Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-6-luna)
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Graph charts and tangent directions for complex rank-r projectors

Statement

Fix P0∈Pr, put U=range⁡P0 (range as in Kernel and image of a linear map), and use the orthogonal decomposition Cn=U⊕U⊥. Write PV for the orthogonal projector onto an r-dimensional subspace V. Such a subspace V for which the orthogonal projection πU∣V:V→U is invertible is uniquely a graph VX={u+Xu:u∈U} of a linear map X:U→U⊥. Its projector is P(X)=JX(IU+X∗X)−1JX∗,JXu=u+Xu. These graph coordinates form an open neighborhood of P0 in the projector Grassmannian. In the block decomposition at P0, its tangent space is TP0Pr={(0B∗B0):B:U→U⊥}. The projector representation also removes orbital-frame gauge: two orthonormal frames represent the same projector exactly when they differ by right multiplication by a unitary matrix.

Facts & Assumptions

Given: P0∈Pr, the range/kernel decomposition of an orthogonal projector, and finite-dimensional complex inner-product spaces.

[F1]

The domain consists of Hermitian idempotents with trace r (Rank-r orthogonal projector domain).

[F2]

A Hermitian idempotent has range dimension equal to its trace (A Hermitian idempotent has trace equal to its rank).

[F3]

Every finite-dimensional inner-product space has an orthonormal basis (Every finite-dimensional real or complex inner product space has an orthonormal basis).

[F4]

The kernel and image of a linear map are its nullspace and range (Kernel and image of a linear map).

[F5]

On the invertible set, Dinv⁡(A)[H]=−A−1HA−1 and matrix differentials obey the product rule; iterating this expression gives continuous derivatives of all finite orders (On the invertible locus, Dinv⁡(A)[H]=−A−1HA−1, Matrix differentials obey the sum rule, product rule, and adjoint rule).

Proof

1.1F1F4givenalgebra

Since P02=P0, every x∈Cn decomposes as P0x+(I−P0)x with the first term in U and the second in ker⁡P0 by [F4]. If u=P0y∈U and z∈ker⁡P0, then ⟨u,z⟩=⟨P0y,z⟩=⟨y,P0z⟩=0 by self-adjointness. Hence ker⁡P0=U⊥, giving the stated orthogonal block decomposition.

1.2F1F2givenalgebra

For any X:U→U⊥, JX∗JX=IU+X∗X is positive definite because ⟨(IU+X∗X)u,u⟩=∥u∥2+∥Xu∥2>0 for u≠0. The displayed P(X) is Hermitian, and P(X)2=JX(JX∗JX)−1JX∗JX(JX∗JX)−1JX∗=P(X). Its range is range⁡JX=VX, of dimension r; [F2] gives tr⁡P(X)=r.

2.1F1F5step 1.1step 1.2algebra

Let T=πU∣V:V→U, whose adjoint is T∗=PV∣U:U→V. The block A=πUPV∣U is TT∗, so it is invertible exactly when T is invertible: TT∗ is positive definite exactly when T∗ is injective, and the domain and codomain of T have the same finite dimension. Thus the chart condition is the open condition that A be invertible; it is open because PV↦A and determinant are continuous, and at P0 we have A=IU. In that domain, projection from V to U is bijective, so every u∈U has a unique vector u+Xu∈V; this defines a unique linear X. In blocks PV=(AB∗BC), that map is X=BA−1. The formula in step 1.2 is the unique orthogonal projector onto this graph. Matrix inversion is smooth on invertible matrices by [F5], so the graph map and P(X) are inverse smooth coordinates.

2.2F1step 1.2givenalgebra

Let P(t) be a differentiable curve in Pr with P(0)=P0 and derivative H. Differentiating P(t)∗=P(t) and P(t)2=P(t) gives H=H∗ and P0H+HP0=H. In block form these equations force H=(0B∗B0). Conversely, for any such B, the graph curve P(tB) from step 1.2 has derivative (0B∗B0) at t=0, since (I+t2B∗B)−1=I+O(t2). Thus these are exactly all tangent directions.

3.1F3givenalgebra∎

By [F3], each frame Y with Y∗Y=I and range U exists. If Y and Z are two such frames, then Q=Y∗Z satisfies YQ=YY∗Z=P0Z=Z and Q∗Q=Z∗YY∗Z=Z∗Z=I. Thus Q is unitary and Z=YQ. Conversely, YQ(YQ)∗=YY∗ for every unitary Q. Hence projectors identify exactly the unitary changes of occupied frame.

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