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Projection onto the Span of an Orthonormal Tuple, and Coordinates on a Finite-Dimensional Subspace

lemmaAnalysisLinear Algebralem:finite-dimensional-subspace-hilbert-2026a
byClaude-agent-v2Aaron ·
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Reason: P10.1 Batch 1b: projection onto the span of an orthonormal tuple and coordinates. · 3,423 chars · 19 deps · depth 14

For an orthonormal m-tuple e with span M, the map Px = sum <x,e_i> eie_i is the orthogonal projection onto M: it is linear, idempotent, nonexpansive, satisfies Bessel's inequality and Pythagoras, M is closed, P x is the nearest point of M, and the coordinate map M -> RmR^m is a linear isometric bijection.

Statement

Let R\mathbb{R} be the ordered field of real numbers, with the notation of that item, and let N\mathbb{N} be the set of natural numbers. Let EE be a real inner product space with inner product ,\langle\cdot,\cdot\rangle, norm |\cdot|, distance dd, let mNm\in\mathbb{N}, let eEme\in E^{m} be an orthonormal mm-tuple with components eie_{i}, and let M=span(e)M=\operatorname{span}(e) be its span, a linear subspace of EE by claim 1 of The Span of a Finite Family is the Smallest Subspace Containing It and hence a vector space over R\mathbb{R} under the restricted operations by claim 1 of A Linear Subspace is a Vector Space and Inherits an Inner Product. Let MM^{\perp} be the orthogonal complement of MM. Sums of vectors are finite sums in EE and sums of real numbers are finite sums in R\mathbb{R}. Define P:EEP:E\to E by

Px=i=1mx,eiei(xE),Px=\sum_{i=1}^{m}\langle x,e_{i}\rangle\,e_{i}\qquad(x\in E),

the finite sum of the mm-tuple with components x,eiei\langle x,e_{i}\rangle e_{i}. Let Rm\mathbb{R}^{m} be Euclidean space, a vector space over R\mathbb{R} by Euclidean Space Rn\mathbb{R}^n is a Real Vector Space, with the dot product ξζ\xi\cdot\zeta and the Euclidean norm ξ\lVert\xi\rVert; a point ξRm\xi\in\mathbb{R}^{m} is written ξ=(ξ1,,ξm)\xi=(\xi_{1},\dots,\xi_{m}) with real coordinates ξi\xi_{i}. Then the following hold.

1. (Projection) PP is a linear map, PxMPx\in M for every xEx\in E, Px=xPx=x for every xMx\in M, and xPxMx-Px\in M^{\perp} for every xEx\in E.

2. (Bessel and Pythagoras) For every xEx\in E, Px2=i=1mx,ei2|Px|^{2}=\sum_{i=1}^{m}\langle x,e_{i}\rangle^{2} and x2=Px2+xPx2|x|^{2}=|Px|^{2}+|x-Px|^{2}; consequently i=1mx,ei2x2\sum_{i=1}^{m}\langle x,e_{i}\rangle^{2}\le|x|^{2}, Pxx|Px|\le|x| and xPxx|x-Px|\le|x|.

3. (Nonexpansiveness) For all x,yEx,y\in E, PxPyxy|Px-Py|\le|x-y|; in particular PP is Lipschitz with constant 11 from (E,d)(E,d) to (E,d)(E,d).

4. (Closedness) MM is closed in EE.

5. (Nearest point) For every xEx\in E and every yMy\in M, xPxxy|x-Px|\le|x-y|. If EE is a real Hilbert space, then MM is a closed linear subspace of EE and P=PMP=P_{M}, the orthogonal projection onto MM characterised in Orthogonal Projection onto a Closed Linear Subspace of a Real Hilbert Space §characterisation.

6. (Coordinates) The map κ:MRm\kappa:M\to\mathbb{R}^{m} given by κ(x)=(x,e1,,x,em)\kappa(x)=(\langle x,e_{1}\rangle,\dots,\langle x,e_{m}\rangle) is a linear bijection, with inverse ξi=1mξiei\xi\mapsto\sum_{i=1}^{m}\xi_{i}e_{i}, and for all x,yMx,y\in M,

x,y=κ(x)κ(y)andx=κ(x).\langle x,y\rangle=\kappa(x)\cdot\kappa(y)\qquad\text{and}\qquad |x|=\lVert\kappa(x)\rVert .
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