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Lean statement

Weighted Schatten moments and operator contraction for coordinate sweeps

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.

Theorem selected for verification: OAI.CubeShuffle.WeightedSweep.weighted_sweep_moments

Lean statement file: WeightedSweepMoments.leanShow on the mapOpenAI’s Lean catalogue does not list this as a main result; the release’s Lean notes for family 238 link it.

See the candidate theoremWho ran the proof-verification programReport a comparison with the paper (GitHub issue)

The Lean statement

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

theorem weighted_sweep_moments :    ∃ (W : YoungDiagram → ℝ) (pStar : ℝ) (p : ℕ → ℝ),      (∀ μ : YoungDiagram, 0 < W μ) ∧      2 ≤ pStar ∧      (∀ d : ℕ, 1 ≤ d → 2 ≤ p d ∧ p d ≤ pStar) ∧      ∀ d : ℕ, 1 ≤ d → ∀ μ : Shapes (2 ^ d),        dimension μ.1 ^ (3 / 4 : ℝ) ≤ W μ.1 ∧        W μ.1 ≤ dimension μ.1 ∧        W μ.1 *          schattenNorm (V := hilbertSpace μ.1) (fourierSweep d μ) (p d) ^ (p d) ≤ 1 ∧        ‖fourierSweep d μ‖ ≤ dimension μ.1 ^ (-3 / (4 * pStar)) := 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.CubeShuffle.Specht.Cell line 9

    abbrev Cell (μ : YoungDiagram) := {x : ℕ × ℕ // x ∈ μ.cells}

  • definition OAI.CubeShuffle.Specht.row line 10

    def row {μ : YoungDiagram} (x : Cell μ) : ℕ := x.1.1

  • definition OAI.CubeShuffle.Specht.col line 11

    def col {μ : YoungDiagram} (x : Cell μ) : ℕ := x.1.2

  • definition OAI.CubeShuffle.Specht.rowIndex line 15

    noncomputable def rowIndex {μ : YoungDiagram} (x : Cell μ) : Fin (μ.colLen 0) :=  ⟨row x, (row_lt_colLen x).trans_le (μ.colLen_anti 0 (col x) (Nat.zero_le _))⟩

  • abbreviation OAI.CubeShuffle.Specht.Tabloid line 18

    abbrev Tabloid (μ : YoungDiagram) :=  {f : Cell μ → Fin (μ.colLen 0) // ∃ p : Equiv.Perm (Cell μ), f = rowIndex ∘ p}

  • definition OAI.CubeShuffle.Specht.baseTabloid line 23

    noncomputable def baseTabloid (μ : YoungDiagram) : Tabloid μ := ⟨rowIndex, 1, rfl⟩

  • definition OAI.CubeShuffle.Specht.tabloidAct line 25

    noncomputable def tabloidAct {μ : YoungDiagram} (p : Equiv.Perm (Cell μ)) :    Equiv.Perm (Tabloid μ) where
    Show the remaining 12 lines
      toFun f := ⟨fun x => f.1 (p⁻¹ x), by    obtain ⟨q,hq⟩ := f.2    refine ⟨q*p⁻¹, ?_⟩    funext x    simp only [hq,Function.comp_apply,Equiv.Perm.mul_apply]⟩  invFun f := ⟨fun x => f.1 (p x), by    obtain ⟨q,hq⟩ := f.2    refine ⟨q*p, ?_⟩    funext x    simp only [hq,Function.comp_apply,Equiv.Perm.mul_apply]⟩  left_inv f := by apply Subtype.ext; funext x; simp  right_inv f := by apply Subtype.ext; funext x; simp

  • definition OAI.CubeShuffle.Specht.tabloidRep line 57

    noncomputable def tabloidRep (μ : YoungDiagram) :    Representation ℂ (Equiv.Perm (Cell μ)) (Tabloid μ → ℂ) where
    Show the remaining 9 lines
      toFun p :=    { toFun := fun v f => v (tabloidAct p⁻¹ f)      map_add' := by intros; rfl      map_smul' := by intros; rfl }  map_one' := by ext v f; simp  map_mul' p q := by    ext v f    simp only [mul_inv_rev,tabloidAct_mul,Equiv.Perm.mul_apply]    rfl

  • definition OAI.CubeShuffle.Specht.delta line 72

    noncomputable def delta {μ : YoungDiagram} (f : Tabloid μ) : Tabloid μ → ℂ :=  fun g => if g=f then 1 else 0

  • definition OAI.CubeShuffle.Specht.colGroup line 75

    noncomputable def colGroup (μ : YoungDiagram) : Subgroup (Equiv.Perm (Cell μ)) where  carrier := {p | ∀ x, col (p x) = col x}  one_mem' := by intro x; rfl  mul_mem' := by intro p q hp hq x; exact (hp (q x)).trans (hq x)  inv_mem' := by intro p hp x; simpa using (hp (p⁻¹ x)).symm

  • definition OAI.CubeShuffle.Specht.permSign line 81

    noncomputable def permSign {α : Type*} [Fintype α] [DecidableEq α] (p : Equiv.Perm α) : ℂ :=  ((Equiv.Perm.sign p : ℤ) : ℂ)

  • definition OAI.CubeShuffle.Specht.alternator line 86

    noncomputable def alternator (C : Subgroup (Equiv.Perm α))    (ρ : Representation ℂ (Equiv.Perm α) V) : Module.End ℂ V := by  classical  exact ∑ c : C, permSign (c : Equiv.Perm α) • ρ c

  • definition OAI.CubeShuffle.Specht.polytabloid line 93

    noncomputable def polytabloid (μ : YoungDiagram) : Tabloid μ → ℂ :=  alternator (colGroup μ) (tabloidRep μ) (delta (baseTabloid μ))

  • definition OAI.CubeShuffle.Specht.space line 96

    noncomputable def space (μ : YoungDiagram) : Submodule ℂ (Tabloid μ → ℂ) :=  Submodule.span ℂ (Set.range (fun p : Equiv.Perm (Cell μ) => tabloidRep μ p (polytabloid μ)))

  • abbreviation OAI.CubeShuffle.Specht.Shapes line 220

    abbrev Shapes (N : ℕ) := {μ : YoungDiagram // μ.card = N}

  • definition OAI.CubeShuffle.WeightedSweep.dimension line 265

    def dimension (μ : YoungDiagram) : ℝ := Module.finrank ℂ (space μ)

  • definition OAI.CubeShuffle.WeightedSweep.schattenMoment line 269

    def schattenMoment {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V]    [FiniteDimensional ℂ V] (A : V →L[ℂ] V) (p : ℝ) : ℝ :=  ∑ i : Fin (Module.finrank ℂ V), (A.toLinearMap.singularValues i) ^ p

  • definition OAI.CubeShuffle.WeightedSweep.schattenNorm line 273

    def schattenNorm {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V]    [FiniteDimensional ℂ V] (A : V →L[ℂ] V) (p : ℝ) : ℝ :=  schattenMoment A p ^ (1 / p)

Possible paper match, with no recorded review

Atlas selected this possible match by comparing words in the Lean statement with every statement in the family. No review of whether the statements mean the same thing is recorded.

Words of the Lean statement, its names split into words, that also appear in the theorem: 3/4, weighted, finite, real, moments and sweep. Found in the paper’s title, which its main theorem states: row. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: exponents, consequently and absolute.

Statements in Row–column symmetry and contraction of coordinate sweeps come first because the release’s name for this Lean statement shares words with that paper’s title.

Theorem 1.1 of Row–column symmetry and contraction of coordinate sweeps

Theorem (Weighted sweep moments)

There are positive weights W_\lambda, an absolute finite p_*, and real exponents 2\le p_d\le p_* such that, for every d\ge1 and every \lambda\vdash2^d,

D_\lambda^{3/4}\le W_\lambda\le D_\lambda, \qquad W_\lambda\|K_d(\lambda)\|_{p_d}^{p_d}\le1.

Consequently \|K_d(\lambda)\|_{\rm op}\le D_\lambda^{-3/(4p_*)}.

Section 1, Introduction Read it in the paper TeX source, line 60
Show the TeX
There are positive weights $W_\lambda$, an absolute finite $p_*$, and real
exponents $2\le p_d\le p_*$ such that, for every $d\ge1$ and every
$\lambda\vdash2^d$,
\begin{equation}
 D_\lambda^{3/4}\le W_\lambda\le D_\lambda,
 \qquad W_\lambda\|K_d(\lambda)\|_{p_d}^{p_d}\le1.
\end{equation}
Consequently $\|K_d(\lambda)\|_{\rm op}\le D_\lambda^{-3/(4p_*)}$.

Other possible paper matches, closest wording first

  • Proposition 9.1 of Row–column symmetry and contraction of coordinate sweeps. Words of the Lean statement, its names split into words, that also appear in the theorem: schatten and real. Found in the paper’s title, which its main theorem states: row and sweeps. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: exponent, uniform and absolute.
  • Theorem 10.1 of Row–column symmetry and contraction of coordinate sweeps. Words of the Lean statement, its names split into words, that also appear in the theorem: schatten and moment. Found in the paper’s title, which its main theorem states: row and sweeps. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: consequently, irreducible and absolute.
  • Theorem 5.1 of Row–column symmetry and contraction of coordinate sweeps. Words of the Lean statement, its names split into words, that also appear in the theorem: spaces, cells, norm, dimension, subgroup, groups and three more. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: operator.
  • Proposition 10.2 of Row–column symmetry and contraction of coordinate sweeps. Words of the Lean statement, its names split into words, that also appear in the theorem: carrier, unit, dimensional, cells, products, groups and four more. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: absolute.
  • Proposition 10.2 of Signed tensor densities and diagram budgets for the Thorp shuffle. Words of the Lean statement, its names split into words, that also appear in the theorem: using, cells, diagram, real, moment, rows and three more. Found in the paper’s title, which its main theorem states: signed. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: constant and absolute.
  • Theorem 1.1 of Compatibility entropy and the spectrum of a Thorp sweep. Words of the Lean statement, its names split into words, that also appear in the theorem: natural, functions, weighted and groups. Found in the paper’s title, which its main theorem states: sweep. Shared only with the release’s name for the Lean statement or OpenAI’s note on it: constants, uniform and absolute.

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

three independent groups report that Comparator accepted runs for this Lean statement file: Carlos Toledo’s cert-machine; MathVet; Neal McBurnett’s openai-math-lean-tooling. 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

Neal McBurnett’s openai-math-lean-tooling

How they ran it, in their words

Each challenge’s solution is built and checked by Comparator at the pinned release, on Lean leanprover/lean4:v4.34.1, recording the verdict, the check time and the peak memory; the run was still in progress at this snapshot (192 accepted, 224 pending).

  • Accepted Their term: “accepted”.

    Re-run through Comparator with Lean’s kernel: accepted (the check took 183 s; peak memory 6.5 GiB).

    Reported 11 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 238’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.

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

  • MathVet

    Finds the whole advertised result stated or implied Their term: “full”.

    The challenge statements imply the headline claim after unpacking definitions or one routine step. Their record

    Their note: ThorpResults.remaining_main (ThorpRemaining) is a conjunction whose last conjunct OptimalOrderMain := IsTheta atTop (mixingTime d) (log (2^d)) states exactly the Θ(log N) mixing for N = 2^d cards, with mixingTime d := sInf {t | distance d t ≤ 1/4}, distance d t := tv (law d t) (uniform d) the total-variation distance of the full permutation law (and InformationMain records that lawFrom from any starting deck has the same distance, plus distance d (2048 d) → 0); the 12 other challenge files are supporting Fourier/representation estimates (regular_trace_smoothing, binary_sweep_contraction_and_mixing, robust_permanent, ...). All of them state estimates for the same hand-built Thorp shuffle.

    Definitions the group asks readers to compare with the paper: Custom Thorp shuffle and 'mixing time': step (d+1) c := (pairSwitch d c on the head bit, then rotate the coordinate order) on State d := Equiv.Perm (Fin d → Bool) with Coins (d+1) = (Fin d → Bool) → Bool iid fair coins, fairMass, tv, mixingTime d := sInf {t | distance d t ≤ 1/4}; this is the standard pair-swap-and-interleave Thorp shuffle and TV-from-uniform with ε = 1/4, but it is a hand-written model and the Θ-statement hides explicit constants (1600d, 2048d, ...). OccupiedOverlap shows an axiom_files hit (HookModel.lean) that is a doc-comment false positive.

  • Carlos Toledo’s cert-machine

    Finds the whole advertised result stated or implied Their term: “MATCHES”.

    The challenge statements state the headline as OpenAI wrote it. Their record

Read the complete assessments on the family page.

OpenAI’s own note on what this Lean statement covers

“The formalization proves uniform representation bounds for one coordinate sweep of the Thorp shuffle. For each irreducible representation of dimension $D$, it chooses a weight between $D^{3/4}$ and $D$ and a Schatten exponent bounded by one absolute constant so that the weighted Schatten moment is at most one. The sweep's operator norm is consequently at most $D^{-c}$ for one absolute $c>0$.”

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

304 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: 162 to its own declarations, 166 to Mathlib’s documentation. 27 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 OAInamespace CubeShuffle.Spechtopen scoped BigOperators Classicalabbrev Cell (μ : YoungDiagram) := {x : ℕ × ℕ // x ∈ μ.cells}def row {μ : YoungDiagram} (x : Cell μ) : ℕ := x.1.1def col {μ : YoungDiagram} (x : Cell μ) : ℕ := x.1.2lemma row_lt_colLen {μ : YoungDiagram} (x : Cell μ) : row x < μ.colLen (col x) :=  YoungDiagram.mem_iff_lt_colLen.mp x.2noncomputable def rowIndex {μ : YoungDiagram} (x : Cell μ) : Fin (μ.colLen 0) :=  ⟨row x, (row_lt_colLen x).trans_le (μ.colLen_anti 0 (col x) (Nat.zero_le _))⟩abbrev Tabloid (μ : YoungDiagram) :=  {f : Cell μ → Fin (μ.colLen 0) // ∃ p : Equiv.Perm (Cell μ), f = rowIndex ∘ p}noncomputable instance (μ : YoungDiagram) : Fintype (Tabloid μ) := Fintype.ofFinite _noncomputable def baseTabloid (μ : YoungDiagram) : Tabloid μ := ⟨rowIndex, 1, rfl⟩noncomputable def tabloidAct {μ : YoungDiagram} (p : Equiv.Perm (Cell μ)) :    Equiv.Perm (Tabloid μ) where  toFun f := ⟨fun x => f.1 (p⁻¹ x), by    obtain ⟨q,hq⟩ := f.2    refine ⟨q*p⁻¹, ?_⟩    funext x    simp only [hq,Function.comp_apply,Equiv.Perm.mul_apply]⟩  invFun f := ⟨fun x => f.1 (p x), by    obtain ⟨q,hq⟩ := f.2    refine ⟨q*p, ?_⟩    funext x    simp only [hq,Function.comp_apply,Equiv.Perm.mul_apply]⟩  left_inv f := by apply Subtype.ext; funext x; simp  right_inv f := by apply Subtype.ext; funext x; simp@[simp] lemma tabloidAct_apply {μ : YoungDiagram} (p : Equiv.Perm (Cell μ))    (f : Tabloid μ) (x : Cell μ) : (tabloidAct p f).1 x = f.1 (p⁻¹ x) := rfl@[simp] lemma tabloidAct_one (μ : YoungDiagram) : tabloidAct (1 : Equiv.Perm (Cell μ)) = 1 := by  ext f x  rfl@[simp] lemma tabloidAct_mul {μ : YoungDiagram} (p q : Equiv.Perm (Cell μ)) :    tabloidAct (p*q) = tabloidAct p * tabloidAct q := by  ext f x  simp only [tabloidAct_apply, mul_inv_rev,Equiv.Perm.mul_apply]@[simp] lemma tabloidAct_inv {μ : YoungDiagram} (p : Equiv.Perm (Cell μ)) :    tabloidAct p⁻¹ = (tabloidAct p)⁻¹ := by  ext f x  simp [tabloidAct,Equiv.Perm.inv_def]noncomputable def tabloidRep (μ : YoungDiagram) :    Representation ℂ (Equiv.Perm (Cell μ)) (Tabloid μ → ℂ) where  toFun p :=    { toFun := fun v f => v (tabloidAct p⁻¹ f)      map_add' := by intros; rfl      map_smul' := by intros; rfl }  map_one' := by ext v f; simp  map_mul' p q := by    ext v f    simp only [mul_inv_rev,tabloidAct_mul,Equiv.Perm.mul_apply]    rfl@[simp] lemma tabloidRep_apply {μ : YoungDiagram} (p : Equiv.Perm (Cell μ))    (v : Tabloid μ → ℂ) (f : Tabloid μ) : tabloidRep μ p v f = v (tabloidAct p⁻¹ f) := rflnoncomputable def delta {μ : YoungDiagram} (f : Tabloid μ) : Tabloid μ → ℂ :=  fun g => if g=f then 1 else 0noncomputable def colGroup (μ : YoungDiagram) : Subgroup (Equiv.Perm (Cell μ)) where  carrier := {p | ∀ x, col (p x) = col x}  one_mem' := by intro x; rfl  mul_mem' := by intro p q hp hq x; exact (hp (q x)).trans (hq x)  inv_mem' := by intro p hp x; simpa using (hp (p⁻¹ x)).symmnoncomputable def permSign {α : Type*} [Fintype α] [DecidableEq α] (p : Equiv.Perm α) : ℂ :=  ((Equiv.Perm.sign p : ℤ) : ℂ)section Alternatorvariable {α V : Type*} [Fintype α] [DecidableEq α] [AddCommGroup V] [Module ℂ V]noncomputable def alternator (C : Subgroup (Equiv.Perm α))    (ρ : Representation ℂ (Equiv.Perm α) V) : Module.End ℂ V := by  classical  exact ∑ c : C, permSign (c : Equiv.Perm α) • ρ cend Alternatornoncomputable def polytabloid (μ : YoungDiagram) : Tabloid μ → ℂ :=  alternator (colGroup μ) (tabloidRep μ) (delta (baseTabloid μ))noncomputable def space (μ : YoungDiagram) : Submodule ℂ (Tabloid μ → ℂ) :=  Submodule.span ℂ (Set.range (fun p : Equiv.Perm (Cell μ) => tabloidRep μ p (polytabloid μ)))lemma orbit_mem_space (μ : YoungDiagram) (p : Equiv.Perm (Cell μ)) :    tabloidRep μ p (polytabloid μ) ∈ space μ := Submodule.subset_span ⟨p,rfl⟩lemma action_mem_space (μ : YoungDiagram) (p : Equiv.Perm (Cell μ))    (v : Tabloid μ → ℂ) (hv : v ∈ space μ) : tabloidRep μ p v ∈ space μ := by  induction hv using Submodule.span_induction with  | mem v hv =>    obtain ⟨q,rfl⟩ := hv    change ((tabloidRep μ p)*(tabloidRep μ q)) (polytabloid μ) ∈ space μ    rw [←map_mul]    exact orbit_mem_space μ (p*q)  | zero => simp  | add v w hv hw ihv ihw => simpa using (space μ).add_mem ihv ihw  | smul a v hv ih => simpa using (space μ).smul_mem a ihnoncomputable def subrepresentation (μ : YoungDiagram) : Subrepresentation (tabloidRep μ) :=  ⟨space μ, fun p v hv => action_mem_space μ p v hv⟩noncomputable def representation (μ : YoungDiagram) :    Representation ℂ (Equiv.Perm (Cell μ)) (space μ) :=  (subrepresentation μ).toRepresentationend CubeShuffle.Spechtnamespace CubeShuffle.PermutationHilbertopen scoped BigOperators ComplexConjugate Classicalopen Complexvariable {X : Type*} [Fintype X]abbrev H (X : Type*) [Fintype X] := EuclideanSpace ℂ Xend CubeShuffle.PermutationHilbertnamespace CubeShuffle.Spechtopen scoped BigOperators Classicalnoncomputable def hilbertEquiv (μ : YoungDiagram) :    (Tabloid μ → ℂ) ≃ₗ[ℂ] PermutationHilbert.H (Tabloid μ) :=  (WithLp.linearEquiv 2 ℂ (Tabloid μ → ℂ)).symmnoncomputable def hilbertSpace (μ : YoungDiagram) :    Submodule ℂ (PermutationHilbert.H (Tabloid μ)) := (space μ).map (hilbertEquiv μ).toLinearMapnoncomputable def spaceHilbertEquiv (μ : YoungDiagram) : space μ ≃ₗ[ℂ] hilbertSpace μ :=  (hilbertEquiv μ).submoduleMap (space μ)noncomputable def unitaryRepresentation (μ : YoungDiagram) :    Representation ℂ (Equiv.Perm (Cell μ)) (hilbertSpace μ) :=  ((spaceHilbertEquiv μ).conjAlgEquiv ℂ).toMonoidHom.comp (representation μ)variable {α ι : Type*} [Fintype α] [Fintype ι]noncomputable def relabelledUnitary (μ : YoungDiagram) (e : α ≃ Cell μ) :    Representation ℂ (Equiv.Perm α) (hilbertSpace μ) :=  (unitaryRepresentation μ).comp e.permCongrHom.toMonoidHomend CubeShuffle.Spechtnamespace CubeShuffleopen scoped BigOperatorsopen Filterabbrev Card (d : ℕ) := Fin d → Booldef Coins : ℕ → Type  | 0 => Unit  | d + 1 => Card d → Boolinstance (d : ℕ) : Fintype (Coins d) := by  cases d <;> dsimp [Coins] <;> infer_instanceinstance (d : ℕ) : Nonempty (Coins d) := by  cases d <;> dsimp [Coins] <;> infer_instancedef switchFun {d : ℕ} (ξ : Card d → Bool) (x : Card (d + 1)) : Card (d + 1) :=  Fin.cons (Bool.xor (x 0) (ξ (Fin.tail x))) (Fin.tail x)theorem switchFun_involutive {d : ℕ} (ξ : Card d → Bool) :    Function.Involutive (switchFun ξ) := by  intro x  funext i  refine Fin.cases ?_ (fun j => ?_) i  · simp only [switchFun, Fin.cons_zero, Fin.tail_cons]    cases x 0 <;> cases ξ (Fin.tail x) <;> rfl  · simp [switchFun, Fin.tail]def pairSwitch {d : ℕ} (ξ : Card d → Bool) : Equiv.Perm (Card (d + 1)) :=  { toFun := switchFun ξ    invFun := switchFun ξ    left_inv := switchFun_involutive ξ    right_inv := switchFun_involutive ξ }def rotate (d : ℕ) : Equiv.Perm (Card d) where  toFun x i := x (finRotate d i)  invFun x i := x ((finRotate d).symm i)  left_inv x := by funext i; simp only [Equiv.apply_symm_apply]  right_inv x := by funext i; simp only [Equiv.symm_apply_apply]def step : (d : ℕ) → Coins d → Equiv.Perm (Card d)  | 0, _ => 1  | d + 1, ξ => rotate (d + 1) * pairSwitch ξdef run (d : ℕ) : (t : ℕ) → (Fin t → Coins d) → Equiv.Perm (Card d)  | 0, _ => 1  | t + 1, ω => step d (ω (Fin.last t)) * run d t (fun i => ω i.castSucc)lemma card_positions (d : ℕ) : Fintype.card (Card d) = 2 ^ d := by  simp [Card]end CubeShufflenamespace CubeShuffle.Spechtopen scoped BigOperators Classical@[simp] lemma card_cell (μ : YoungDiagram) : Fintype.card (Cell μ) = μ.card := by  simp [Cell, YoungDiagram.card]abbrev Shapes (N : ℕ) := {μ : YoungDiagram // μ.card = N}noncomputable def labels {N : ℕ} (μ : Shapes N) : Cell μ.1 ≃ Fin N :=  (Fintype.equivFin (Cell μ.1)).trans (finCongr ((card_cell μ.1).trans μ.2))noncomputable def cardLabels (d : ℕ) (μ : Shapes (2^d)) : Card d ≃ Cell μ.1 :=  ((Fintype.equivFin (Card d)).trans (finCongr (card_positions d))).trans (labels μ).symmnoncomputable def cardRepresentation (d : ℕ) (μ : Shapes (2^d)) :    Representation ℂ (Equiv.Perm (Card d)) (hilbertSpace μ.1) :=  relabelledUnitary μ.1 (cardLabels d μ)end CubeShuffle.Spechtnamespace CubeShuffle.UnitaryFiniteopen scoped BigOperators ComplexConjugate Classicalvariable {G : Type*} [Group G] [Fintype G]variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V] [FiniteDimensional ℂ V]noncomputable def continuousRepresentation (ρ : Representation ℂ G V) : G →* (V →L[ℂ] V) where  toFun g := (ρ g).toContinuousLinearMap  map_one' := by ext v; simp  map_mul' g h := by ext v; simpend CubeShuffle.UnitaryFiniterun_cmd Lean.modifyEnv fun env => Lean.Meta.auxLemmasExt.setState env {}namespace CubeShuffle.UnitaryFiniteopen scoped BigOperators Classicalvariable {G : Type*} [Group G] [Fintype G]variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V] [FiniteDimensional ℂ V]variable {Ω Ξ : Type*} [Fintype Ω] [Fintype Ξ]noncomputable def sampleOperator (ρ : Representation ℂ G V) (P : Ω → G) : V →L[ℂ] V :=  (Fintype.card Ω:ℂ)⁻¹ • ∑ ω,continuousRepresentation ρ (P ω)end CubeShuffle.UnitaryFinitenoncomputable sectionopen scoped BigOperators Classicalnamespace CubeShuffle.WeightedSweepopen Specht UnitaryFinitedef dimension (μ : YoungDiagram) : ℝ := Module.finrank ℂ (space μ)def fourierSweep (d : ℕ) (μ : Shapes (2^d)) :    hilbertSpace μ.1 →L[ℂ] hilbertSpace μ.1 :=  sampleOperator (V := hilbertSpace μ.1) (cardRepresentation d μ) (run d d)def schattenMoment {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V]    [FiniteDimensional ℂ V] (A : V →L[ℂ] V) (p : ℝ) : ℝ :=  ∑ i : Fin (Module.finrank ℂ V), (A.toLinearMap.singularValues i) ^ pdef schattenNorm {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V]    [FiniteDimensional ℂ V] (A : V →L[ℂ] V) (p : ℝ) : ℝ :=  schattenMoment A p ^ (1 / p)end CubeShuffle.WeightedSweependnoncomputable sectionopen scoped BigOperators Classicalnamespace CubeShuffle.WeightedSweepopen Specht UnitaryFinitetheorem weighted_sweep_moments :    ∃ (W : YoungDiagram → ℝ) (pStar : ℝ) (p : ℕ → ℝ),      (∀ μ : YoungDiagram, 0 < W μ) ∧      2 ≤ pStar ∧      (∀ d : ℕ, 1 ≤ d → 2 ≤ p d ∧ p d ≤ pStar) ∧      ∀ d : ℕ, 1 ≤ d → ∀ μ : Shapes (2 ^ d),        dimension μ.1 ^ (3 / 4 : ℝ) ≤ W μ.1 ∧        W μ.1 ≤ dimension μ.1 ∧        W μ.1 *          schattenNorm (V := hilbertSpace μ.1) (fourierSweep d μ) (p d) ^ (p d) ≤ 1 ∧        ‖fourierSweep d μ‖ ≤ dimension μ.1 ^ (-3 / (4 * pStar)) := by  sorryend CubeShuffle.WeightedSweependend 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.

Optimal-order mixing of the Thorp shuffle

Theorem (Optimal-order mixing)

As d\to\infty,

\|q_d^{*(1600d)}-U_n\|_{\mathrm{TV}}\longrightarrow0.

For every integer t\ge0,

\|q_d^{*t}-U_n\|_{\mathrm{TV}} \ge 1-\frac{2^{tn/2}}{n!}.

Consequently the mixing time at distance 1/4 satisfies

t_{\mathrm{mix}}(d)\ge \left\lceil\frac2n\log_2\frac{3n!}{4}\right\rceil =2d-O(1), \qquad t_{\mathrm{mix}}(d)=\Theta(d).
Section 1, Introduction Read it in the paper TeX source, line 53
Show the TeX
As $d\to\infty$,
\[
 \|q_d^{*(1600d)}-U_n\|_{\mathrm{TV}}\longrightarrow0.
\]
For every integer $t\ge0$,
\[
 \|q_d^{*t}-U_n\|_{\mathrm{TV}}
 \ge 1-\frac{2^{tn/2}}{n!}.
\]
Consequently the mixing time at distance $1/4$ satisfies
\[
 t_{\mathrm{mix}}(d)\ge
 \left\lceil\frac2n\log_2\frac{3n!}{4}\right\rceil
 =2d-O(1),
 \qquad t_{\mathrm{mix}}(d)=\Theta(d).
\]

From partial permutation information to Fourier bounds

Theorem (Complementary cosets control Fourier matrices)

Partition X into b nonempty sets M_1,\ldots,M_b. Put H_i=H_{M_i}. Suppose f is a nonnegative measure on G of mass at most one and, for every g\in G and i,

f(gH_i)\le \frac{B}{[G:H_i]}.

For every u>0 and every irreducible \rho of degree D,

\|\widehat f(\rho)\|_{\HS}^2 \le bBC_uD^{-1+(u+2)/b}.

There is also an independent orbit-span proof of the bound

\|\widehat f(\rho)\|_{\op}^2 \le bBC_uD^{-1+(u+2)/b}.

No restriction is imposed on block sizes or on the multiplicities in \rho|_{H_1\times\cdots\times H_b}.

Section 1, What partial observations can determine Read it in the paper TeX source, line 18
Show the TeX
Partition $X$ into $b$ nonempty sets $M_1,\ldots,M_b$. Put $H_i=H_{M_i}$. Suppose $f$ is a nonnegative measure on $G$ of mass at most one and, for every $g\in G$ and $i$,
\begin{equation}
 f(gH_i)\le \frac{B}{[G:H_i]}.
\end{equation}
For every $u>0$ and every irreducible $\rho$ of degree $D$,
\begin{equation}
 \|\widehat f(\rho)\|_{\HS}^2
 \le bBC_uD^{-1+(u+2)/b}.
\end{equation}
There is also an independent orbit-span proof of the bound
\begin{equation}
 \|\widehat f(\rho)\|_{\op}^2
 \le bBC_uD^{-1+(u+2)/b}.
\end{equation}
No restriction is imposed on block sizes or on the multiplicities in $\rho|_{H_1\times\cdots\times H_b}$.

Conditional permutations in a revealed switching environment

Theorem (Conditional permutation and full-deck mixing)

Let n=2^d, and start the shuffle from any deterministic deck. After J(s_0+1) sweeps, where s_0=400 and J=40000, the conditional free-slot law defined above satisfies

\sup_{\text{initial layouts}}\E_{\mathcal E} \|\nu_{\mathcal E}-U_{n/2}\|_{\TV}\longrightarrow0 \qquad(d\longrightarrow\infty).

Consequently the full-deck law approaches uniform, uniformly in the starting deck, after 16\,040\,400d physical shuffles. For every integer t\ge0, after t physical shuffles the full-deck distance from uniform is at least 1-2^{tn/2}/n!. Thus the full-deck mixing time is of order d.

Section 1, Introduction Read it in the paper TeX source, line 11
Show the TeX
Let $n=2^d$, and start the shuffle from any deterministic deck.
After $J(s_0+1)$ sweeps, where $s_0=400$ and $J=40000$, the conditional free-slot law defined above satisfies
\[
 \sup_{\text{initial layouts}}\E_{\mathcal E}
       \|\nu_{\mathcal E}-U_{n/2}\|_{\TV}\longrightarrow0
       \qquad(d\longrightarrow\infty).
\]
Consequently the full-deck law approaches uniform, uniformly in the starting deck, after $16\,040\,400d$ physical shuffles. For every integer $t\ge0$, after $t$ physical shuffles the full-deck distance from uniform is at least
$1-2^{tn/2}/n!$. Thus the full-deck mixing time is of order $d$.

Routing densities and representation contraction for Thorp sweeps

Theorem (Routing density and representation contraction)

There are absolute constants \eta,c,C>0 such that, with a=1/1000,

\log\E_{y\sim u_{N,k}}R_x(y)^{1+a} \le Ck(k/N)^\eta \qquad(1\le k\le N),

uniformly over every starting injection x. For every sufficiently large dyadic N and every nontrivial irreducible representation,

T_N(\lambda)=0\quad\hbox{or}\quad \|T_N(\lambda)\|_{\op}\le D_\lambda^{-c}.

Consequently an absolute number of forward sweeps has worst-start total-variation distance from uniform tending to zero as d\to\infty.

Section 1, Introduction Read it in the paper TeX source, line 30
Show the TeX
There are absolute constants $\eta,c,C>0$ such that, with $a=1/1000$,
\[
 \log\E_{y\sim u_{N,k}}R_x(y)^{1+a}
 \le Ck(k/N)^\eta
 \qquad(1\le k\le N),
\]
uniformly over every starting injection $x$. For every sufficiently
large dyadic $N$ and every nontrivial irreducible representation,
\[
 T_N(\lambda)=0\quad\hbox{or}\quad
 \|T_N(\lambda)\|_{\op}\le D_\lambda^{-c}.
\]
Consequently an absolute number of forward sweeps has worst-start
total-variation distance from uniform tending to zero as $d\to\infty$.

Row–column symmetry and contraction of coordinate sweeps

Theorem (Weighted sweep moments)

There are positive weights W_\lambda, an absolute finite p_*, and real exponents 2\le p_d\le p_* such that, for every d\ge1 and every \lambda\vdash2^d,

D_\lambda^{3/4}\le W_\lambda\le D_\lambda, \qquad W_\lambda\|K_d(\lambda)\|_{p_d}^{p_d}\le1.

Consequently \|K_d(\lambda)\|_{\rm op}\le D_\lambda^{-3/(4p_*)}.

Section 1, Introduction Read it in the paper TeX source, line 60
Show the TeX
There are positive weights $W_\lambda$, an absolute finite $p_*$, and real
exponents $2\le p_d\le p_*$ such that, for every $d\ge1$ and every
$\lambda\vdash2^d$,
\begin{equation}
 D_\lambda^{3/4}\le W_\lambda\le D_\lambda,
 \qquad W_\lambda\|K_d(\lambda)\|_{p_d}^{p_d}\le1.
\end{equation}
Consequently $\|K_d(\lambda)\|_{\rm op}\le D_\lambda^{-3/(4p_*)}$.
Corollary (Optimal order of mixing)

There is an absolute constant C such that, for every d\ge1,

\left\lceil\frac2N\log_2\frac{3N!}{4}\right\rceil \le t_{\rm mix}(d)\le Cd, \qquad N=2^d.

In particular t_{\rm mix}(d)=\Theta(d), and its lower bound is 2d-O(1).

Section 1, Introduction Read it in the paper TeX source, line 93
Show the TeX
There is an absolute constant $C$ such that, for every $d\ge1$,
\[
 \left\lceil\frac2N\log_2\frac{3N!}{4}\right\rceil
 \le t_{\rm mix}(d)\le Cd,
 \qquad N=2^d.
\]
In particular $t_{\rm mix}(d)=\Theta(d)$, and its lower bound is
$2d-O(1)$.

Random-subspace tests and trace smoothing for coordinate sweeps

Theorem (Regular-trace smoothing)

There is an absolute P\ge2 such that for every dyadic n\ge2,

\operatorname{Tr}_{\rm reg}|Q_n|^P\le1+n^{-10}.

If v is an integer with 2v\ge P, then v independent sweeps have total-variation distance at most \frac12n^{-5} from uniform, from every deterministic initial deck. Here \|\mu-\nu\|_{\rm TV}=\tfrac12\sum_g|\mu(g)-\nu(g)|.

Section 1, Introduction Read it in the paper TeX source, line 24
Show the TeX
There is an absolute $P\ge2$ such that for every dyadic $n\ge2$,
\begin{equation}
 \operatorname{Tr}_{\rm reg}|Q_n|^P\le1+n^{-10}.
\end{equation}
If $v$ is an integer with $2v\ge P$, then $v$ independent sweeps have total-variation distance at most $\frac12n^{-5}$ from uniform, from every deterministic initial deck. Here $\|\mu-\nu\|_{\rm TV}=\tfrac12\sum_g|\mu(g)-\nu(g)|$.

Compatibility entropy and the spectrum of a Thorp sweep

Theorem (Weighted compatibility)

There are absolute constants L,C_0>0 such that the following holds. Put m=\sqrt n, assume m/2\le A,D\le2m, and take m sufficiently large that \theta=1-L/\log m>0. For all nonnegative functions w_i:S_D\to[0,\infty) and v_k:S_A\to[0,\infty),

\frac{n!}{|R||C|}\, \mathbb E_U\!\left[\mathbf1_{\mathcal I} \prod_{i=1}^A w_i(r_i)\prod_{k=1}^D v_k(c_k)\right] \le e^{C_0n^{.54}} \prod_{i=1}^A(\mathbb E w_i^{1/\theta})^\theta \prod_{k=1}^D(\mathbb E v_k^{1/\theta})^\theta .

The expectations on the right are uniform on the indicated symmetric groups, and logarithms are natural.

Section 1, Introduction Read it in the paper TeX source, line 24
Show the TeX
There are absolute constants $L,C_0>0$ such that the following holds. Put $m=\sqrt n$, assume $m/2\le A,D\le2m$, and take $m$ sufficiently large that $\theta=1-L/\log m>0$. For all nonnegative functions $w_i:S_D\to[0,\infty)$ and $v_k:S_A\to[0,\infty)$,
\begin{equation}
 \frac{n!}{|R||C|}\,
 \mathbb E_U\!\left[\mathbf1_{\mathcal I}
       \prod_{i=1}^A w_i(r_i)\prod_{k=1}^D v_k(c_k)\right]
 \le e^{C_0n^{.54}}
       \prod_{i=1}^A(\mathbb E w_i^{1/\theta})^\theta
       \prod_{k=1}^D(\mathbb E v_k^{1/\theta})^\theta .
\end{equation}
The expectations on the right are uniform on the indicated symmetric groups, and logarithms are natural.
Theorem (A bounded regular moment)

There is an absolute finite p_*>0 such that, for every dyadic n,

Z_n(p_*)\le1+\frac1{16}.

For every integer M\ge p_*, M independent forward sweeps have worst-start total-variation distance at most 1/8 from uniform.

Section 1, Introduction Read it in the paper TeX source, line 45
Show the TeX
There is an absolute finite $p_*>0$ such that, for every dyadic $n$,
\begin{equation}
 Z_n(p_*)\le1+\frac1{16}.
\end{equation}
For every integer $M\ge p_*$, $M$ independent forward sweeps have worst-start total-variation distance at most $1/8$ from uniform.
Corollary (Singular ranks and full-deck mixing)

For every nontrivial \lambda\vdash n and 1\le r\le D_\lambda,

s_r(T_{n,\lambda})\le(16D_\lambda r)^{-1/(2p_*)}.

If s_j(T_n) denotes the full regular singular list, including all multiplicities and zeros, then

s_j(T_n)\le j^{-1/(2p_*)}\qquad(1\le j\le n!).

The constant singular value is the first value. The physical Thorp chain has worst-start 1/4 mixing time \Theta(d); more precisely its lower bound is 2d-O(1). For every fixed integer M>p_*, the worst-start total-variation distance after Md physical shuffles tends to zero as d\to\infty.

Section 1, Introduction Read it in the paper TeX source, line 53
Show the TeX
For every nontrivial $\lambda\vdash n$ and $1\le r\le D_\lambda$,
\[
 s_r(T_{n,\lambda})\le(16D_\lambda r)^{-1/(2p_*)}.
\]
If $s_j(T_n)$ denotes the full regular singular list, including all multiplicities and zeros, then
\[
 s_j(T_n)\le j^{-1/(2p_*)}\qquad(1\le j\le n!).
\]
The constant singular value is the first value. The physical Thorp chain has worst-start $1/4$ mixing time $\Theta(d)$; more precisely its lower bound is $2d-O(1)$. For every fixed integer $M>p_*$, the worst-start total-variation distance after $Md$ physical shuffles tends to zero as $d\to\infty$.

Signed tensor densities and diagram budgets for the Thorp shuffle

Theorem (A moment bound for every signed occurrence)

For each sufficiently small fixed \bar\eta>0, choose a sufficiently small \bar\kappa>0 with \bar\kappa<\bar\eta/256. There is an integer r\ge1, depending only on these fixed constants, such that for every d\ge1, every \lambda\vdash n=2^d, and every occurrence (ten:spin:eq:1),

\log\!\left(D_\lambda\operatorname{Tr}_{V_\lambda}(B_n^*B_n)^r\right) \le\eta_d F(\alpha,\beta)+g_n(l),

where

\eta_d=\bar\eta\left(1-\frac1{2\sqrt d}\right),\qquad \kappa_d=\bar\kappa\left(1-\frac1{2\sqrt d}\right),\qquad g_n(l)=\max\{0,\kappa_d l\log n-l\log(n/l)\}.

Set g_n(0)=0 and interpret the logarithm of a zero trace as -\infty.

Section 1, Introduction Read it in the paper TeX source, line 48
Show the TeX
For each sufficiently small fixed $\bar\eta>0$, choose a sufficiently
small $\bar\kappa>0$ with $\bar\kappa<\bar\eta/256$. There is an
integer $r\ge1$, depending only on these fixed constants, such that for
every $d\ge1$, every $\lambda\vdash n=2^d$, and every
occurrence~\eqref{ten:spin:eq:1},
\begin{equation}
 \log\!\left(D_\lambda\operatorname{Tr}_{V_\lambda}(B_n^*B_n)^r\right)
 \le\eta_d F(\alpha,\beta)+g_n(l),
\end{equation}
where
\[
 \eta_d=\bar\eta\left(1-\frac1{2\sqrt d}\right),\qquad
 \kappa_d=\bar\kappa\left(1-\frac1{2\sqrt d}\right),\qquad
 g_n(l)=\max\{0,\kappa_d l\log n-l\log(n/l)\}.
\]
Set $g_n(0)=0$ and interpret the logarithm of a zero trace as $-\infty$.
Corollary (Fixed-sweep convergence of the full deck)

There is an absolute positive integer L such that

\mathbb E_{U_{S_n}}|f_{d,L}-1|^2\longrightarrow0 \qquad(d\longrightarrow\infty).

The convergence is uniform over starting orders. Moreover t_{\mathrm{mix}}(d)=\Theta(d).

Section 1, Introduction Read it in the paper TeX source, line 82
Show the TeX
There is an absolute positive integer $L$ such that
\[
 \mathbb E_{U_{S_n}}|f_{d,L}-1|^2\longrightarrow0
 \qquad(d\longrightarrow\infty).
\]
The convergence is uniform over starting orders. Moreover
$t_{\mathrm{mix}}(d)=\Theta(d)$.

Conditional coordinate sweeps and analytic transfer

Theorem (Binary sweep contraction)

There are absolute constants g>0 and d_0 such that, for d\ge d_0 and every \lambda\vdash 2^d,

\|K_\lambda\|_{\op}\le D_\lambda^{-g}.

The sign representation is annihilated. There is an absolute positive integer w such that the law after w independent sweeps converges to uniform in total variation as d\to\infty, uniformly over deterministic initial decks.

Section 1, Introduction Read it in the paper TeX source, line 54
Show the TeX
There are absolute constants \(g>0\) and \(d_0\) such that, for \(d\ge d_0\)
and every \(\lambda\vdash 2^d\),
\[
 \|K_\lambda\|_{\op}\le D_\lambda^{-g}.
\]
The sign representation is annihilated. There is an absolute positive integer \(w\)
such that the law after \(w\) independent sweeps converges to uniform in
total variation as \(d\to\infty\), uniformly over deterministic initial
decks.
Proposition (Support obstruction)

For every integer t\ge0,

\|q_d^{*t}-U_N\|_{\TV}\ge1-\frac{2^{tN/2}}{N!}.

Consequently,

t_{\rm mix}(d)\ge \left\lceil\frac2N\log_2\!\left(\frac{3N!}{4}\right)\right\rceil =2d-O(1).
Section 1, Introduction Read it in the paper TeX source, line 68
Show the TeX
For every integer \(t\ge0\),
\[
 \|q_d^{*t}-U_N\|_{\TV}\ge1-\frac{2^{tN/2}}{N!}.
\]
Consequently,
\[
 t_{\rm mix}(d)\ge
 \left\lceil\frac2N\log_2\!\left(\frac{3N!}{4}\right)\right\rceil
 =2d-O(1).
\]

A strict four-row permanent inequality and permutation moments

Theorem (A robust four-row inequality)

There are absolute constants p_0\in(4/3,2) and \varepsilon>0 with the following property. Let \nu be a probability measure on S_4 such that

\|\nu-u\|_{\TV}<\varepsilon, \qquad \nu\{\pi:\pi(i)=j\}=\frac14\quad(1\le i,j\le4).

Then every four nonnegative functions on \{1,2,3,4\} satisfy

\E_\nu\prod_{i=1}^4f_i(\pi(i))\le\prod_{i=1}^4\|f_i\|_{p_0}.
Section 1, Introduction Read it in the paper TeX source, line 14
Show the TeX
There are absolute constants $p_0\in(4/3,2)$ and $\varepsilon>0$ with the following property. Let $\nu$ be a probability measure on $S_4$ such that
\[
 \|\nu-u\|_{\TV}<\varepsilon,
 \qquad
 \nu\{\pi:\pi(i)=j\}=\frac14\quad(1\le i,j\le4).
\]
Then every four nonnegative functions on $\{1,2,3,4\}$ satisfy
\begin{equation}
 \E_\nu\prod_{i=1}^4f_i(\pi(i))\le\prod_{i=1}^4\|f_i\|_{p_0}.
\end{equation}
Theorem (A fixed moment with a degree saving)

There exist an even integer r\ge2 and \eta>0, independent of N, such that for every dyadic N and every \lambda\vdash N,

D_\lambda\Tr B_N(\lambda)^r\le D_\lambda^{1-\eta}.

Consequently there is an absolute integer q for which the total-variation distance of q independent forward sweeps from uniform tends to zero as N\to\infty, uniformly over the starting deck.

Section 1, Introduction Read it in the paper TeX source, line 46
Show the TeX
There exist an even integer $r\ge2$ and $\eta>0$, independent of $N$, such that for every dyadic $N$ and every $\lambda\vdash N$,
\begin{equation}
 D_\lambda\Tr B_N(\lambda)^r\le D_\lambda^{1-\eta}.
\end{equation}
Consequently there is an absolute integer $q$ for which the total-variation distance of $q$ independent forward sweeps from uniform tends to zero as $N\to\infty$, uniformly over the starting deck.
Configuration and file facts
OpenAI’s Lean catalogue
OpenAI’s Lean catalogue does not list this as a main result; the release’s Lean notes for family 238 link it.
Solution module
OAI.Probability.CubeShuffle.WeightedMoments
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
42 local vocabulary declarations
Lines of Lean, without comments or blank lines
175
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

Weighted Schatten moments and operator contraction for coordinate sweeps

Family 238: Optimal logarithmic mixing of the Thorp shuffle

Candidate pairing

Theorem (Weighted sweep moments)

There are positive weights W_\lambda, an absolute finite p_*, and real exponents 2\le p_d\le p_* such that, for every d\ge1 and every \lambda\vdash2^d,

D_\lambda^{3/4}\le W_\lambda\le D_\lambda, \qquad W_\lambda\|K_d(\lambda)\|_{p_d}^{p_d}\le1.

Consequently \|K_d(\lambda)\|_{\rm op}\le D_\lambda^{-3/(4p_*)}.

Row–column symmetry and contraction of coordinate sweeps

TeX label thm:weighted, build/sections/introduction.tex, line 60

The Lean statement says

theorem weighted_sweep_moments :    ∃ (W : YoungDiagram → ℝ) (pStar : ℝ) (p : ℕ → ℝ),      (∀ μ : YoungDiagram, 0 < W μ) ∧      2 ≤ pStar ∧      (∀ d : ℕ, 1 ≤ d → 2 ≤ p d ∧ p d ≤ pStar) ∧      ∀ d : ℕ, 1 ≤ d → ∀ μ : Shapes (2 ^ d),        dimension μ.1 ^ (3 / 4 : ℝ) ≤ W μ.1 ∧        W μ.1 ≤ dimension μ.1 ∧        W μ.1 *          schattenNorm (V := hilbertSpace μ.1) (fourierSweep d μ) (p d) ^ (p d) ≤ 1 ∧        ‖fourierSweep d μ‖ ≤ dimension μ.1 ^ (-3 / (4 * pStar)) := 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.

Atlas selected this possible match because the two statements share words. No review of whether they mean the same thing is recorded.three independent groups report that Comparator accepted runs for this file at the release version shown here.Statement review: none recorded

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

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