import Mathlib import OAI.Computability.MaxCut.Games.Deletion import OAI.Computability.MaxCut.PCP.MatrixParity import OAI.Computability.MaxCut.Games.MatrixFourier namespace OAI /-! Fourier expansion of actual affine restrictions and parity extraction. -/ noncomputable section namespace MaxCutGames.Fourier.MatrixParityRow open MatrixCharacters MatrixFourier MatrixParity open scoped BigOperators Classical variable {E C V : Type*} [AddCommGroup E] [Module F2 E] [AddCommGroup C] [Module F2 C] [AddCommGroup V] [Module F2 V] [FiniteDimensional F2 E] [FiniteDimensional F2 C] [FiniteDimensional F2 V] [Fintype (E →ₗ[F2] C)] [Fintype (C →ₗ[F2] E)] [Fintype (V →ₗ[F2] C)] omit [FiniteDimensional F2 E] [FiniteDimensional F2 C] [FiniteDimensional F2 V] [Fintype (E →ₗ[F2] C)] [Fintype (C →ₗ[F2] E)] [Fintype (V →ₗ[F2] C)] in theorem traceCharacter_comp (Q : E →ₗ[F2] V) (A : V →ₗ[F2] C) (T : C →ₗ[F2] E) : linearTraceCharacter T (A.comp Q) = linearTraceCharacter (Q.comp T) A := by simp only [linearTraceCharacter_apply, linearTracePair, LinearMap.comp_assoc] omit [FiniteDimensional F2 E] [FiniteDimensional F2 C] [Fintype (E →ₗ[F2] C)] [Fintype (C →ₗ[F2] E)] in theorem traceCharacter_re_add (T : C →ₗ[F2] E) (X Y : E →ₗ[F2] C) : (linearTraceCharacter T (X + Y)).re = (linearTraceCharacter T X).re * (linearTraceCharacter T Y).re := by rw [AddChar.map_add_eq_mul, Complex.mul_re] simp [linearTraceCharacter_apply, binarySign_im] omit [FiniteDimensional F2 E] [Fintype (E →ₗ[F2] C)] [Fintype (C →ₗ[F2] E)] in /-- Characters restricted to the row vanish unless the dual map lands in the kernel of `Q`. For `Q = W.mkQ` this is precisely `range T ≤ W`. -/ theorem row_character_average (Q : E →ₗ[F2] V) (T : C →ₗ[F2] E) : (𝔼 A : V →ₗ[F2] C, (linearTraceCharacter T (A.comp Q)).re) = if Q.comp T = 0 then 1 else 0 := by have hcomplex : (𝔼 A : V →ₗ[F2] C, linearTraceCharacter T (A.comp Q)) = if Q.comp T = 0 then 1 else 0 := by simp only [traceCharacter_comp, Fintype.expect_eq_sum_div_card, sum_linearTraceCharacter] split <;> simp [Fintype.card_ne_zero] have h := congrArg Complex.re hcomplex simpa only [Complex.re_expect, apply_ite, Complex.one_re, Complex.zero_re] using h omit [FiniteDimensional F2 E] [Fintype (E →ₗ[F2] C)] in /-- Averaging a finite trace-character expansion on an actual affine row. -/ theorem row_spectral_average (Q : E →ₗ[F2] V) (X₀ : E →ₗ[F2] C) (a : (C →ₗ[F2] E) → ℝ) : (𝔼 A : V →ₗ[F2] C, ∑ T : C →ₗ[F2] E, a T * (linearTraceCharacter T (X₀ + A.comp Q)).re) = ∑ T : C →ₗ[F2] E, if Q.comp T = 0 then a T * (linearTraceCharacter T X₀).re else 0 := by rw [Finset.expect_sum_comm] apply Finset.sum_congr rfl intro T _ simp only [traceCharacter_re_add, ← mul_assoc] rw [← Finset.mul_expect, row_character_average] split <;> simp /-- Equation (5.18), with the primal row parametrized by actual quotient maps. -/ theorem row_fourier_average (Q : E →ₗ[F2] V) (X₀ : E →ₗ[F2] C) (g : (E →ₗ[F2] C) → ℝ) : (𝔼 A : V →ₗ[F2] C, g (X₀ + A.comp Q)) = ∑ T : C →ₗ[F2] E, if Q.comp T = 0 then linearCoeff g T * (linearTraceCharacter T X₀).re else 0 := by rw [← row_spectral_average] apply Finset.expect_congr rfl intro A _ exact (linear_fourier_inversion g _).symm omit [FiniteDimensional F2 E] [Fintype (E →ₗ[F2] C)] [Fintype (C →ₗ[F2] E)] in theorem shift_character_average [Fintype C] (τ : E →ₗ[F2] F2) (T : C →ₗ[F2] E) : (𝔼 c : C, (linearTraceCharacter T (τ.smulRight c)).re) = if τ.comp T = 0 then 1 else 0 := by have hc := linearTrace_shift_average τ T rw [← Fintype.expect_eq_sum_div_card] at hc have hr := congrArg Complex.re hc simpa only [Complex.re_expect, apply_ite, Complex.one_re, Complex.zero_re] using hr /-- The folding average is the Fourier projection onto parity-zero frequencies. -/ theorem shift_fourier_average [Fintype C] (τ : E →ₗ[F2] F2) (X : E →ₗ[F2] C) (g : (E →ₗ[F2] C) → ℝ) : (𝔼 c : C, g (X + τ.smulRight c)) = ∑ T : C →ₗ[F2] E, (if τ.comp T = 0 then linearCoeff g T else 0) * (linearTraceCharacter T X).re := by calc _ = 𝔼 c : C, ∑ T : C →ₗ[F2] E, linearCoeff g T * (linearTraceCharacter T (X + τ.smulRight c)).re := by apply Finset.expect_congr rfl intro c _ exact (linear_fourier_inversion g _).symm _ = _ := by rw [Finset.expect_sum_comm] apply Finset.sum_congr rfl intro T _ simp only [traceCharacter_re_add, ← mul_assoc] rw [← Finset.mul_expect, shift_character_average] split <;> simp /-- The parity-zero row subtotal equals the row average of the folded average. -/ theorem row_shift_fourier_average [Fintype C] (Q : E →ₗ[F2] V) (τ : E →ₗ[F2] F2) (X₀ : E →ₗ[F2] C) (g : (E →ₗ[F2] C) → ℝ) : (𝔼 A : V →ₗ[F2] C, 𝔼 c : C, g (X₀ + A.comp Q + τ.smulRight c)) = ∑ T : C →ₗ[F2] E, if Q.comp T = 0 ∧ τ.comp T = 0 then linearCoeff g T * (linearTraceCharacter T X₀).re else 0 := by simp only [shift_fourier_average] rw [row_spectral_average] apply Finset.sum_congr rfl intro T _ split_ifs <;> simp_all omit [FiniteDimensional F2 E] [FiniteDimensional F2 C] [Fintype (E →ₗ[F2] C)] [Fintype (C →ₗ[F2] E)] in theorem signed_coefficient_le_abs (a : ℝ) (T : C →ₗ[F2] E) (X : E →ₗ[F2] C) : a * (linearTraceCharacter T X).re ≤ |a| := by rcases Integration.BinaryLinear.scalar_cases (linearTracePair X T) with h | h · simpa [linearTraceCharacter_apply, h] using le_abs_self a · simpa [linearTraceCharacter_apply, h] using neg_le_abs a /-- Actual coefficient extraction from a dense affine row and a uniformly small folding average. The row frequency count is an explicit finite cardinal bound; the quotient/subspace specialization supplies it by counting maps into `W`. -/ theorem coefficient_of_dense_row [Fintype C] (Q : E →ₗ[F2] V) (τ : E →ₗ[F2] F2) (X₀ : E →ₗ[F2] C) (g : (E →ₗ[F2] C) → ℝ) (ρ : ℝ) (N : Nat) (ρ_pos : 0 < ρ) (N_pos : 0 < N) (row_count : (Finset.univ.filter fun T : C →ₗ[F2] E => Q.comp T = 0).card ≤ N) (dense : ρ < 𝔼 A : V →ₗ[F2] C, g (X₀ + A.comp Q)) (shift_bound : ∀ X, (𝔼 c : C, g (X + τ.smulRight c)) ≤ ρ / 2) : ∃ T : C →ₗ[F2] E, Q.comp T = 0 ∧ τ.comp T ≠ 0 ∧ ρ / (2 * (N : ℝ)) < |linearCoeff g T| := by classical let row : Finset (C →ₗ[F2] E) := Finset.univ.filter fun T => Q.comp T = 0 let term (T : C →ₗ[F2] E) := linearCoeff g T * (linearTraceCharacter T X₀).re let β : ℝ := (ρ / 2) / (N : ℝ) have hN : (0 : ℝ) < (N : ℝ) := Nat.cast_pos.mpr N_pos have hβ : 0 ≤ β := le_of_lt (div_pos (div_pos ρ_pos zero_lt_two) hN) have hbudget : (N : ℝ) * β = ρ / 2 := by dsimp [β] rw [mul_comm, div_mul_cancel₀ _ (ne_of_gt hN)] have htotal : ρ < ∑ T : C →ₗ[F2] E, if Q.comp T = 0 then term T else 0 := by rw [row_fourier_average] at dense convert dense using 1 congr 1 funext T split_ifs <;> rfl have hzero : (∑ T : C →ₗ[F2] E, if Q.comp T = 0 ∧ τ.comp T = 0 then term T else 0) ≤ ρ / 2 := by change (∑ T : C →ₗ[F2] E, if Q.comp T = 0 ∧ τ.comp T = 0 then linearCoeff g T * (linearTraceCharacter T X₀).re else 0) ≤ _ rw [← row_shift_fourier_average] apply Finset.expect_le Finset.univ_nonempty intro A _ exact shift_bound (X₀ + A.comp Q) have hsplit : (∑ T : C →ₗ[F2] E, if Q.comp T = 0 then term T else 0) = (∑ T : C →ₗ[F2] E, if Q.comp T = 0 ∧ τ.comp T = 0 then term T else 0) + ∑ T ∈ row, if τ.comp T = 0 then 0 else term T := by simp only [row, Finset.sum_filter] rw [← Finset.sum_add_distrib] apply Finset.sum_congr rfl intro T _ split_ifs <;> simp_all have hnonzero : ρ / 2 < ∑ T ∈ row, if τ.comp T = 0 then 0 else term T := by linarith by_contra hnone have hsmall : ∀ T ∈ row, (if τ.comp T = 0 then 0 else term T) ≤ β := by intro T hT split_ifs with hτ · exact hβ · have hQ : Q.comp T = 0 := (Finset.mem_filter.mp hT).2 have hc : |linearCoeff g T| ≤ β := by by_contra hc apply hnone refine ⟨T, hQ, hτ, ?_⟩ have hlarge : β < |linearCoeff g T| := lt_of_not_ge hc simpa only [β, div_div] using hlarge exact (signed_coefficient_le_abs (linearCoeff g T) T X₀).trans hc have hsum := Finset.sum_le_sum hsmall have hcard : (row.card : ℝ) ≤ (N : ℝ) := by exact_mod_cast row_count have hcount := mul_le_mul_of_nonneg_right hcard hβ have hsum' : (∑ T ∈ row, if τ.comp T = 0 then 0 else term T) ≤ (row.card : ℝ) * β := by simpa only [Finset.sum_const, nsmul_eq_mul] using hsum linarith /-- Dense-row extraction for a genuinely folded color map. The zero-parity subtotal bound follows from folding, rather than being supplied as a hypothesis. -/ theorem coefficient_of_folded_dense_row [Fintype C] {D : Type*} [AddCommGroup D] [Module F2 D] (Q : E →ₗ[F2] V) (τ : E →ₗ[F2] F2) (X₀ : E →ₗ[F2] C) (inclusion : C →ₗ[F2] D) (inclusion_injective : Function.Injective inclusion) (F : (E →ₗ[F2] C) → D) (folded : ∀ X c, F (X + τ.smulRight c) = F X + inclusion c) (y : D) (ρ : ℝ) (N : Nat) (ρ_pos : 0 < ρ) (N_pos : 0 < N) (color_bound : 1 / (Fintype.card C : ℝ) ≤ ρ / 2) (row_count : (Finset.univ.filter fun T : C →ₗ[F2] E => Q.comp T = 0).card ≤ N) (dense : ρ < 𝔼 A : V →ₗ[F2] C, if F (X₀ + A.comp Q) = y then (1 : ℝ) else 0) : ∃ T : C →ₗ[F2] E, Q.comp T = 0 ∧ τ.comp T ≠ 0 ∧ ρ / (2 * (N : ℝ)) < |linearCoeff (fun X => if F X = y then 1 else 0) T| := by apply coefficient_of_dense_row Q τ X₀ (fun X => if F X = y then 1 else 0) ρ N ρ_pos N_pos row_count dense intro X rw [Fintype.expect_eq_sum_div_card] exact (folded_indicator_average_le τ inclusion inclusion_injective F folded X y).trans color_bound lemma color_card_bound [Fintype C] (r s : Nat) (ρ : ℝ) (hρ : ρ = 2 / (2 : ℝ) ^ (s - r)) (hdim : s - r ≤ Module.finrank F2 C) : 1 / (Fintype.card C : ℝ) ≤ ρ / 2 := by have hcard : Fintype.card C = 2 ^ Module.finrank F2 C := by simpa [F2, ZMod.card] using Module.card_fintype (Module.finBasis F2 C) have hleNat : 2 ^ (s - r) ≤ Fintype.card C := by rw [hcard] exact Nat.pow_le_pow_right (by decide : 0 < 2) hdim have hle : (2 : ℝ) ^ (s - r) ≤ (Fintype.card C : ℝ) := by exact_mod_cast hleNat calc 1 / (Fintype.card C : ℝ) ≤ 1 / (2 : ℝ) ^ (s - r) := one_div_le_one_div_of_le (pow_pos zero_lt_two _) hle _ = ρ / 2 := by rw [hρ]; ring omit [FiniteDimensional F2 E] [FiniteDimensional F2 C] [Fintype (E →ₗ[F2] C)] [Fintype (C →ₗ[F2] E)] in lemma fixed_row_folded {R D : Type*} [AddCommGroup R] [Module F2 R] [AddCommGroup D] [Module F2 D] (τ : E →ₗ[F2] F2) (questionInclusion : C →ₗ[F2] R) (colorInclusion : C →ₗ[F2] D) (FU : (E →ₗ[F2] R) → D) (Z : E →ₗ[F2] R) (folded : ∀ Y c, FU (Y + τ.smulRight (questionInclusion c)) = FU Y + colorInclusion c) : ∀ X c, FU (Z + questionInclusion.comp (X + τ.smulRight c)) = FU (Z + questionInclusion.comp X) + colorInclusion c := by intro X c have hshift : questionInclusion.comp (τ.smulRight c) = τ.smulRight (questionInclusion c) := by ext e simp [LinearMap.smulRight_apply] rw [LinearMap.comp_add, hshift, ← add_assoc, folded] /-- Lemma 5.3 on an actual quotient-parametrized dense row. The density parameter is stated as a ratio of natural powers, avoiding truncated negative exponents. -/ theorem lemma53_quotient [Fintype C] {D : Type*} [AddCommGroup D] [Module F2 D] (W : Submodule F2 E) [Fintype ((E ⧸ W) →ₗ[F2] C)] [Fintype (C →ₗ[F2] W)] (τ : E →ₗ[F2] F2) (X₀ : E →ₗ[F2] C) (inclusion : C →ₗ[F2] D) (inclusion_injective : Function.Injective inclusion) (F : (E →ₗ[F2] C) → D) (folded : ∀ X c, F (X + τ.smulRight c) = F X + inclusion c) (y : D) (r s : Nat) (ρ : ℝ) (hρ : ρ = 2 / (2 : ℝ) ^ (s - r)) (hW : Module.finrank F2 W ≤ r) (hC : Module.finrank F2 C ≤ s) (hdim : s - r ≤ Module.finrank F2 C) (dense : ρ < 𝔼 A : (E ⧸ W) →ₗ[F2] C, if F (X₀ + A.comp W.mkQ) = y then (1 : ℝ) else 0) : ∃ T : C →ₗ[F2] E, τ.comp T ≠ 0 ∧ ρ / (2 * ((2 ^ (r * s) : Nat) : ℝ)) < |linearCoeff (fun X => if F X = y then 1 else 0) T| := by have hρpos : 0 < ρ := by rw [hρ] exact div_pos zero_lt_two (pow_pos zero_lt_two _) have hcount : (Finset.univ.filter fun T : C →ₗ[F2] E => W.mkQ.comp T = 0).card ≤ 2 ^ (r * s) := by have hcard := MatrixRestrictions.quotientKernel_filter_card (C := C) W have heq : (Finset.univ.filter fun T : C →ₗ[F2] E => W.mkQ.comp T = 0).card = Fintype.card (C →ₗ[F2] W) := by convert hcard using 1 congr 1 ext T simp rw [heq] exact MatrixParity.card_linearMaps_le (E := W) (C := C) r s hW hC obtain ⟨T, _, hτ, hβ⟩ := coefficient_of_folded_dense_row W.mkQ τ X₀ inclusion inclusion_injective F folded y ρ (2 ^ (r * s)) hρpos (Nat.two_pow_pos _) (color_card_bound r s ρ hρ hdim) hcount dense exact ⟨T, hτ, hβ⟩ end MaxCutGames.Fourier.MatrixParityRow end end OAI