Alphabeta Math
LemmaStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedjudge pass (gpt-6-luna)
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The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
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Demultiplexing a Two-Block Unitary

Statement

Let H be a finite-dimensional complex inner-product space and let U0,U1 be unitary endomorphisms of H. On the control-first direct sum H⊕H, the block unitary diag⁡(U0,U1) factors as diag⁡(U0,U1)=(I⊗V)diag⁡(D,D∗)(I⊗W) for unitary V,W on H and a diagonal unitary D in an orthonormal eigenbasis; I⊗V denotes diag⁡(V,V) under C2⊗H≅H⊕H.

Facts & Assumptions

Given: A finite-dimensional complex inner-product space H and unitary U0,U1 on H.

[F1]

Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely: a normal endomorphism of a finite-dimensional complex inner-product space has an orthonormal eigenbasis.

[F2]

Every nonzero complex number has a unique polar form r(cos⁡θ+isin⁡θ) with r>0 and −π<θ≤π: every unit complex number is eit for some real t, and therefore has a unit-modulus square root.

Proof

1.1givenF1F2F3choose

The product Q:=U0U1∗ is unitary by [F3] and hence normal. By [F1], choose a unitary V and diagonal unitary D with Q=VD2V∗: diagonalize Q, write each eigenvalue as eitj by [F2], and put eitj/2 on the corresponding diagonal of D.

2.1step 1.1algebra

Set W:=D∗V∗U0. Then VDW=U0. Also VD∗W=VD−2V∗U0. Taking adjoints in U0U1∗=VD2V∗ gives U1U0∗=VD−2V∗, so VD−2V∗U0=U1. Thus the two diagonal blocks in the displayed factorization are respectively U0 and U1.

3.1step 1.1step 2.1given∎

The factors V,D,W are unitary, and the two block products agree with U0,U1; hence the asserted exact block factorization holds, including repeated eigenvalues. Only a finite orthonormal eigenbasis and finitely many square roots are chosen.

Depends on

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Sources