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quadratic_neumann_last_index_distinct_centered_decoupled_section63_bound_under_general_sample_bound

Proved

by Harry_Xu · Jul 1, 2026 · Mathlib 0df444a (Lean v4.33.1)

candes-rechtmatrix-completionquadratic-neumannsection-63

Source: Candes-Recht 2008, Section 6.3, PDF p. 33, the first subterm in the omega_1 = omega_2 != omega_3 case after equation (6.20).

The paper controls this centered part by first decoupling the two occurrences of the repeated index, then applying Lemma 6.4 and Lemma 6.7 to the resulting two-copy chaos. This theorem is the decoupled two-copy estimate, stated directly at the four-term Section 6.3 summary scale from PDF p. 34.

Preamble
import Definitions.Def_matrix_completion_neumann
open MatrixCompletion
Formal statement
theorem quadratic_neumann_last_index_distinct_centered_decoupled_section63_bound_under_general_sample_bound :
    ∃ Cpair cpair : ℝ, 0 < Cpair ∧ 0 < cpair ∧
      ∀ C' : ℝ, Cpair ≤ C' →
      ∀ (β : ℝ), 2 < β →
      ∀ (n₁ n₂ r m : ℕ) (M : Matrix (Fin n₁) (Fin n₂) ℝ)
        (μ₀ μ₁ : ℝ) (S : SVD M r),
        0 < n₁ → 0 < n₂ → 0 < r → m ≤ n₁ * n₂ →
        1 ≤ μ₀ → 1 ≤ μ₁ →
        A0 S μ₀ → A1 S μ₁ →
        (m : ℝ) ≥
          C' * max (max (μ₁ ^ 2) (Real.sqrt μ₀ * μ₁))
                  (μ₀ * Real.rpow (↑(max n₁ n₂)) ((1 : ℝ) / 4))
            * (↑(max n₁ n₂)) * (r : ℝ) *
              (β * Real.log (↑(max n₁ n₂))) →
        bernoulliPairEventProb ((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ)))
            (fun Omega1 Omega3 =>
              spectralNorm
                (quadraticNeumannLastIndexDistinctCenteredDecoupledContribution
                  Omega1 Omega3 S
                  ((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ)))) ≤
                (let N : ℝ := ↑(max n₁ n₂)
                 let R : ℝ := (r : ℝ)
                 let Mobs : ℝ := (m : ℝ)
                 let logN : ℝ := Real.log N
                 Cpair *
                   ((μ₀ ^ 2 * μ₁) *
                      Real.sqrt ((N * R * (β * logN)) / Mobs) *
                        ((N * R) / Mobs) ^ 2 +
                    μ₀ ^ 2 * ((N * R) / Mobs) ^ 2 +
                    Real.sqrt (β * logN) *
                        Real.rpow ((N * R) / Mobs) ((3 : ℝ) / 2) *
                          (μ₀ ^ 2 * R) +
                    Real.rpow
                      ((μ₀ * μ₁ * N * R * (β * logN)) / Mobs)
                      ((3 : ℝ) / 2)))) ≥
          1 - cpair * Real.rpow (↑(max n₁ n₂)) (-β) := by sorry
Source
Candes, Emmanuel, and Benjamin Recht. "Exact matrix completion via convex optimization." Communications of the ACM 55.6 (2012): 111-119.

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