import OAI.GroupTheory.Thompson.FiniteAverage import OAI.GroupTheory.Thompson.HilbertAverage import Mathlib.Algebra.BigOperators.Group.Finset.Piecewise import Mathlib.Tactic.FieldSimp import Mathlib.Tactic.Linarith import Mathlib.Tactic.Ring namespace OAI /-! # Exact finite correlation and variance estimates The diagonal and off-diagonal coefficients are exact finite counts. The mixed sum has one exceptional parent column, hence D nested terms and D(D-1) separated terms. Every count identity permits arbitrary signed coefficients. The final cancellation imposes no positivity assumption on the common correlation alpha. -/ noncomputable section universe uG uE namespace ThompsonNonamenability open scoped BigOperators InnerProductSpace variable {D : ℕ} /-- One distinguished position and all the other positions, with signed values. -/ theorem sum_one_exception (i : Fin D) (b c : ℝ) : (∑ j : Fin D, if j = i then b else c) = b + ((D : ℝ) - 1) * c := by classical have hterm (j : Fin D) : (if j = i then b else c) = c + (if j = i then b - c else 0) := by by_cases h : j = i <;> simp [h] simp_rw [hterm] simp only [Finset.sum_add_distrib, Fintype.sum_ite_eq', Finset.sum_const, Finset.card_univ, Fintype.card_fin, nsmul_eq_mul] ring /-- D diagonal terms and D(D-1) off-diagonal terms, with no sign premise. -/ theorem sum_matrix_le (K : Fin D → Fin D → ℝ) (b c : ℝ) (hdiag : ∀ j, K j j ≤ b) (hoff : ∀ j k, j ≠ k → K j k ≤ c) : (∑ j, ∑ k, K j k) ≤ (D : ℝ) * ((D : ℝ) - 1) * c + (D : ℝ) * b := by classical calc (∑ j, ∑ k, K j k) ≤ ∑ j : Fin D, ∑ k : Fin D, if k = j then b else c := by apply Finset.sum_le_sum intro j _ apply Finset.sum_le_sum intro k _ by_cases h : k = j · subst k simpa using hdiag j · simpa only [ite_eq_right h] using hoff j k (Ne.symm h) _ = (D : ℝ) * ((D : ℝ) - 1) * c + (D : ℝ) * b := by simp_rw [sum_one_exception] simp only [Finset.sum_const, Finset.card_univ, Fintype.card_fin, nsmul_eq_mul] ring /-- The exceptional column contributes D terms, irrespective of the row index. -/ theorem sum_fixed_column_ge (i : Fin D) (K : Fin D → Fin D → ℝ) (b c : ℝ) (hnested : ∀ j, b ≤ K j i) (hsep : ∀ j k, k ≠ i → c ≤ K j k) : (D : ℝ) * ((D : ℝ) - 1) * c + (D : ℝ) * b ≤ ∑ j, ∑ k, K j k := by classical calc (D : ℝ) * ((D : ℝ) - 1) * c + (D : ℝ) * b = ∑ _j : Fin D, ∑ k : Fin D, if k = i then b else c := by simp_rw [sum_one_exception] simp only [Finset.sum_const, Finset.card_univ, Fintype.card_fin, nsmul_eq_mul] ring _ ≤ ∑ j, ∑ k, K j k := by apply Finset.sum_le_sum intro j _ apply Finset.sum_le_sum intro k _ by_cases h : k = i · subst k simpa using hnested j · simpa only [ite_eq_right h] using hsep j k h private theorem normalize_pair_total (hD : 0 < D) (b c : ℝ) : ((D : ℝ)⁻¹)^2 * ((D : ℝ) * ((D : ℝ) - 1) * c + (D : ℝ) * b) = (1 - (D : ℝ)⁻¹) * c + (D : ℝ)⁻¹ * b := by have hd : (D : ℝ) ≠ 0 := ne_of_gt (Nat.cast_pos.mpr hD) field_simp [hd] variable {G : Type uG} {E : Type uE} [NormedAddCommGroup E] [InnerProductSpace ℝ E] /-- The literal finite average of the real inner product. -/ def corr (A : Finset G) (x y : G → E) : ℝ := realAvg A (fun g => ⟪x g, y g⟫_ℝ) theorem corr_comm (A : Finset G) (x y : G → E) : corr A x y = corr A y x := by unfold corr apply realAvg_congr intro g _ exact real_inner_comm (y g) (x g) theorem unit_inner_abs_le (x y : E) (hx : ‖x‖ ≤ 1) (hy : ‖y‖ ≤ 1) : |⟪x, y⟫_ℝ| ≤ 1 := by calc |⟪x, y⟫_ℝ| ≤ ‖x‖ * ‖y‖ := abs_real_inner_le_norm x y _ ≤ 1 * 1 := mul_le_mul hx hy (norm_nonneg y) zero_le_one _ = 1 := by ring theorem corr_abs_le_one (A : Finset G) (hA : A.Nonempty) (x y : G → E) (hx : ∀ g ∈ A, ‖x g‖ ≤ 1) (hy : ∀ g ∈ A, ‖y g‖ ≤ 1) : |corr A x y| ≤ 1 := by unfold corr apply abs_le.mpr constructor · apply const_le_realAvg A hA intro g hg exact (abs_le.mp (unit_inner_abs_le (x g) (y g) (hx g hg) (hy g hg))).1 · apply realAvg_le_const A hA intro g hg exact (abs_le.mp (unit_inner_abs_le (x g) (y g) (hx g hg) (hy g hg))).2 theorem realAvg_norm_finMean_sq (A : Finset G) (x : G → Fin D → E) : realAvg A (fun g => ‖finMean (x g)‖^2) = ((D : ℝ)⁻¹)^2 * ∑ j, ∑ k, corr A (fun g => x g j) (fun g => x g k) := by simp only [norm_finMean_sq, realAvg_const_mul, realAvg_sum_univ, corr] theorem corr_finMean (A : Finset G) (x y : G → Fin D → E) : corr A (fun g => finMean (x g)) (fun g => finMean (y g)) = ((D : ℝ)⁻¹)^2 * ∑ j, ∑ k, corr A (fun g => x g j) (fun g => y g k) := by simp only [corr, inner_finMean, pow_two, realAvg_const_mul, realAvg_sum_univ] theorem realAvg_norm_sub_sq (A : Finset G) (x y : G → E) : realAvg A (fun g => ‖x g - y g‖^2) = realAvg A (fun g => ‖x g‖^2) - 2 * corr A x y + realAvg A (fun g => ‖y g‖^2) := by simp only [norm_sub_sq_real, realAvg_add, realAvg_sub, realAvg_const_mul, corr] /-- Parent or sibling averages: the same exact diagonal count applies to both. -/ theorem realAvg_norm_finMean_sq_le (A : Finset G) (hA : A.Nonempty) (hD : 0 < D) (x : G → Fin D → E) (c : ℝ) (hx : ∀ g ∈ A, ∀ j, ‖x g j‖ ≤ 1) (hsep : ∀ j k, j ≠ k → corr A (fun g => x g j) (fun g => x g k) ≤ c) : realAvg A (fun g => ‖finMean (x g)‖^2) ≤ (1 - (D : ℝ)⁻¹) * c + (D : ℝ)⁻¹ := by rw [realAvg_norm_finMean_sq] have hdiag (j : Fin D) : corr A (fun g => x g j) (fun g => x g j) ≤ 1 := (abs_le.mp (corr_abs_le_one A hA _ _ (fun g hg => hx g hg j) (fun g hg => hx g hg j))).2 calc ((D : ℝ)⁻¹)^2 * ∑ j, ∑ k, corr A (fun g => x g j) (fun g => x g k) ≤ ((D : ℝ)⁻¹)^2 * ((D : ℝ) * ((D : ℝ) - 1) * c + (D : ℝ) * 1) := mul_le_mul_of_nonneg_left (sum_matrix_le _ 1 c hdiag hsep) (sq_nonneg _) _ = (1 - (D : ℝ)⁻¹) * c + (D : ℝ)⁻¹ := by simpa only [mul_one] using normalize_pair_total hD 1 c /-- Only the designated parent column is uncontrolled in a mixed sum. -/ theorem corr_finMean_ge (A : Finset G) (hA : A.Nonempty) (hD : 0 < D) (i : Fin D) (z x : G → Fin D → E) (c : ℝ) (hz : ∀ g ∈ A, ∀ j, ‖z g j‖ ≤ 1) (hx : ∀ g ∈ A, ∀ k, ‖x g k‖ ≤ 1) (hsep : ∀ j k, k ≠ i → c ≤ corr A (fun g => z g j) (fun g => x g k)) : (1 - (D : ℝ)⁻¹) * c - (D : ℝ)⁻¹ ≤ corr A (fun g => finMean (z g)) (fun g => finMean (x g)) := by have hnested (j : Fin D) : -1 ≤ corr A (fun g => z g j) (fun g => x g i) := (abs_le.mp (corr_abs_le_one A hA _ _ (fun g hg => hz g hg j) (fun g hg => hx g hg i))).1 calc (1 - (D : ℝ)⁻¹) * c - (D : ℝ)⁻¹ = ((D : ℝ)⁻¹)^2 * ((D : ℝ) * ((D : ℝ) - 1) * c + (D : ℝ) * (-1)) := by rw [normalize_pair_total hD] ring _ ≤ ((D : ℝ)⁻¹)^2 * ∑ j, ∑ k, corr A (fun g => z g j) (fun g => x g k) := mul_le_mul_of_nonneg_left (sum_fixed_column_ge i _ (-1) c hnested hsep) (sq_nonneg _) _ = corr A (fun g => finMean (z g)) (fun g => finMean (x g)) := (corr_finMean A z x).symm /-- The finite Hilbert variance bound with exact cancellation of signed alpha. -/ theorem finite_variance_bound (A : Finset G) (hA : A.Nonempty) (hD : 0 < D) (x : G → Fin D → E) (y : G → Fin D → Fin D → E) (α η : ℝ) (hx : ∀ g ∈ A, ∀ k, ‖x g k‖ ≤ 1) (hy : ∀ g ∈ A, ∀ i j, ‖y g i j‖ ≤ 1) (hparent : ∀ j k, j ≠ k → |corr A (fun g => x g j) (fun g => x g k) - α| ≤ η) (hchild : ∀ i j k, j ≠ k → |corr A (fun g => y g i j) (fun g => y g i k) - α| ≤ η) (hmixed : ∀ i j k, k ≠ i → |corr A (fun g => y g i j) (fun g => x g k) - α| ≤ η) : ∀ i, realAvg A (fun g => ‖finMean (y g i) - finMean (x g)‖^2) ≤ 4 / (D : ℝ) + 4 * (1 - 1 / (D : ℝ)) * η := by intro i have hp := realAvg_norm_finMean_sq_le A hA hD x (α + η) hx (by intro j k hjk have h := (abs_le.mp (hparent j k hjk)).2 linarith) have hq := realAvg_norm_finMean_sq_le A hA hD (fun g => y g i) (α + η) (fun g hg => hy g hg i) (by intro j k hjk have h := (abs_le.mp (hchild i j k hjk)).2 linarith) have hm := corr_finMean_ge A hA hD i (fun g => y g i) x (α - η) (fun g hg => hy g hg i) hx (by intro j k hki have h := (abs_le.mp (hmixed i j k hki)).1 linarith) rw [realAvg_norm_sub_sq] calc realAvg A (fun g => ‖finMean (y g i)‖^2) - 2 * corr A (fun g => finMean (y g i)) (fun g => finMean (x g)) + realAvg A (fun g => ‖finMean (x g)‖^2) ≤ ((1 - (D : ℝ)⁻¹) * (α + η) + (D : ℝ)⁻¹) - 2 * ((1 - (D : ℝ)⁻¹) * (α - η) - (D : ℝ)⁻¹) + ((1 - (D : ℝ)⁻¹) * (α + η) + (D : ℝ)⁻¹) := by linarith only [hp, hq, hm] _ = 4 / (D : ℝ) + 4 * (1 - 1 / (D : ℝ)) * η := by simp only [div_eq_mul_inv, one_mul] ring end ThompsonNonamenability end end OAI