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TheoremStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedjudge pass (gpt-6-luna)
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Schwarz and trace-norm channel contraction

Statement

Let Φ:Md(C)→Me(C) be a finite channel, and define ∥X∥∞=sup⁡∥v∥=1∥Xv∥ and ∥X∥1=Tr⁡X∗X. Its trace dual Φ†:Me(C)→Md(C) from Channel duals and norm closure satisfies

∥Φ†(A)∥∞≤∥A∥∞(A∈Me(C)). For every X∈Md(C), the Schrödinger map contracts the trace norm: ∥Φ(X)∥1≤∥X∥1.

The second inequality applies to arbitrary complex matrices, not only density matrices.

Facts & Assumptions

Given: Integers d,e≥1, a finite channel Φ:Md(C)→Me(C), and finite matrix operator and trace norms as defined in the Statement.

[F1]

Finite completely positive trace-preserving maps: complete positivity includes positivity of the ancilla extension id⁡2⊗Φ, and trace preservation is exact on all input matrices.

[F2]

Channel duals and norm closure: the trace dual is unital and completely positive and satisfies Tr⁡(Φ(X)A)=Tr⁡(XΦ†(A)).

[F3]

Finite matrix spectral and state calculus: the standard finite-dimensional inner product is taken linear in its first argument; finite Hermitian matrices have orthonormal spectral decompositions and positive matrices have positive square roots defined by spectral calculus; the finite trace is cyclic.

Proof

1.1givenF2F3algebra

By [F2], Φ† is positive. For any Hermitian H∈Me(C), its finite spectral decomposition [F3] is H=∑λλPλ, where each λ is real and each spectral projection Pλ is positive semidefinite. Hence every Φ†(Pλ) is Hermitian, so Φ†(H) is Hermitian. Write an arbitrary A as A=H+iK, where H=(A+A∗)/2 and K=(A−A∗)/(2i) are Hermitian. By complex linearity, Φ†(A∗)=Φ†(H)−iΦ†(K)=Φ†(A)∗.

1.2givenF3constructalgebra

For any n≥1 and Z∈Mn(C), use the standard inner product ⟨u,v⟩=∑kukvk‾, linear in its first argument, and define ∣u⟩⟨v∣ as the map x↦⟨x,v⟩u. Since Z∗Z is positive, with ⟨Z∗Zv,v⟩=∥Zv∥2, [F3] diagonalizes it in an orthonormal basis (vj) with eigenvalues sj2≥0. For each sj>0, put uj=Zvj/sj. Then ⟨uj,uk⟩=δjk, and Z=∑sj>0sj∣uj⟩⟨vj∣. The positive square root of Z∗Z has eigenvalues sj, so ∥Z∥1=∑jsj.

2.1givenF1F2step 1.1algebra

For A∈Me(C), the block matrix (A∗AA∗AIe) is positive semidefinite because its quadratic form at (x,y) is ∥Ax+y∥2. Apply id⁡2⊗Φ†: by [F2] the trace dual is completely positive, and the definition in [F1] makes its extension by the two-dimensional ancilla positive. By unitality in [F2] and adjoint preservation from step 1.1, the resulting block is (Φ†(A∗A)Φ†(A)∗Φ†(A)Id)≥0.

2.2step 1.2F3choosealgebra

For any n≥1, Z∈Mn(C), and B∈Mn(C) with ∥B∥∞≤1, write Zab=∑sj>0sj(uj)a(vj)b‾ using step 1.2. Expanding both diagonal-sum traces gives Tr⁡(BZ)=∑a,bBabZba=∑sj>0sj∑a,bBab(uj)b(vj)a‾ and Tr⁡(ZB)=∑a,bZabBba=∑sj>0sj∑a,bBab(uj)b(vj)a‾. The inner sum is ⟨Buj,vj⟩ for the inner product fixed in step 1.2. For each unit vj, 0≤∥Buj−⟨Buj,vj⟩vj∥2=∥Buj∥2−∣⟨Buj,vj⟩∣2, so both trace magnitudes are at most ∑jsj=∥Z∥1. Extend the two finite orthonormal lists (uj), (vj) to orthonormal bases and choose a unitary B carrying each uj to vj; then both trace magnitudes equal ∑jsj. Thus ∥Z∥1=sup⁡∥B∥∞≤1∣Tr⁡(BZ)∣=sup⁡∥B∥∞≤1∣Tr⁡(ZB)∣, including Z=0.

3.1step 2.1F2F3algebra

In the positive block from step 2.1, evaluate the quadratic form at (x,−Φ†(A)x). This gives ⟨(Φ†(A∗A)−Φ†(A)∗Φ†(A))x,x⟩≥0 for every x, so Φ†(A)∗Φ†(A)≤Φ†(A∗A). Also A∗A≤∥A∥∞2Ie; positivity and unitality in [F2] then give Φ†(A)∗Φ†(A)≤∥A∥∞2Id, proving ∥Φ†(A)∥∞≤∥A∥∞.

4.1step 3.1step 2.2F2algebra∎

Apply the second dual norm formula from step 2.2 in output dimension e to Φ(X). For each A∈Me(C) with ∥A∥∞≤1, step 3.1 gives ∥Φ†(A)∥∞≤1, so the same formula in input dimension d bounds ∣Tr⁡(XΦ†(A))∣≤∥X∥1. The trace-pairing identity [F2] therefore gives ∥Φ(X)∥1=sup⁡∥A∥∞≤1∣Tr⁡(Φ(X)A)∣=sup⁡∥A∥∞≤1∣Tr⁡(XΦ†(A))∣≤∥X∥1.

Depends on

Dependency tree · 2 levels

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