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import OAI.Computability.PerfectCompleteness.Algebra.AffineLinearHeavyWitness
import OAI.Computability.PerfectCompleteness.Algebra.BilinearGramCompressionLemmas
import OAI.Computability.PerfectCompleteness.Algebra.TensorBucketEvaluationLemmas
import OAI.Computability.PerfectCompleteness.Algebra.TensorSliceDimension
import OAI.Computability.PerfectCompleteness.Foundations.OutputAnnihilator
import OAI.Computability.PerfectCompleteness.Sampling.OwnLawHeavyList
namespace OAI
section
namespace PerfectCompleteness.TensorAffineHeavyWitness
open scoped TensorProduct Classical
open QuarterBalance (F2)
open UniqueGamesTheorem.Foundations.Games
noncomputable section
variable {ℓ : Nat} {H : Type*} [AddCommGroup H] [Module F2 H]
[Finite H] [FiniteDimensional F2 H]
local instance dualFintype {V : Type*} [AddCommGroup V] [Module F2 V] [Fintype V] :
Fintype (Module.Dual F2 V) :=
Fintype.ofInjective (fun f : Module.Dual F2 V => (f : V → F2)) DFunLike.coe_injective
def heavyList (W : Submodule F2 (Fin ℓ → F2))
(μ : FiniteDistribution (W ⊗[F2] H)) (G : (W ⊗[F2] H) → (Fin ℓ → F2))
(τ : ℝ) (σ : Module.Dual F2 (Fin ℓ → F2)) :
Finset (Module.Dual F2 (W ⊗[F2] H)) :=
OwnLawHeavyList.heavyList μ (fun X => QuarterBalance.sign (σ (G X))) τ
omit [FiniteDimensional F2 H] in
theorem heavyList_card_le (W : Submodule F2 (Fin ℓ → F2))
(μ : FiniteDistribution (W ⊗[F2] H)) (G : (W ⊗[F2] H) → (Fin ℓ → F2))
(τ biasBound : ℝ) (hτ : 0 < τ) (hbiasBound : 0 ≤ biasBound) (hsmall : biasBound ≤ τ ^ 2 / 2)
(hbias : ∀ Φ : Module.Dual F2 (W ⊗[F2] H), Φ ≠ 0 →
|μ.expectation (fun X => QuarterBalance.sign (Φ X))| ≤ biasBound)
(σ : Module.Dual F2 (Fin ℓ → F2)) :
((heavyList W μ G τ σ).card : ℝ) ≤ 2 / τ ^ 2 := by
apply OwnLawHeavyList.heavyList_card_le μ _ τ biasBound hτ hbiasBound hsmall
· intro X
exact (OwnLawHeavyList.character_sq σ (G X)).le
· exact hbias
def conditionalMatch (W : Submodule F2 (Fin ℓ → F2))
(μ : FiniteDistribution (W ⊗[F2] H)) (G : (W ⊗[F2] H) → (Fin ℓ → F2))
(Q : Submodule F2 (Module.Dual F2 H)) (target : Q →ₗ[F2] W)
(z : Module.Dual F2 H) (offset : Fin ℓ → F2) : ℝ :=
AffineLinearHeavyWitness.conditionalMatch μ (TensorRestriction.restrictionMap Q)
target G (TensorBucketEvaluation.tensorOutputLinear W z) offset
theorem exists_heavy_candidate (W : Submodule F2 (Fin ℓ → F2))
(μ : FiniteDistribution (W ⊗[F2] H)) (G : (W ⊗[F2] H) → (Fin ℓ → F2))
(ρ h₀ biasBound : ℝ) (hρ : 0 < ρ) (hh₀ : 0 < h₀) (hbiasBound : 0 ≤ biasBound)
(hsmall : biasBound ≤ h₀ / 2)
(hbias : ∀ Φ : Module.Dual F2 (W ⊗[F2] H), Φ ≠ 0 →
|μ.expectation (fun X => QuarterBalance.sign (Φ X))| ≤ biasBound)
(hexcluded : 1 / (2 : ℝ) ^ Module.finrank F2 W < ρ / 8)
(Q : Submodule F2 (Module.Dual F2 H))
(hsize : h₀ ≤ 1 / (2 : ℝ) ^ Module.finrank F2 (Q →ₗ[F2] W))
(target : Q →ₗ[F2] W) (z : Module.Dual F2 H) (offset : Fin ℓ → F2)
(hmatch : ρ ≤ conditionalMatch W μ G Q target z offset) :
∃ σ : Module.Dual F2 (Fin ℓ → F2), σ.comp W.subtype ≠ 0 ∧
∃ Φ ∈ heavyList W μ G (ρ * h₀ / 4) σ,
∀ w : W, σ w = 1 → TensorCosetEvaluation.scalarRestriction Φ w - z ∈ Q := by
let : Module.Free F2 (Q →ₗ[F2] W) := Module.Free.of_divisionRing F2 (Q →ₗ[F2] W)
let : Fintype (Module.Dual F2 (W ⊗[F2] H)) :=
Fintype.ofInjective (fun functional : Module.Dual F2 (W ⊗[F2] H) =>
(functional : (W ⊗[F2] H) → F2)) DFunLike.coe_injective
let b := Module.finBasis F2 (Q →ₗ[F2] W)
let c := Module.finBasis F2 (Fin ℓ → F2)
have hsize' : h₀ ≤ 1 / (Fintype.card
(Fin (Module.finrank F2 (Q →ₗ[F2] W)) → Bool) : ℝ) := by
simpa only [Fintype.card_fun, Fintype.card_bool, Fintype.card_fin,
Nat.cast_pow, Nat.cast_ofNat] using hsize
have hbad : ((OutputAnnihilator.bad W).card : ℝ) /
Fintype.card (Module.Dual F2 (Fin ℓ → F2)) < ρ / 8 := by
rw [OutputAnnihilator.bad_fraction]
exact hexcluded
unfold conditionalMatch at hmatch
have candidateBasis :=
AffineLinearHeavyWitness.exists_heavy_in_dual_coset
(U := W ⊗[F2] H) (V := Q →ₗ[F2] W) (K := Fin ℓ → F2) μ b c
have candidateRestriction := candidateBasis
(TensorRestriction.restrictionMap Q)
(TensorRestriction.restrictionMap_surjective (W := W) Q)
have candidateData := candidateRestriction
target G (TensorBucketEvaluation.tensorOutputLinear W z) offset
(OutputAnnihilator.bad W) ρ h₀ biasBound
have candidateBounds := candidateData hρ hh₀ hsize' hbiasBound hsmall hbias hbad
have candidateWitness := candidateBounds hmatch
obtain ⟨σ, hσ, ψ, hψ, hheavy⟩ := candidateWitness
refine ⟨σ, (OutputAnnihilator.not_mem_bad_iff W σ).mp hσ,
σ.comp (TensorBucketEvaluation.tensorOutputLinear W z) + ψ, ?_, ?_⟩
· simp only [heavyList, OwnLawHeavyList.heavyList, SmallBias.heavySet,
Finset.mem_filter, Finset.mem_univ, true_and] at hheavy ⊢
simpa only [OwnLawHeavyList.character, BinaryDualCoordinates.character] using hheavy
· intro w hw
have hψ' : TensorCosetEvaluation.scalarRestriction ψ w ∈ Q :=
TensorCosetEvaluation.scalarRestriction_mem_of_vanishes Q ψ
(TensorRestriction.dualImage_vanishes Q ψ hψ) w
rw [TensorTargetCharacter.comp_tensorOutputLinear,
TensorCosetEvaluation.scalarRestriction_add,
TensorCosetEvaluation.scalarRestriction_pure]
have hw' : (σ.comp W.subtype) w = 1 := hw
rw [hw', one_smul, add_sub_cancel_left]
exact hψ'
theorem lemma53 (W : Submodule F2 (Fin ℓ → F2))
(μ : FiniteDistribution (W ⊗[F2] H)) (G : (W ⊗[F2] H) → (Fin ℓ → F2))
(r : Nat) (hcodim : Module.finrank F2 ((Fin ℓ → F2) ⧸ W) ≤ r)
(ρ biasBound : ℝ) (hρ : 0 < ρ) (hbiasBound : 0 ≤ biasBound)
(hgap : 1 / (2 : ℝ) ^ (ℓ - r) < ρ / 8)
(hsmall : biasBound ≤ min ((1 / (2 : ℝ) ^ (r * ℓ)) / 2)
((ρ * (1 / (2 : ℝ) ^ (r * ℓ)) / 4) ^ 2 / 2))
(hbias : ∀ Φ : Module.Dual F2 (W ⊗[F2] H), Φ ≠ 0 →
|μ.expectation (fun X => QuarterBalance.sign (Φ X))| ≤ biasBound) :
(∀ σ : Module.Dual F2 (Fin ℓ → F2),
((heavyList W μ G (ρ * (1 / (2 : ℝ) ^ (r * ℓ)) / 4) σ).card : ℝ) ≤
2 / (ρ * (1 / (2 : ℝ) ^ (r * ℓ)) / 4) ^ 2) ∧
∀ (Q : Submodule F2 (Module.Dual F2 H)), Module.finrank F2 Q ≤ r →
∀ (target : Q →ₗ[F2] W) (z : Module.Dual F2 H) (offset : Fin ℓ → F2),
ρ ≤ conditionalMatch W μ G Q target z offset →
∃ σ : Module.Dual F2 (Fin ℓ → F2), σ.comp W.subtype ≠ 0 ∧
∃ Φ ∈ heavyList W μ G (ρ * (1 / (2 : ℝ) ^ (r * ℓ)) / 4) σ,
∀ w : W, σ w = 1 →
TensorCosetEvaluation.scalarRestriction Φ w - z ∈ Q := by
have hh₀ : 0 < 1 / (2 : ℝ) ^ (r * ℓ) := by positivity
have hτ : 0 < ρ * (1 / (2 : ℝ) ^ (r * ℓ)) / 4 := by positivity
have hsmall' := le_min_iff.mp hsmall
constructor
· intro σ
exact heavyList_card_le W μ G _ biasBound hτ hbiasBound hsmall'.2 hbias σ
· intro Q hQ target z offset hmatch
have hexcluded : 1 / (2 : ℝ) ^ Module.finrank F2 W < ρ / 8 := by
rw [← OutputAnnihilator.bad_fraction W]
apply OutputAnnihilator.bad_fraction_lt_of_codim_le W r ρ hcodim
simpa only [Module.finrank_fin_fun] using hgap
have hsize : 1 / (2 : ℝ) ^ (r * ℓ) ≤
1 / (2 : ℝ) ^ Module.finrank F2 (Q →ₗ[F2] W) := by
simpa only [TensorSliceDimension.mask_card, Nat.cast_pow, Nat.cast_ofNat] using
TensorSliceDimension.reciprocal_equation_mask_card_ge W Q hQ
exact exists_heavy_candidate W μ G ρ _ biasBound hρ hh₀ hbiasBound hsmall'.1 hbias hexcluded
Q hsize target z offset hmatch
end
end PerfectCompleteness.TensorAffineHeavyWitness
end
end OAI