Ket Is Prod iff rank eq one
MState.Ket.IsProd_iff_rank_eq_one
Plain-language statement
A ket on a product space is a product state if and only if its coefficient matrix has rank 1.
Exact Lean statement
theorem Ket.IsProd_iff_rank_eq_one {d₁ d₂ : Type*} [Fintype d₁] [Fintype d₂] [DecidableEq d₁] [DecidableEq d₂]
(ψ : Ket (d₁ × d₂)) :
ψ.IsProd ↔ (Matrix.of (fun i j => ψ (i, j))).rank = 1Formal artifact
Lean source
theorem Ket.IsProd_iff_rank_eq_one {d₁ d₂ : Type*} [Fintype d₁] [Fintype d₂] [DecidableEq d₁] [DecidableEq d₂] (ψ : Ket (d₁ × d₂)) : ψ.IsProd ↔ (Matrix.of (fun i j => ψ (i, j))).rank = 1 := by rw [ Ket.IsProd_iff_mul_eq_mul ]; constructor; · intro h; obtain ⟨ξ, ψ', hξψ'⟩ : ∃ ξ : d₁ → ℂ, ∃ ψ' : d₂ → ℂ, ∀ i j, ψ (i, j) = ξ i * ψ' j := by -- Let's choose any $j₀$ such that $\psi(i, j₀) \neq 0$ for some $i$. obtain ⟨j₀, hj₀⟩ : ∃ j₀ : d₂, ∃ i₀ : d₁, ψ (i₀, j₀) ≠ 0 := by have := ψ.exists_ne_zero; exact ⟨ this.choose.2, this.choose.1, this.choose_spec ⟩; choose i₀ hi₀ using hj₀; exact ⟨ fun i => ψ ( i, j₀ ) / ψ ( i₀, j₀ ), fun j => ψ ( i₀, j ), fun i j => by rw [ div_mul_eq_mul_div, eq_div_iff hi₀ ] ; linear_combination h i i₀ j j₀ ⟩; -- Since the matrix is a product of two vectors, its rank is 1. have h_rank : Matrix.rank (Matrix.of (fun i j => ξ i * ψ' j)) ≤ 1 := by -- The range of the matrix is spanned by the single vector ξ. have h_range : LinearMap.range (Matrix.mulVecLin (Matrix.of (fun i j => ξ i * ψ' j))) ≤ Submodule.span ℂ {ξ} := by rintro x ⟨ y, rfl ⟩; rw [ Submodule.mem_span_singleton ]; exact ⟨ ∑ j, ψ' j * y j, by ext i; simp [ Matrix.mulVec, dotProduct, mul_comm, mul_left_comm, Finset.mul_sum _ _ _ ] ⟩; exact le_trans ( Submodule.finrank_mono h_range ) ( finrank_span_le_card _ ) |> le_trans <| by norm_num; cases h_rank.eq_or_lt <;> simp_all [ Matrix.rank, Submodule.eq_bot_iff ]; · convert ‹Module.finrank ℂ ( LinearMap.range ( Matrix.mulVecLin ( Matrix.of fun i j => ξ i * ψ' j ) ) ) = 1› using 3 ; aesop; · aesop; · ext; simp [hξψ']; · have := ψ.exists_ne_zero simp_all only [ne_eq, mul_eq_zero, not_or, Prod.exists, exists_and_left, exists_and_right] obtain ⟨left, right⟩ := this obtain ⟨w, h_2⟩ := left obtain ⟨w_1, h_3⟩ := right rename_i h_1 specialize h_1 ( Pi.single w_1 1 ) simp_all [ funext_iff] · rw [ Matrix.rank ]; rw [ finrank_eq_one_iff' ] intro a i₁ i₂ j₁ j₂ simp_all only [ne_eq, Subtype.forall, LinearMap.mem_range, Matrix.mulVecBilin_apply, forall_exists_index, Subtype.exists, Submodule.mk_eq_zero, SetLike.mk_smul_mk, Subtype.mk.injEq, forall_apply_eq_imp_iff, exists_and_left, exists_prop] obtain ⟨w, h⟩ := a obtain ⟨left, right⟩ := h obtain ⟨left_1, right⟩ := right obtain ⟨w_1, h⟩ := left_1 subst h obtain ⟨ c, hc ⟩ := right ( Pi.single j₁ 1 ) ; obtain ⟨ d, hd ⟩ := right ( Pi.single j₂ 1 ) ; simp_all only [funext_iff, Matrix.mulVec, Matrix.of_apply, Pi.zero_apply, not_forall, Pi.smul_apply, smul_eq_mul, Matrix.mulVec_single, MulOpposite.op_one, one_smul, Matrix.col_apply] rw [ ← hc i₁, ← hd i₁, ← hc i₂, ← hd i₂ ] ; ring- Project
- quantumInfo
- License
- MIT
- Commit
- 56e83a9288a3
- Source
- QuantumInfo/Finite/MState.lean:913-962
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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.