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LemmaStatement: AI-adaptedProof: AI-adaptedPipeline-generatedverified 2026-10-22 (gpt-6.1-sol)
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The Gram pseudoinverse reconstructs a spanning Hermitian frame

Statement

Let d,m≥1, let F1,…,Fm∈Hd span Hd over R, and form S, G=S∗S, G+, and Da as in the preceding finite-frame definition. If G=∑λ>0λPλ is its finite spectral resolution, then G+=∑λ>0λ−1Pλ. Moreover, every X∈Hd is reconstructed by

X=∑a=1mTr⁡(XFa)Da.

This holds for redundant families as well as bases; G need not be invertible.

Facts & Assumptions

Given: d,m≥1, a spanning family F1,…,Fm∈Hd, its synthesis map S, Gram matrix G=S∗S, Moore–Penrose inverse G+, and canonical dual Da.

[A1]

The finite family F1,…,Fm spans Hd over R, as required in the Statement.

[F1]

Finite Hermitian frames and their Gram pseudoinverse: Hd is a real space with the trace pairing Tr⁡(AB); Gab=Tr⁡(FaFb); Da=∑b(G+)baFb.

[F2]

The real trace pairing on finite Hermitian matrices is an inner product: the Hilbert–Schmidt trace pairing is a real inner product, G=S∗S is real positive semidefinite, and ker⁡G=ker⁡S.

[F3]

Finite matrix spectral and state calculus: every finite Hermitian matrix has an orthonormal eigenbasis with real eigenvalues.

[F4]

The Moore--Penrose pseudoinverse A+ as the solution of the four Penrose equations: G+ satisfies GG+G=G, G+GG+=G+, and both GG+ and G+G are self-adjoint.

[F5]

Every finite real or complex matrix has a unique Moore--Penrose pseudoinverse: every finite real matrix has a unique matrix satisfying the four Penrose equations.

Proof

1.1F1F2algebra

By [F2], G is real symmetric positive semidefinite, G=S∗S, and ker⁡G=ker⁡S. The coordinate formula for the adjoint is (S∗X)a=⟨Fa,X⟩HS=Tr⁡(XFa) by [F1] and [F2].

2.1F2F3F4F5step 1.1algebra

Regard the real symmetric positive semidefinite matrix G as a complex Hermitian matrix and apply [F3]. Its eigenvalues are real. If z=x+iy is in the complex eigenspace for a real eigenvalue λ, then realness of G gives Gx=λx and Gy=λy; thus that eigenspace is the complexification of its real eigenspace. Real eigenspaces for distinct eigenvalues are orthogonal, since Gu=λu, Gv=μv, and symmetry give (λ−μ)uTv=0. The real eigenspaces form a direct sum of dimension m: their complexifications are the orthogonal complex eigenspaces, which span Cm by [F3]. Each eigenvalue is nonnegative because, for a nonzero real eigenvector x with Gx=λx, λ∥x∥22=xTGx≥0. In each real eigenspace, take a finite basis v1,…,vk and set u1=v1/∥v1∥2 and uj=(vj−∑i<j(vjTui)ui)/∥vj−∑i<j(vjTui)ui∥2 for 2≤j≤k; basis independence makes every denominator nonzero, and these vectors form a real orthonormal basis. These bases give a real spectral resolution G=∑λ≥0λPλ with real orthogonal projections whose sum is I. Put H0=∑λ>0λ−1Pλ. Orthogonality gives GH0G=G, H0GH0=H0, and GH0=H0G=∑λ>0Pλ, which are self-adjoint. Thus H0 satisfies the four Penrose equations [F4], and uniqueness in [F5] gives H0=G+. Consequently Q=G+G=∑λ>0Pλ is an orthogonal projection and ker⁡Q=ker⁡G, so Ran⁡(I−Q)=ker⁡G=ker⁡S by [F2].

3.1A1F1F2step 1.1step 2.1algebra∎

The synthesis map of the canonical dual is D=SG+ by [F1]. For any X∈Hd, the spanning hypothesis [A1] supplies c∈Rm with X=Sc. Then D(S∗X)=SG+S∗Sc=SG+Gc=SQc=Sc=X, because c−Qc∈Ran⁡(I−Q)=ker⁡S by step 2.1. The coordinates of S∗X are Tr⁡(XFa) by step 1.1, which proves the stated sum.

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