => Real.sqrt (Matrix.det (a y))  let u' := u ∘ c.symm  (density (c x))⁻¹ * ∑ i, fderiv ℝ    (fun y => density y * ∑ j, (a y)⁻¹ i j *      fderiv ℝ u' y (Module.finBasis ℝ E j))    (c x) (Module.finBasis ℝ E i)/-- One compact-chart seminorm test for the usual smooth topology of metrics. -/structure CoordinateTest (E : Type*) [NormedAddCommGroup E] [NormedSpace ℝ E]    [FiniteDimensional ℝ E] (M : Type*) [TopologicalSpace M] [ChartedSpace E M] where  center : M  compactSet : Set E  isCompact : IsCompact compactSet  inTarget : compactSet ⊆ (chartAt E center).target  order : ℕ  row : CoordIndex E  column : CoordIndex E/-- The finite compact-chart derivative tests defining a C∞ neighborhood.A single positive tolerance suffices for the finitely many tests. -/def IsSmoothNeighborhood (g₀ : SmoothMetric E M) (N : Set (SmoothMetric E M)) : Prop :=  ∃ tests : List (CoordinateTest E M), ∃ ε : ℝ, 0 < ε ∧    ∀ g : SmoothMetric E M,      (∀ t ∈ tests, ∀ y ∈ t.compactSet,        ‖iteratedFDeriv ℝ t.order          (fun z => metricCoefficients g t.center z t.row t.column -            metricCoefficients g₀ t.center z t.row t.column) y‖ < ε) → g ∈ N/-- Hausdorff measure for the path distance of the actual Riemannian metric,not the metric inherited from any ambient embedding. -/def nodalMeasure [T3Space M] (g : SmoothMetric E M) (d : ℝ) (u : M → ℝ) : ℝ≥0∞ :=  letI : RiemannianBundle (fun x : M => TangentSpace 𝓘(ℝ, E) x) :=    ⟨g.toRiemannianMetric⟩  letI : IsContinuousRiemannianBundle E (fun x : M => TangentSpace 𝓘(ℝ, E) x) :=    ⟨⟨g.inner, g.contMDiff.continuous, fun _ _ _ => rfl⟩⟩  letI : EMetricSpace M := EMetricSpace.ofRiemannianMetric 𝓘(ℝ, E) M  letI : MeasurableSpace M := borel M  letI : BorelSpace M := ⟨rfl⟩  Measure.hausdorffMeasure d {x | u x = 0}/-- The eigensequence belongs to one fixed metric and has finite nodal measure. -/def HasUnboundedNodalRatio [T3Space M] (g : SmoothMetric E M) (d : ℕ) : Prop :=  ∃ (u : ℕ → M → ℝ) (eigenvalue : ℕ → ℝ),    (∀ j, ContMDiff 𝓘(ℝ, E) 𝓘(ℝ, ℝ) ∞ (u j) ∧ u j ≠ 0 ∧ 0 < eigenvalue j ∧      (∀ x, -laplaceBeltrami g (u j) x = eigenvalue j * u j x) ∧      nodalMeasure g (d - 1 : ℕ) (u j) ≠ (∞ : ℝ≥0∞)) ∧    Tendsto eigenvalue atTop atTop ∧    Tendsto (fun j => (nodalMeasure g (d - 1 : ℕ) (u j)).toReal / Real.sqrt (eigenvalue j))      atTop atTopend Definitions/-- The round metric is the pullback of the Euclidean scalar product underinclusion of the unit sphere. This predicate specifies exactly that tensor. -/def IsRound (g : SmoothMetric (Euclidean 3) (Sphere 3)) : Prop :=  ∀ (x : Sphere 3) (v w : TangentSpace 𝓘(ℝ, Euclidean 3) x),    g.inner x v w = inner ℝ      (mfderiv 𝓘(ℝ, Euclidean 3) 𝓘(ℝ, Euclidean 4)        (fun y : Sphere 3 => (y : Euclidean 4)) x v)      (mfderiv 𝓘(ℝ, Euclidean 3) 𝓘(ℝ, Euclidean 4)        (fun y : Sphere 3 => (y : Euclidean 4)) x w)endopen Set Filter Manifold Bundle MeasureTheoryopen scoped Topology ContDiff ENNRealtheorem sphere_three (gRound : SmoothMetric (Euclidean 3) (Sphere 3))    (hRound : IsRound gRound) :    ∀ N : Set (SmoothMetric (Euclidean 3) (Sphere 3)),      IsSmoothNeighborhood gRound N →      ∃ g ∈ N, HasUnboundedNodalRatio g 3 := by  sorrytheorem sphere_two_torus_two :    ∃ g : SmoothMetric FourModel FourManifold,      HasUnboundedNodalRatio g 4 := by  sorryend YauCounterexamplesendend OAI
Every extracted statement of the accompanying papers

The statements the atlas extracted automatically from each accompanying paper’s TeX source, with links to the full sources.

Sharp nodal length on smooth surfaces

Theorem

Let (M,g) be a closed connected C^\infty Riemannian surface. There is a finite constant C=C(M,g) such that every nonzero real Laplace eigenfunction satisfying

-\Delta_g u=\lambda u,\qquad \lambda>0,

obeys

\mathcal H_g^1(Z_u)\le C\sqrt\lambda.

Here \mathcal H_g^1 is Hausdorff measure for the Riemannian distance. The same constant applies to every eigenfunction in every positive eigenspace.

Section 1, Introduction and main result Read it in the paper TeX source, line 7
Show the TeX
Let $(M,g)$ be a closed connected $C^\infty$ Riemannian surface.
There is a finite constant $C=C(M,g)$ such that every nonzero real
Laplace eigenfunction satisfying
\[
 -\Delta_g u=\lambda u,\qquad \lambda>0,
\]
obeys
\[
 \mathcal H_g^1(Z_u)\le C\sqrt\lambda.
\]
Here $\mathcal H_g^1$ is Hausdorff measure for the Riemannian distance.
The same constant applies to every eigenfunction in every positive
eigenspace.

Smooth counterexamples to Yau’s nodal upper bound in dimensions three and four

Theorem

Let g_* be the round metric on \Sph^3. Every neighborhood of g_* in the C^\infty topology contains a smooth Riemannian metric g_\infty for which there are nonzero smooth real functions u_j and positive numbers \lambda_j satisfying

-\Delta_{g_\infty}u_j=\lambda_j u_j,\qquad \lambda_j\longrightarrow\infty,\qquad \frac{\HH^2_{g_\infty}(Z_{u_j})}{\sqrt{\lambda_j}} \longrightarrow\infty.
Section 1, Introduction Read it in the paper TeX source, line 18
Show the TeX
Let $g_*$ be the round metric on $\Sph^3$. Every neighborhood of $g_*$ in
the $C^\infty$ topology contains a smooth Riemannian metric $g_\infty$ for
which there are nonzero smooth real functions $u_j$ and positive numbers
$\lambda_j$ satisfying
\[
 -\Delta_{g_\infty}u_j=\lambda_j u_j,\qquad
 \lambda_j\longrightarrow\infty,\qquad
 \frac{\HH^2_{g_\infty}(Z_{u_j})}{\sqrt{\lambda_j}}
       \longrightarrow\infty.
\]
Theorem

There are a smooth Riemannian metric g_\infty on S^2\times\T^2, nonzero smooth real functions u_j, and positive numbers \lambda_j\to\infty such that

-\Delta_{g_\infty}u_j=\lambda_j u_j,\qquad \frac{\cH^3_{g_\infty}(Z_{u_j})}{\sqrt{\lambda_j}} \longrightarrow\infty.
Section 1, Introduction Read it in the paper TeX source, line 31
Show the TeX
There are a smooth Riemannian metric $g_\infty$ on $S^2\times\T^2$,
nonzero smooth real functions $u_j$, and positive numbers
$\lambda_j\to\infty$ such that
\[
 -\Delta_{g_\infty}u_j=\lambda_j u_j,\qquad
 \frac{\cH^3_{g_\infty}(Z_{u_j})}{\sqrt{\lambda_j}}
       \longrightarrow\infty.
\]

Power-law violations of Yau’s nodal upper bound

Theorem

There exist a smooth Riemannian metric g on S^4\times S^1, a number \epsilon_0>0, and nonzero real smooth functions u_j with positive eigenvalues \lambda_j such that

-\Delta_g u_j=\lambda_j u_j,\qquad \lambda_j\longrightarrow\infty,\qquad \frac{\Hh_g^4(\Z(u_j))} {\lambda_j^{1/2+\epsilon_0}}\longrightarrow\infty.

The metric and \epsilon_0 are fixed throughout the sequence.

Section 1, Introduction Read it in the paper TeX source, line 28
Show the TeX
There exist a smooth Riemannian metric $g$ on $S^4\times S^1$, a number
$\epsilon_0>0$, and nonzero real smooth functions $u_j$ with positive
eigenvalues $\lambda_j$ such that
\[
 -\Delta_g u_j=\lambda_j u_j,\qquad
 \lambda_j\longrightarrow\infty,\qquad
 \frac{\Hh_g^4(\Z(u_j))}
      {\lambda_j^{1/2+\epsilon_0}}\longrightarrow\infty.
\]
The metric and $\epsilon_0$ are fixed throughout the sequence.
Configuration and file facts
OpenAI’s Lean catalogue
OpenAI lists this as a main result in its Lean catalogue.
Allowed axioms
propext, Quot.sound, Classical.choiceThe axioms this configuration allows a proof to use. A replay shows which of them a proof uses.
Imports
Mathlib
Imports from outside Mathlib
None
Local vocabulary
18 local vocabulary declarations
Lines of Lean, without comments or blank lines
88
Second proof-verification program (nanoda)
Off in OpenAI's configuration.

Statement comparison

A shareable summary of this page: the proposed paper match, what the Lean statement expresses, and which reviews are recorded.

Plectis Atlas

Nodal counterexamples in dimensions three and four

Family 350: Yau’s nodal bounds: surfaces and higher dimensions

No paper statement selected

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

The Lean statement says

theorem sphere_three (gRound : SmoothMetric (Euclidean 3) (Sphere 3))    (hRound : IsRound gRound) :    ∀ N : Set (SmoothMetric (Euclidean 3) (Sphere 3)),      IsSmoothNeighborhood gRound N →      ∃ g ∈ N, HasUnboundedNodalRatio g 3 := by  sorrytheorem sphere_two_torus_two :    ∃ g : SmoothMetric FourModel FourManifold,      HasUnboundedNodalRatio g 4 := by  sorry

A Lean statement states the theorem and leaves its proof as sorry on purpose. OpenAI’s proof is in a separate solution module, and a program called Comparator checks that proof against this statement.

No paper theorem is paired with this Lean statement.two independent groups report that Comparator accepted runs for this file at the release version shown here.Statement review: none recorded

18 local vocabulary declarationsAllowed axioms: propext, Quot.sound, Classical.choiceopenai/math at fd4aeebwcook04.github.io/plectis-atlas/statements/SmoothYau.html

Recorded comparisons with the paper

Atlas records no contributed comparison of this statement with the paper.

Contributed Comparator run reports

Atlas records no contributed report of running Comparator for this statement file.

Questions to resolve when comparing this statement with the paper

  • Both independent readers find this family's challenges state less than its headline, while the atlas's AI draft classes this file as stating a paper's theorem as the paper does; check which part of the headline it covers.

Compare this statement with the paperShare a Comparator run reportSuggest a change