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QR and polar retractions on Stiefel and Grassmann

Definition

For X∈St⁡(n,r) and η∈TXSt⁡(n,r), put Y=X+η. On the domain where Y has full column rank, let qf⁡(Y) be the Q factor in the unique reduced QR factorization Y=QR with R upper triangular and positive diagonal. Define the QR map by RXQR(η)=qf⁡(X+η). Define the polar map by RXpol(η)=(X+η)((X+η)T(X+η))−1/2, where the exponent denotes the inverse of the unique positive-definite square root. For a Grassmann tangent at [X], use its unique horizontal representative η satisfying XTη=0 and define the induced map by taking the output column space. Under X↦XQ, this representative changes to ηQ, so the input matrix changes to (X+η)Q. The polar formula is right-equivariant: RXQpol(ηQ)=RXpol(η)Q for every Q∈O⁡(r).

These are defined only where the displayed input is full rank. In fact, for a Stiefel tangent η, X+η always has full column rank, since ∥(X+η)v∥22=∥v∥22+∥ηv∥22 for every v∈Rr.

Facts & Assumptions

Given: X∈St⁡(n,r) and η∈TXSt⁡(n,r) as in Tangent spaces and Frobenius projections on Stiefel and Grassmann.

[F1]

Gram–Schmidt orthonormalization gives an orthonormal basis from a linearly independent ordered family (Gram–Schmidt turns every finite independent list into an orthonormal list with the same successive spans).

[F3]

Every positive-definite self-adjoint bundle endomorphism has a unique smooth positive square root (Positive-definite bundle endomorphisms have smooth positive square roots).

[F4]

A reduced QR factorization writes a full-column-rank matrix as an orthonormal-column factor times an upper-triangular factor (Full, reduced, and column-pivoted computational QR factorisations).

[F5]

A tangent matrix satisfies XTη+ηTX=0 (Tangent spaces and Frobenius projections on Stiefel and Grassmann).

[F6]

A Grassmann tangent has a unique horizontal representative, and changing the frame from X to XQ changes it from η to ηQ (Real Stiefel and Grassmann optimization conventions).

Proof

technique · verify the domains and orthonormality of both formulas
1.1F1F2F3F5givenalgebra

By [F5], tangency gives XTη+ηTX=0. Therefore for v≠0, ∥(X+η)v∥22=∥v∥22+vT(XTη+ηTX)v+∥ηv∥22=∥v∥22+∥ηv∥22>0. Thus X+η has full column rank. More generally, for any full-rank Y, vTYTYv=∥Yv∥22>0 for v≠0, so its Gram matrix is positive definite; [F1] supplies the QR factor, while [F2] diagonalizes the Gram matrix and [F3] supplies its positive square root and inverse.

2.1F1F2F3F4F6givenstep 1.1inductionalgebra∎

For full-column-rank Y=[y1 ⋯ yr], its columns are linearly independent. Apply Gram–Schmidt [F1], writing uj=yj−∑i<j(qiTyj)qi and qj=uj/∥uj∥2. The residuals are nonzero, so Q=[q1 ⋯ qr] has orthonormal columns. Set R=QTY. For i>j, qi is orthogonal to span⁡(y1,…,yj), so Rij=0; and Rjj=qjTyj=∥uj∥2>0. Since each yj lies in span⁡(q1,…,qj), QR=Y. This constructs a reduced QR factorization with positive diagonal. To check uniqueness, if Y=Q1R1=Q2R2 are two such factorizations, then Q2TQ1=R2R1−1 is orthogonal and upper triangular with positive diagonal. Its first column has only its first entry, which must be 1 by unit norm and positivity; orthogonality zeros the rest of its first row. Induction on the remaining block makes it Ir, so Q1=Q2 and R1=R2. For the polar factor U=Y(YTY)−1/2, symmetry of the root and its defining square give UTU=(YTY)−1/2(YTY)(YTY)−1/2=Ir. Hence both outputs have orthonormal columns. For a Grassmann input, [F6] says a frame change X↦XQ0 changes η to ηQ0, so the input Y=X+η becomes YQ0 with the same column space; uniqueness of the positive root gives (Q0TYTYQ0)−1/2=Q0T(YTY)−1/2Q0, so the polar output is multiplied by Q0. Thus the Grassmann outputs are well-defined.

Remark

The formulas here are exact-arithmetic definitions. The finite-precision Householder QR supplier proves a backward-error statement under its operationwise assumptions and does not assert that a computed Q is exactly orthogonal (The scaled Householder QR implementation is backward stable). No floating-point retraction guarantee is claimed by this page.

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Sources