import Mathlib import OAI.Computability.MaxCut.Games.Basic namespace OAI noncomputable section /-! Finite threshold-overlap estimates used in the Dinur--Steurer argument. These statements are numerical inequalities, not parallel-repetition premises. The Boolean gate keeps the constraint predicate inside the overlap energy. Weights need not be normalized: a finite auxiliary measure is permitted. -/ namespace MaxCutGames.Repetition.Analytic open scoped BigOperators variable {ι : Type*} [Fintype ι] def quadraticMass (w f g : ι → ℝ) : ℝ := ∑ i, w i * ((f i) ^ 2 + (g i) ^ 2) / 2 def gatedCorrelation (w f g : ι → ℝ) (gate : ι → Bool) : ℝ := ∑ i, if gate i then w i * f i * g i else 0 def gatedMinimum (w f g : ι → ℝ) (gate : ι → Bool) : ℝ := ∑ i, if gate i then w i * min ((f i) ^ 2) ((g i) ^ 2) else 0 def gatedMaximum (w f g : ι → ℝ) (gate : ι → Bool) : ℝ := ∑ i, if gate i then w i * max ((f i) ^ 2) ((g i) ^ 2) else 0 theorem quadraticMass_nonnegative (w f g : ι → ℝ) (hw : ∀ i, 0 ≤ w i) : 0 ≤ quadraticMass w f g := by apply Finset.sum_nonneg intro i _ exact div_nonneg (mul_nonneg (hw i) (add_nonneg (sq_nonneg _) (sq_nonneg _))) (by norm_num) theorem gatedCorrelation_nonnegative (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) (hf : ∀ i, 0 ≤ f i) (hg : ∀ i, 0 ≤ g i) : 0 ≤ gatedCorrelation w f g gate := by apply Finset.sum_nonneg intro i _ split · exact mul_nonneg (mul_nonneg (hw i) (hf i)) (hg i) · exact le_rfl theorem gatedCorrelation_le_mass (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) : gatedCorrelation w f g gate ≤ quadraticMass w f g := by apply Finset.sum_le_sum intro i _ split · have hfg : f i * g i ≤ ((f i) ^ 2 + (g i) ^ 2) / 2 := by nlinarith [sq_nonneg (f i - g i)] simpa only [← mul_assoc, mul_div_assoc] using mul_le_mul_of_nonneg_left hfg (hw i) · exact div_nonneg (mul_nonneg (hw i) (add_nonneg (sq_nonneg _) (sq_nonneg _))) (by norm_num) theorem gatedMinimum_nonnegative (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) : 0 ≤ gatedMinimum w f g gate := by apply Finset.sum_nonneg intro i _ split · exact mul_nonneg (hw i) (le_min (sq_nonneg _) (sq_nonneg _)) · exact le_rfl theorem gatedMinimum_le_mass (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) : gatedMinimum w f g gate ≤ quadraticMass w f g := by apply Finset.sum_le_sum intro i _ split · have hmin : min ((f i) ^ 2) ((g i) ^ 2) ≤ ((f i) ^ 2 + (g i) ^ 2) / 2 := by have h₁ := min_le_left ((f i) ^ 2) ((g i) ^ 2) have h₂ := min_le_right ((f i) ^ 2) ((g i) ^ 2) linarith simpa only [mul_div_assoc] using mul_le_mul_of_nonneg_left hmin (hw i) · exact div_nonneg (mul_nonneg (hw i) (add_nonneg (sq_nonneg _) (sq_nonneg _))) (by norm_num) theorem gatedMinimum_add_maximum_le (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) : gatedMinimum w f g gate + gatedMaximum w f g gate ≤ 2 * quadraticMass w f g := by unfold gatedMinimum gatedMaximum quadraticMass rw [← Finset.sum_add_distrib, Finset.mul_sum] apply Finset.sum_le_sum intro i _ by_cases hi : gate i = true · simp only [hi, ↓reduceIte] have h := min_add_max ((f i) ^ 2) ((g i) ^ 2) rw [← mul_add, h] ring_nf ; exact le_rfl · simp only [hi, Bool.false_eq_true, ↓reduceIte, zero_add] have := hw i positivity /-- A gated finite Cauchy--Schwarz estimate. This is the algebraic heart of the threshold-rounding inequality, with no independence assumption. -/ theorem gatedCorrelation_sq_le_min_mul_max (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) : gatedCorrelation w f g gate ^ 2 ≤ gatedMinimum w f g gate * gatedMaximum w f g gate := by apply Finset.sum_sq_le_sum_mul_sum_of_sq_le_mul · intro i _ split · exact mul_nonneg (hw i) (le_min (sq_nonneg _) (sq_nonneg _)) · exact le_rfl · intro i _ split · exact mul_nonneg (hw i) ((sq_nonneg (f i)).trans (le_max_left _ _)) · exact le_rfl · intro i _ by_cases hi : gate i = true · simp only [hi, ↓reduceIte] rcases le_total ((f i) ^ 2) ((g i) ^ 2) with h | h · rw [min_eq_left h, max_eq_right h] ring_nf ; exact le_rfl · rw [min_eq_right h, max_eq_left h] ring_nf ; exact le_rfl · simp [hi] theorem gatedCorrelation_sq_le_min_quadratic (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) : gatedCorrelation w f g gate ^ 2 ≤ gatedMinimum w f g gate * (2 * quadraticMass w f g - gatedMinimum w f g gate) := by have hmax := gatedMinimum_add_maximum_le w f g gate hw have hmin := gatedMinimum_nonnegative w f g gate hw exact (gatedCorrelation_sq_le_min_mul_max w f g gate hw).trans (mul_le_mul_of_nonneg_left (by linarith) hmin) /-- Sharp homogeneous Cheeger form. The expression under the square root is nonnegative by the preceding proved inequality. -/ theorem gatedMinimum_cheeger (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) : quadraticMass w f g - Real.sqrt (quadraticMass w f g ^ 2 - gatedCorrelation w f g gate ^ 2) ≤ gatedMinimum w f g gate := by have h := gatedCorrelation_sq_le_min_quadratic w f g gate hw have hsq : (quadraticMass w f g - gatedMinimum w f g gate) ^ 2 ≤ quadraticMass w f g ^ 2 - gatedCorrelation w f g gate ^ 2 := by nlinarith have hsqrt := Real.le_sqrt_of_sq_le hsq linarith /-- The near-perfect form suffices for alphabet-independent repetition. The total squared mass may be at most one, rather than exactly one. -/ theorem gatedMinimum_near_one (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) {η : ℝ} (_hη : 0 ≤ η) (hη₁ : η ≤ 1) (hmass : quadraticMass w f g ≤ 1) (hcorrelation : 1 - η ≤ gatedCorrelation w f g gate) : 1 - Real.sqrt (2 * η) ≤ gatedMinimum w f g gate := by have hmin := gatedMinimum_nonnegative w f g gate hw have h := gatedCorrelation_sq_le_min_quadratic w f g gate hw have hcorr : 0 ≤ gatedCorrelation w f g gate := by linarith have hsqcorr : (1 - η) ^ 2 ≤ gatedCorrelation w f g gate ^ 2 := by nlinarith have hupper : gatedMinimum w f g gate * (2 * quadraticMass w f g - gatedMinimum w f g gate) ≤ gatedMinimum w f g gate * (2 - gatedMinimum w f g gate) := by apply mul_le_mul_of_nonneg_left _ hmin linarith have hsq : (1 - gatedMinimum w f g gate) ^ 2 ≤ 2 * η := by nlinarith [sq_nonneg η] have hsqrt := Real.le_sqrt_of_sq_le hsq linarith /-- Unit-mass form for the joint question-pair and auxiliary-coordinate law. -/ theorem gatedMinimum_unit_mass (w f g : ι → ℝ) (gate : ι → Bool) (hw : ∀ i, 0 ≤ w i) (hf : ∀ i, 0 ≤ f i) (hg : ∀ i, 0 ≤ g i) (hmass : quadraticMass w f g = 1) : 1 - Real.sqrt (2 * (1 - gatedCorrelation w f g gate)) ≤ gatedMinimum w f g gate := by have hc₀ := gatedCorrelation_nonnegative w f g gate hw hf hg have hc₁ := gatedCorrelation_le_mass w f g gate hw rw [hmass] at hc₁ apply gatedMinimum_near_one w f g gate hw · linarith · linarith · exact hmass.le · linarith end MaxCutGames.Repetition.Analytic /-! Finite vertex-specific padding of nonnegative vectors to unit squared row mass. The new coordinates can only increase any nonnegative relation energy. -/ namespace MaxCutGames.Repetition section open scoped BigOperators open Foundations.Games variable {V A Ω E : Type*} [Fintype V] [Fintype Ω] [Fintype E] def rowSquareMass (f : V → Ω → ℝ) (v : V) : ℝ := ∑ ω, (f v ω) ^ 2 def paddedAmplitude [DecidableEq V] (f : V → Ω → ℝ) (v : V) : Ω ⊕ V → ℝ | Sum.inl ω => f v ω | Sum.inr w => if v = w then Real.sqrt (1 - rowSquareMass f v) else 0 def paddedLabel (a : V → Ω → A) (fallback : A) (v : V) : Ω ⊕ V → A | Sum.inl ω => a v ω | Sum.inr _ => fallback omit [Fintype V] in theorem paddedAmplitude_nonnegative [DecidableEq V] (f : V → Ω → ℝ) (hf : ∀ v ω, 0 ≤ f v ω) (v : V) (ω : Ω ⊕ V) : 0 ≤ paddedAmplitude f v ω := by cases ω with | inl ω => exact hf v ω | inr w => simp only [paddedAmplitude] split · exact Real.sqrt_nonneg _ · exact le_rfl theorem paddedAmplitude_row [DecidableEq V] (f : V → Ω → ℝ) (hrow : ∀ v, rowSquareMass f v ≤ 1) (v : V) : rowSquareMass (paddedAmplitude f) v = 1 := by have hs : Real.sqrt (1 - rowSquareMass f v) ^ 2 = 1 - rowSquareMass f v := Real.sq_sqrt (sub_nonneg.mpr (hrow v)) simp only [rowSquareMass] at hs simp only [rowSquareMass, Fintype.sum_sum_type, paddedAmplitude] simp only [ite_pow, zero_pow (by decide : 2 ≠ 0)] rw [Finset.sum_ite_eq, ite_eq_left (Finset.mem_univ v), hs] ring def pairEnergy (ν : FiniteDistribution E) (left right : E → V) (R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) : ℝ := ν.expectation fun e => ∑ ω, if R e (a (left e) ω) (a (right e) ω) then f (left e) ω * f (right e) ω else 0 def pairOverlap (ν : FiniteDistribution E) (left right : E → V) (R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) : ℝ := ν.expectation fun e => ∑ ω, if R e (a (left e) ω) (a (right e) ω) then min ((f (left e) ω) ^ 2) ((f (right e) ω) ^ 2) else 0 omit [Fintype V] in theorem pairEnergy_nonnegative (ν : FiniteDistribution E) (left right : E → V) (R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) (hf : ∀ v ω, 0 ≤ f v ω) : 0 ≤ pairEnergy ν left right R a f := by apply Finset.sum_nonneg intro e _ apply mul_nonneg (ν.nonnegative e) apply Finset.sum_nonneg intro ω _ split · exact mul_nonneg (hf (left e) ω) (hf (right e) ω) · exact le_rfl theorem pairEnergy_le_padded [DecidableEq V] (ν : FiniteDistribution E) (left right : E → V) (R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) (hf : ∀ v ω, 0 ≤ f v ω) (fallback : A) : pairEnergy ν left right R a f ≤ pairEnergy ν left right R (paddedLabel a fallback) (paddedAmplitude f) := by unfold pairEnergy FiniteDistribution.expectation apply Finset.sum_le_sum intro e _ apply mul_le_mul_of_nonneg_left _ (ν.nonnegative e) dsimp only rw [Fintype.sum_sum_type] simp only [paddedLabel, paddedAmplitude] have hnonneg : 0 ≤ ∑ w : V, if R e fallback fallback then (if left e = w then Real.sqrt (1 - rowSquareMass f (left e)) else 0) * (if right e = w then Real.sqrt (1 - rowSquareMass f (right e)) else 0) else 0 := by apply Finset.sum_nonneg intro w _ split · exact mul_nonneg (paddedAmplitude_nonnegative f hf (left e) (Sum.inr w)) (paddedAmplitude_nonnegative f hf (right e) (Sum.inr w)) · exact le_rfl exact le_add_of_nonneg_right hnonneg end /-! Flatten the genuine finite occurrence law together with the auxiliary coordinate into the Cheeger inequality. The occurrence may retain hidden information; both endpoint label tables still depend only on their vertex. -/ open scoped BigOperators open Foundations.Games variable {V A Ω E : Type*} [Fintype V] [Fintype Ω] [Fintype E] omit [Fintype V] in theorem pairQuadraticMass_eq_one (ν : FiniteDistribution E) (left right : E → V) (f : V → Ω → ℝ) (hrow : ∀ v, rowSquareMass f v = 1) : Analytic.quadraticMass (fun p : E × Ω => ν.weight p.1) (fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2) = 1 := by unfold Analytic.quadraticMass rw [Fintype.sum_prod_type] have he (e : E) : (∑ ω, ν.weight e * ((f (left e) ω) ^ 2 + (f (right e) ω) ^ 2) / 2) = ν.weight e := by calc _ = ν.weight e * ((∑ ω, (f (left e) ω) ^ 2) + (∑ ω, (f (right e) ω) ^ 2)) / 2 := by simp only [div_eq_mul_inv, mul_add, add_mul, Finset.sum_add_distrib, Finset.mul_sum, Finset.sum_mul] _ = ν.weight e := by change ν.weight e * (rowSquareMass f (left e) + rowSquareMass f (right e)) / 2 = _ rw [hrow, hrow] ring simp_rw [he] exact ν.normalized omit [Fintype V] in theorem pairGatedCorrelation_eq_energy (ν : FiniteDistribution E) (left right : E → V) (R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) : Analytic.gatedCorrelation (fun p : E × Ω => ν.weight p.1) (fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2) (fun p => R p.1 (a (left p.1) p.2) (a (right p.1) p.2)) = pairEnergy ν left right R a f := by simp only [Analytic.gatedCorrelation, pairEnergy, FiniteDistribution.expectation, Fintype.sum_prod_type, Finset.mul_sum, mul_ite, mul_zero, mul_assoc] omit [Fintype V] in theorem pairGatedMinimum_eq_overlap (ν : FiniteDistribution E) (left right : E → V) (R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) : Analytic.gatedMinimum (fun p : E × Ω => ν.weight p.1) (fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2) (fun p => R p.1 (a (left p.1) p.2) (a (right p.1) p.2)) = pairOverlap ν left right R a f := by simp only [Analytic.gatedMinimum, pairOverlap, FiniteDistribution.expectation, Fintype.sum_prod_type, Finset.mul_sum, mul_ite, mul_zero] omit [Fintype V] in theorem pairEnergy_le_one_of_unit_rows (ν : FiniteDistribution E) (left right : E → V) (R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) (hrow : ∀ v, rowSquareMass f v = 1) : pairEnergy ν left right R a f ≤ 1 := by have h := Analytic.gatedCorrelation_le_mass (fun p : E × Ω => ν.weight p.1) (fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2) (fun p => R p.1 (a (left p.1) p.2) (a (right p.1) p.2)) (fun p => ν.nonnegative p.1) rw [pairGatedCorrelation_eq_energy, pairQuadraticMass_eq_one ν left right f hrow] at h exact h omit [Fintype V] in /-- The overlap used by finite threshold sampling is large whenever the actual weighted occurrence energy is large. -/ theorem pairOverlap_ge_energy (ν : FiniteDistribution E) (left right : E → V) (R : E → A → A → Bool) (a : V → Ω → A) (f : V → Ω → ℝ) (hf : ∀ v ω, 0 ≤ f v ω) (hrow : ∀ v, rowSquareMass f v = 1) : 1 - Real.sqrt (2 * (1 - pairEnergy ν left right R a f)) ≤ pairOverlap ν left right R a f := by have h := Analytic.gatedMinimum_unit_mass (fun p : E × Ω => ν.weight p.1) (fun p => f (left p.1) p.2) (fun p => f (right p.1) p.2) (fun p => R p.1 (a (left p.1) p.2) (a (right p.1) p.2)) (fun p => ν.nonnegative p.1) (fun p => hf (left p.1) p.2) (fun p => hf (right p.1) p.2) (pairQuadraticMass_eq_one ν left right f hrow) rw [pairGatedCorrelation_eq_energy, pairGatedMinimum_eq_overlap] at h exact h end MaxCutGames.Repetition end end OAI