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quadratic_neumann_section63_summary_bound_min_dim

Proved

by Harry_Xu · Jul 1, 2026 · Mathlib c5ea003 (Lean v4.30.0)

candes-rechtmatrix-completionquadratic-neumannsection-63

Source: Candès–Recht 2008, Section 6.3, PDF pp. 30--34, the five-way split (6.20) and the summary display on PDF p. 34.

The theorem-regime §6.3 summary estimate for the second Neumann correction, stated at the corrected rectangular five-term scale Φ + t₅ (the sound scale for the first-index-distinct case; the N-only four-term Φ of quadratic_neumann_section63_summary_bound_under_general_sample_bound is too tight for thin matrices because the honest Lemma-6.8 mean cross-term 2(μ₀ r/min)² sends a spectral contribution proportional to the (N/min)-aware fifth term t₅ = √(βlogN)·μ₀²·((N R)/M)^{3/2}·√((N R)/min)).

Assembled from the five index-partition case bounds: the corrected first-index-distinct case at Φ + t₅, and the other four cases (all-equal, middle/last-index-distinct, all-distinct) at the four-term Φ, lifted to Φ + t₅ by monotonicity (t₅ ≥ 0).

Preamble
import Definitions.Def_matrix_completion_neumann
open MatrixCompletion
Formal statement
theorem quadratic_neumann_section63_summary_bound_min_dim :
    ∃ Csec csec : ℝ, 0 < Csec ∧ 0 < csec ∧
      ∀ C' : ℝ, Csec ≤ 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))) →
        bernoulliEventProb ((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ)))
            (fun Omega =>
              NeumannCertificateTermSpectralBound Omega S
                ((m : ℝ) / ((n₁ : ℝ) * (n₂ : ℝ))) 2
                (let N : ℝ := ↑(max n₁ n₂)
                 let R : ℝ := (r : ℝ)
                 let Mobs : ℝ := (m : ℝ)
                 let logN : ℝ := Real.log N
                 Csec *
                   ((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) +
                    Real.sqrt (β * logN) * μ₀ ^ 2 *
                        Real.rpow ((N * R) / Mobs) ((3 : ℝ) / 2) *
                          Real.sqrt ((N * R) / (↑(min n₁ n₂)))))) ≥
          1 - csec * 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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