OAI/Algebra/DepthFive/TraceRank.lean

GitHub source file

6 declarations, 0 contain sorry, 0 declared as axioms

  1. theorem OAI.Problem335.sq_sum_le_support_card_mul_sum_sq line 11

    Source documentation

    Cauchy--Schwarz with only the nonzero summands counted.

    theorem sq_sum_le_support_card_mul_sum_sq {ι : Type*} [Fintype ι]
        (f : ι → ℝ) :
        (∑ i, f i) ^ 2 ≤ (Fintype.card {i // f i ≠ 0} : ℝ) * ∑ i, f i ^ 2 := by
    …
  2. theorem OAI.Problem335.hermitian_trace_sq_eq_sum_eigenvalues_sq line 27

    Source documentation

    The second spectral moment of a Hermitian matrix.

    theorem hermitian_trace_sq_eq_sum_eigenvalues_sq {ι : Type*} [Fintype ι]
        [DecidableEq ι] {A : Matrix ι ι ℂ} (hA : A.IsHermitian) :
        (A ^ 2).trace = ∑ i, ((hA.eigenvalues i : ℂ) ^ 2) := by
    …
  3. theorem OAI.Problem335.hermitian_trace_sq_le_rank_mul_trace_sq line 37

    Source documentation

    The trace-rank bound used in the moment method. Positivity is not needed for this squared formulation: Hermitian symmetry suffices.

    theorem hermitian_trace_sq_le_rank_mul_trace_sq {ι : Type*} [Fintype ι]
        [DecidableEq ι] {A : Matrix ι ι ℂ} (hA : A.IsHermitian) :
        A.trace.re ^ 2 ≤ (A.rank : ℝ) * (A ^ 2).trace.re := by
    …
  4. theorem OAI.Problem335.hermitian_trace_sq_pos line 46

    Source documentation

    A nonzero Hermitian matrix has strictly positive second moment.

    theorem hermitian_trace_sq_pos {ι : Type*} [Fintype ι]
        [DecidableEq ι] {A : Matrix ι ι ℂ} (hA : A.IsHermitian) (hne : A ≠ 0) :
        0 < (A ^ 2).trace.re := by
    …
  5. theorem OAI.Problem335.hermitian_rank_ge_trace_ratio line 58

    Source documentation

    The ratio form of the trace-rank bound.

    theorem hermitian_rank_ge_trace_ratio {ι : Type*} [Fintype ι]
        [DecidableEq ι] {A : Matrix ι ι ℂ} (hA : A.IsHermitian)
        (hsecond : 0 < (A ^ 2).trace.re) :
        A.trace.re ^ 2 / (A ^ 2).trace.re ≤ (A.rank : ℝ) := by
    …
  6. theorem OAI.Problem335.gram_rank_ge_trace_ratio line 67

    Source documentation

    Applied to the Gram matrix, the moment method bounds the rank of the original rectangular matrix.

    theorem gram_rank_ge_trace_ratio {ι κ : Type*} [Fintype ι] [Fintype κ]
        [DecidableEq κ] (A : Matrix ι κ ℂ)
        (hsecond : 0 < ((A.conjTranspose * A) ^ 2).trace.re) :
        (A.conjTranspose * A).trace.re ^ 2 / ((A.conjTranspose * A) ^ 2).trace.re ≤ (A.rank : ℝ) := by
    …