import Mathlib.Analysis.Real.Sqrt import Mathlib.Data.Fintype.Sum import OAI.Computability.UniqueGames.Foundations.FiniteTrialsLemmas import OAI.Computability.UniqueGames.Repetition.AnalyticCheegerLemmas import OAI.Computability.UniqueGames.Repetition.CollisionLemmas namespace OAI section /-! Finite vertex-specific padding of nonnegative vectors to unit squared row mass. The new coordinates can only increase any nonnegative relation energy. -/ namespace UniqueGamesTheorem.Repetition open scoped BigOperators open Foundations.Games noncomputable section 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 end UniqueGamesTheorem.Repetition end section /-! 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. -/ namespace UniqueGamesTheorem.Repetition open scoped BigOperators open Foundations.Games noncomputable section 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 end UniqueGamesTheorem.Repetition end section /-! The collision norm as an actual finite distribution on symmetrized edges. An edge retains the hidden common right question, while each label remains a function of its own left question. Projection uniqueness turns the sum over common right answers into a Boolean compatibility predicate exactly. -/ namespace UniqueGamesTheorem.Repetition.ProjectionKernel open Foundations.Games open scoped BigOperators noncomputable section attribute [local instance] Classical.propDecidable variable {Q₁ Q₂ A₁ A₂ Ω : Type*} [Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂] [Fintype Ω] abbrev SymmetricEdge (Q₁ Q₂ : Type*) := Q₂ × Q₁ × Q₁ def symmetricLeft (e : SymmetricEdge Q₁ Q₂) : Q₁ := e.2.1 def symmetricRight (e : SymmetricEdge Q₁ Q₂) : Q₁ := e.2.2 def symmetricDistribution (K : ProjectionKernel Q₁ Q₂ A₁ A₂) : FiniteDistribution (SymmetricEdge Q₁ Q₂) where weight e := K.outer.weight e.1 * (K.inner e.1).weight e.2.1 * (K.inner e.1).weight e.2.2 nonnegative e := mul_nonneg (mul_nonneg (K.outer.nonnegative _) ((K.inner _).nonnegative _)) ((K.inner _).nonnegative _) normalized := by rw [Fintype.sum_prod_type] calc _ = ∑ y, K.outer.weight y := by apply Finset.sum_congr rfl intro y _ rw [Fintype.sum_prod_type] calc _ = ∑ x, K.outer.weight y * (K.inner y).weight x := by apply Finset.sum_congr rfl intro x _ dsimp only rw [← Finset.mul_sum, (K.inner y).normalized, mul_one] _ = K.outer.weight y := by rw [← Finset.mul_sum, (K.inner y).normalized, mul_one] _ = 1 := K.outer.normalized def symmetricAccept (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (e : SymmetricEdge Q₁ Q₂) (a a' : A₁) : Bool := by classical exact decide (∃ b, K.accepts e.2.1 e.1 a b = true ∧ K.accepts e.2.2 e.1 a' b = true) /-- A coordinate has one possible nonzero label at each question. -/ def singleLabelVector (a : Q₁ → Ω → A₁) (f : Q₁ → Ω → ℝ) (ω : Ω) (x : Q₁) (b : A₁) : ℝ := by classical exact if a x ω = b then f x ω else 0 theorem sum_projection_gates (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (y : Q₂) (x x' : Q₁) (a a' : A₁) (r s : ℝ) : (∑ b, (if K.accepts x y a b then r else 0) * (if K.accepts x' y a' b then s else 0)) = if K.symmetricAccept (y, x, x') a a' then r * s else 0 := by classical by_cases hex : ∃ b, K.accepts x y a b = true ∧ K.accepts x' y a' b = true · obtain ⟨b₀, hb₀, hb₀'⟩ := hex have hex' : ∃ b, K.accepts x y a b = true ∧ K.accepts x' y a' b = true := ⟨b₀, hb₀, hb₀'⟩ simp only [symmetricAccept, hex', decide_true, ite_true] calc _ = (if K.accepts x y a b₀ then r else 0) * (if K.accepts x' y a' b₀ then s else 0) := by apply Finset.sum_eq_single b₀ · intro b _ hne have hb : K.accepts x y a b ≠ true := by intro hb exact hne (K.projection x y a b b₀ hb hb₀) simp [hb] · simp _ = r * s := by simp [hb₀, hb₀'] · simp only [symmetricAccept, hex, decide_false, Bool.false_eq_true, ite_false] apply Finset.sum_eq_zero intro b _ by_cases hb : K.accepts x y a b = true · have hb' : K.accepts x' y a' b ≠ true := fun hb' => hex ⟨b, hb, hb'⟩ simp [hb'] · simp [hb] theorem apply_single_label (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (labels : Q₁ → A₁) (f : Q₁ → ℝ) (y : Q₂) (b : A₂) : K.apply (fun x a => if labels x = a then f x else 0) y b = ∑ x, (K.inner y).weight x * (if K.accepts x y (labels x) b then f x else 0) := by classical unfold apply apply Finset.sum_congr rfl intro x _ congr 1 calc _ = ∑ a, if labels x = a then (if K.accepts x y (labels x) b then f x else 0) else 0 := by apply Finset.sum_congr rfl intro a _ by_cases ha : labels x = a · subst a simp · simp [ha] _ = _ := by simp theorem energy_single_label (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (labels : Q₁ → A₁) (f : Q₁ → ℝ) : K.energy (fun x a => if labels x = a then f x else 0) = K.symmetricDistribution.expectation (fun e => if K.symmetricAccept e (labels (symmetricLeft e)) (labels (symmetricRight e)) then f (symmetricLeft e) * f (symmetricRight e) else 0) := by classical have hexpand (y : Q₂) : (∑ b, (∑ x, (K.inner y).weight x * (if K.accepts x y (labels x) b then f x else 0)) ^ 2) = ∑ x, ∑ x', (K.inner y).weight x * (K.inner y).weight x' * (if K.symmetricAccept (y, x, x') (labels x) (labels x') then f x * f x' else 0) := by simp only [pow_two, Finset.sum_mul, Finset.mul_sum] rw [Finset.sum_comm] apply Finset.sum_congr rfl intro x _ rw [Finset.sum_comm] apply Finset.sum_congr rfl intro x' _ calc _ = (K.inner y).weight x * (K.inner y).weight x' * ∑ b, (if K.accepts x y (labels x) b then f x else 0) * (if K.accepts x' y (labels x') b then f x' else 0) := by rw [Finset.mul_sum] apply Finset.sum_congr rfl intro b _ ring _ = _ := by rw [K.sum_projection_gates] unfold energy simp_rw [K.apply_single_label, hexpand] simp only [FiniteDistribution.expectation, symmetricDistribution, Fintype.sum_prod_type, symmetricLeft, symmetricRight, Finset.mul_sum] apply Finset.sum_congr rfl intro y _ apply Finset.sum_congr rfl intro x _ apply Finset.sum_congr rfl intro x' _ simp only [mul_assoc] rfl /-- Coordinate expansion and the symmetrized edge law agree exactly. -/ theorem vectorEnergy_singleLabelVector (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (a : Q₁ → Ω → A₁) (f : Q₁ → Ω → ℝ) : K.vectorEnergy (singleLabelVector a f) = pairEnergy K.symmetricDistribution symmetricLeft symmetricRight K.symmetricAccept a f := by classical unfold vectorEnergy singleLabelVector simp_rw [K.energy_single_label] unfold pairEnergy FiniteDistribution.expectation rw [Finset.sum_comm] apply Finset.sum_congr rfl intro e _ rw [Finset.mul_sum] /-- Ordinary deterministic labelings give the collision assignment energy. -/ theorem symmetric_probability_eq_assignmentEnergy (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (labels : Q₁ → A₁) : K.symmetricDistribution.probability (fun e => K.symmetricAccept e (labels (symmetricLeft e)) (labels (symmetricRight e))) = K.assignmentEnergy labels := by classical change _ = K.energy (fun x a => if labels x = a then (1 : ℝ) else 0) rw [K.energy_single_label] simp only [FiniteDistribution.probability, FiniteDistribution.expectation, mul_ite, mul_one, mul_zero] end end UniqueGamesTheorem.Repetition.ProjectionKernel end section /-! Apply finite positive-vector determinization to the actual projection kernel. The target coordinates retain both the right question and the right answer. The selected label may depend on the auxiliary coordinate, but only on its own left question. Every question's squared vector mass is preserved exactly. -/ namespace UniqueGamesTheorem.Repetition.ProjectionKernel open scoped BigOperators noncomputable section attribute [local instance] Classical.propDecidable variable {Q₁ Q₂ A₁ A₂ Ω : Type*} [Fintype Q₁] [Fintype Q₂] [Fintype A₁] [Fintype A₂] [Fintype Ω] /-- Explicit matrix coefficients of the projection operator. -/ def linearCoefficient (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (t : Q₂ × A₂) (x : Q₁) (a : A₁) : ℝ := (K.inner t.1).weight x * (if K.accepts x t.1 a t.2 then 1 else 0) theorem apply_eq_linearCoefficient_sum (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (h : Q₁ → A₁ → ℝ) (y : Q₂) (b : A₂) : K.apply h y b = ∑ x, ∑ a, K.linearCoefficient (y, b) x a * h x a := by unfold apply simp_rw [Finset.mul_sum] apply Finset.sum_congr rfl intro x _ apply Finset.sum_congr rfl intro a _ by_cases ha : K.accepts x y a b = true <;> simp [linearCoefficient, ha] theorem energy_eq_linearCoefficient_sum (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (h : Q₁ → A₁ → ℝ) : K.energy h = ∑ t : Q₂ × A₂, K.outer.weight t.1 * (∑ x, ∑ a, K.linearCoefficient t x a * h x a) ^ 2 := by rw [Fintype.sum_prod_type] simp_rw [← K.apply_eq_linearCoefficient_sum, ← Finset.mul_sum] rfl /-- Scalar kernel determinization preserves the whole mass at every question. -/ theorem exists_energy_le_deterministicVector [Nonempty A₁] (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (h : Q₁ → A₁ → ℝ) (hh : ∀ x a, 0 ≤ h x a) : ∃ labels : Q₁ → A₁, K.energy h ≤ K.energy (deterministicVector h labels) := by classical obtain ⟨labels, _, _, hlabels⟩ := exists_deterministic_vector h hh (fun t : Q₂ × A₂ => K.outer.weight t.1) (fun t => K.outer.nonnegative t.1) K.linearCoefficient refine ⟨labels, ?_⟩ rw [K.energy_eq_linearCoefficient_sum, K.energy_eq_linearCoefficient_sum] exact hlabels /-- The amplitude at a question is the sum of its original label entries. -/ def vectorAmplitude (h : Ω → Q₁ → A₁ → ℝ) (x : Q₁) (ω : Ω) : ℝ := rowMass (h ω) x omit [Fintype Q₁] [Fintype Ω] in theorem vectorAmplitude_nonnegative (h : Ω → Q₁ → A₁ → ℝ) (hh : ∀ ω x a, 0 ≤ h ω x a) (x : Q₁) (ω : Ω) : 0 ≤ vectorAmplitude h x ω := rowMass_nonnegative (h ω) (hh ω) x omit [Fintype Q₁] in @[simp] theorem rowSquareMass_vectorAmplitude (h : Ω → Q₁ → A₁ → ℝ) (x : Q₁) : rowSquareMass (vectorAmplitude h) x = vectorMass h x := rfl /-- Auxiliary coordinates are determinized separately; they need not be independent, normalized, or nonempty. -/ theorem exists_vectorEnergy_le_singleLabelVector [Nonempty A₁] (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (h : Ω → Q₁ → A₁ → ℝ) (hh : ∀ ω x a, 0 ≤ h ω x a) : ∃ labels : Q₁ → Ω → A₁, K.vectorEnergy h ≤ K.vectorEnergy (singleLabelVector labels (vectorAmplitude h)) := by classical have hex (ω : Ω) := K.exists_energy_le_deterministicVector (h ω) (hh ω) let labels (ω : Ω) : Q₁ → A₁ := Classical.choose (hex ω) have hlabels (ω : Ω) : K.energy (h ω) ≤ K.energy (deterministicVector (h ω) (labels ω)) := Classical.choose_spec (hex ω) refine ⟨fun x ω => labels ω x, ?_⟩ apply Finset.sum_le_sum intro ω _ have heq : deterministicVector (h ω) (labels ω) = singleLabelVector (fun x ω => labels ω x) (vectorAmplitude h) ω := by funext x a by_cases ha : a = labels ω x · simp [deterministicVector, singleLabelVector, vectorAmplitude, ha] · simp [deterministicVector, singleLabelVector, ha, Ne.symm ha] exact heq ▸ hlabels ω /-- Package the deterministic labels, amplitudes, exact mass preservation, and energy inequality for use by the finite threshold-rounding construction. -/ theorem exists_mass_preserving_singleLabelVector [Nonempty A₁] (K : ProjectionKernel Q₁ Q₂ A₁ A₂) (h : Ω → Q₁ → A₁ → ℝ) (hh : ∀ ω x a, 0 ≤ h ω x a) : ∃ (labels : Q₁ → Ω → A₁) (f : Q₁ → Ω → ℝ), (∀ x ω, 0 ≤ f x ω) ∧ (∀ x, rowSquareMass f x = vectorMass h x) ∧ K.vectorEnergy h ≤ K.vectorEnergy (singleLabelVector labels f) := by obtain ⟨labels, hlabels⟩ := K.exists_vectorEnergy_le_singleLabelVector h hh exact ⟨labels, vectorAmplitude h, vectorAmplitude_nonnegative h hh, rowSquareMass_vectorAmplitude h, hlabels⟩ end end UniqueGamesTheorem.Repetition.ProjectionKernel end end OAI