Alphabeta Math
DefinitionDefinition: AI-adaptedProof: Not applicablePipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-22
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  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
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The Hilbert orthogonal projection onto a closed subspace

Definition

Assume the Axiom of Countable Choice. Let M be a closed linear subspace of a real or complex Hilbert space H (Linear subspace of a vector space). By the orthogonal-decomposition theorem (Orthogonal decomposition by a closed subspace) every x∈H has a unique representation

x=PMx+(x−PMx),PMx∈M,x−PMx∈M⊥,

and the Hilbert orthogonal projection onto M is the map

PM:H⟶M⊆H,x⟼PMx,

assigning to x its unique M-component. Its defining properties are therefore

PMx∈M,x−PMx∈M⊥(x∈H),

which characterise PM uniquely: a map with these defining properties must agree with the M-component of the unique decomposition of each x.

Agreement with the finite-dimensional projection. If V is a finite-dimensional inner-product space and W⊆V a subspace, then For a subspace W of a finite-dimensional inner product space, V=W⊕W⊥ writes V=W⊕W⊥ and The orthogonal projection PWv is the W-component in V=W⊕W⊥ defines PWv as the unique W-component of v; the defining properties displayed above are the same, so they define the same map on a finite-dimensional Hilbert space.

Range and kernel. PMx∈M for every x, and PMm=m for m∈M because m=m+0 with 0∈M⊥; conversely PMx=0 says exactly that x=x−0∈M⊥. Hence the range of PM is M and its kernel is M⊥, and PM is the identity on M and zero on M⊥.

Depends on

Dependency tree · 2 levels

Sources