Plain-language statement
If the kernels of the components are contained, then the kernel of the Kronecker product is contained.
Exact Lean statement
lemma ker_kron_le_of_le {d₁ d₂ : Type*} [Fintype d₁] [Fintype d₂] [DecidableEq d₁] [DecidableEq d₂]
(A C : Matrix d₁ d₁ ℂ) (B D : Matrix d₂ d₂ ℂ)
(hA : LinearMap.ker A.toEuclideanLin ≤ LinearMap.ker C.toEuclideanLin)
(hB : LinearMap.ker B.toEuclideanLin ≤ LinearMap.ker D.toEuclideanLin) :
LinearMap.ker (A.kronecker B).toEuclideanLin ≤ LinearMap.ker (C.kronecker D).toEuclideanLinFormal artifact
Lean source
lemma ker_kron_le_of_le {d₁ d₂ : Type*} [Fintype d₁] [Fintype d₂] [DecidableEq d₁] [DecidableEq d₂] (A C : Matrix d₁ d₁ ℂ) (B D : Matrix d₂ d₂ ℂ) (hA : LinearMap.ker A.toEuclideanLin ≤ LinearMap.ker C.toEuclideanLin) (hB : LinearMap.ker B.toEuclideanLin ≤ LinearMap.ker D.toEuclideanLin) : LinearMap.ker (A.kronecker B).toEuclideanLin ≤ LinearMap.ker (C.kronecker D).toEuclideanLin := by intro x hx simp only [Matrix.kronecker, LinearMap.mem_ker, Matrix.toLpLin_apply, WithLp.toLp_eq_zero] at hx ⊢ -- By definition of Kronecker product, we know that $(A \otimes B)x = 0$ if and only if for all $i$ and $j$, $\sum_{k,l} A_{ik} B_{jl} x_{kl} = 0$. have h_kronecker : ∀ i j, ∑ k, A i k • ∑ l, B j l • x (k, l) = 0 := by intro i j replace hx := congr_fun hx ( i, j ) simp only [Matrix.mulVec, dotProduct, Matrix.kroneckerMap_apply, Pi.zero_apply, smul_eq_mul, Finset.mul_sum] at hx ⊢ rw [ ← Finset.sum_product' ] simpa only [mul_assoc, Finset.univ_product_univ] using hx -- Apply the hypothesis `hA` to each term in the sum. have h_apply_hA : ∀ i j, ∑ k, C i k • ∑ l, B j l • x (k, l) = 0 := by intro i j specialize hA ( show (WithLp.toLp 2 ( fun k => ∑ l, B j l • x ( k, l ) )) ∈ LinearMap.ker ( Matrix.toEuclideanLin A ) from ?_ ) · simp_all only [smul_eq_mul, LinearMap.mem_ker] ext i_1 : 1 simp_all only [PiLp.zero_apply] apply h_kronecker · exact congr(WithLp.ofLp $hA i) ext ⟨ i, j ⟩ simp only [smul_eq_mul, Matrix.mulVec, dotProduct, Matrix.kroneckerMap_apply, Pi.zero_apply] at h_kronecker h_apply_hA ⊢ have h_apply_hB : ∑ l, D j l • ∑ k, C i k • x (k, l) = 0 := by specialize hB simp_all only [funext_iff, Pi.zero_apply, Prod.forall, smul_eq_mul] have := hB ( show (WithLp.toLp 2 ( fun l => ∑ k, C i k * x ( k, l ) )) ∈ LinearMap.ker ( Matrix.toEuclideanLin B ) from ?_ ) · simp_all only [LinearMap.mem_ker] ; exact congr(WithLp.ofLp $this j) · ext j specialize h_apply_hA i j simp [ Matrix.mulVec, dotProduct, Finset.mul_sum ] at h_apply_hA ⊢ simp_rw [mul_left_comm] rw [Finset.sum_comm] exact h_apply_hA rw [← h_apply_hB] simp only [smul_eq_mul, Finset.mul_sum] rw [ Finset.sum_sigma' ]; refine' Finset.sum_bij ( fun x _ => ⟨ x.2, x.1 ⟩ ) _ _ _ _ · simp · simp · simp · simp only [Finset.mem_univ, mul_assoc, Prod.mk.eta, mul_left_comm, imp_self, implies_true]- Project
- quantumInfo
- License
- MIT
- Commit
- 56e83a9288a3
- Source
- QuantumInfo/Finite/Entropy/Relative.lean:1180-1227
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Project documentation
The operator norm of the conjugate transpose is equal to the operator norm. -/ theorem Matrix.opNorm_conjTranspose_eq_opNorm {m n : Type*} [Fintype m] [Fintype n] [DecidableEq m] [DecidableEq n] (A : Matrix m n 𝕜) : Matrix.opNorm Aᴴ = Matrix.opNorm A := by unfold Matrix.opNorm rw [← ContinuousLinearMap.adjoint.norm_map (toEuclideanLin A).toContinuousLine...
Source project: quantumInfo
Person-level attribution pending.
Convex roof of pure
convex_roof_of_pure
Plain-language statement
The convex roof extension of g : KetUpToPhase d → ℝ≥0 applied to a pure state ψ is g (KetUpToPhase.mk ψ).
Source project: quantumInfo
Person-level attribution pending.
Id achieves Rate log dim
CPTPMap.id_achievesRate_log_dim
Plain-language statement
The identity channel on D dimensional space achieves a rate of log2(D).
Source project: quantumInfo
Person-level attribution pending.