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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
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