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Finite-dimensional Schumacher quantum source coding theorem

Statement

Let ρ be a density operator on a nonzero finite-dimensional source space, and use the squared entanglement-fidelity code model of Finite IID quantum source and compression code. Write S(ρ) in nats.

  1. For every R>S(ρ) there is a sequence of compression codes with Fe(n)→1 and lim sup⁡nn−1ln⁡Mn≤R.
  2. If a sequence of codes satisfies lim sup⁡nn−1ln⁡Mn<S(ρ), then Fe(n)→0.

Thus the asymptotic reliable compression rate is exactly S(ρ) nats per source letter, or S(ρ)/ln⁡2 qubits per source letter.

Facts & Assumptions

Given: A nonzero finite-dimensional source space, a density operator ρ, and the compression-code convention of the Statement.

[F1]

Finite IID quantum source and compression code: an (n,M) code factors through an M-dimensional code space, and its squared entanglement fidelity is the overlap of a purification with the recovered state.

[F2]

Typical-projector bounds for finite quantum sources and cq ensembles: the spectral typical projector for ρ⊗n has mass tending to one, rank at most en(S(ρ)+δ), and every included eigenvalue is at most e−n(S(ρ)−δ).

[F3]

Compression dimension bounds entanglement fidelity: any code factoring through dimension M has entanglement fidelity at most the sum of the M largest eigenvalues of ρ⊗n.

[F4]

Finite-dimensional quantum channel: a quantum channel is completely positive and trace preserving.

[F5]

Kraus and Choi characterizations of complete positivity and Trace preservation is Kraus normalization: finite channels have finite Kraus families, and a trace-preserving family satisfies ∑jKj∗Kj=I.

Proof

1.1F1F2F4F5F6givenconstruct

Fix δ>0, choose an ordered eigenbasis of ρ once, and take the spectral typical projector Πn from [F2]. Order its finitely many product eigenvectors lexicographically; the resulting map to the first rn standard code basis vectors defines a partial isometry Wn with Wn∗Wn=Πn, where rn=rank⁡Πn. Let the code space have dimension Mn=rn+1 and let ∣⊥⟩ be its extra flag, orthogonal to Pn:=WnWn∗. Define En(X)=WnXWn∗+tr⁡((I−Πn)X)∣⊥⟩⟨⊥∣,Dn(Y)=Wn∗YWn+⟨⊥∣Y∣⊥⟩ ρ⊗n. The encoder Kraus family consists of Wn and ∣⊥⟩⟨ej∣ over an orthonormal basis of ker⁡Πn; its Kraus squares sum to Πn+(I−Πn)=I. The decoder Kraus family consists of Wn∗ and λj∣fj⟩⟨⊥∣ from a spectral decomposition ρ⊗n=∑jλj∣fj⟩⟨fj∣; its Kraus squares sum to Pn+∣⊥⟩⟨⊥∣=I. Thus both maps are channels by [F4]–[F6]. If (Kℓ)ℓ is the finite composite Kraus family, substituting its action into [F1] gives Fe(n)=∑ℓ∣⟨ϕ∣(id⁡R⊗Kℓ)∣ϕ⟩∣2. The branch K0=Wn∗Wn=Πn contributes ∣⟨ϕ∣(id⁡R⊗Πn)∣ϕ⟩∣2=(tr⁡(ρ⊗nΠn))2, and every other branch contributes a nonnegative squared modulus. Therefore Fe(n)≥(tr⁡(ρ⊗nΠn))2→1. The basis order makes the sequence of codes explicit and uses no choice axiom.

1.2F2givenalgebrachoose

Suppose lim sup⁡nn−1ln⁡Mn<S(ρ). Choose δ>0 and N so that Mn≤en(S(ρ)−2δ) for n≥N. Let Πn be the typical projector from [F2], and let ϵn=1−tr⁡(ρ⊗nΠn)→0. Each eigenvalue in its range is at most e−n(S(ρ)−δ). Therefore the sum of any Mn eigenvalues of ρ⊗n is at most ϵn+Mne−n(S(ρ)−δ)≤ϵn+e−nδ→0: the part outside the typical range contributes at most its total mass, and each selected eigenvalue inside contributes at most the displayed maximum.

2.1F2step 1.1algebrachoose

Since rn≤en(S(ρ)+δ) and en(S+δ)≥1, Mn=rn+1≤2en(S(ρ)+δ). Hence lim sup⁡nn−1ln⁡Mn≤S(ρ)+δ. Given R>S(ρ), choose δ<R−S(ρ) to obtain the direct assertion.

3.1F1F3step 1.2∎

Apply [F3] to each n-block code with intermediate dimension Mn. Step 1.2 shows that its fidelity is at most a quantity tending to zero, hence Fe(n)→0. The argument includes zero eigenvalues and requires no full-rank source assumption.

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