Metamath Proof Explorer


Theorem minvec

Description: Minimizing vector theorem, or the Hilbert projection theorem. There is exactly one vector in a complete subspace W that minimizes the distance to an arbitrary vector A in a parent inner product space. Theorem 3.3-1 of Kreyszig p. 144, specialized to subspaces instead of convex subsets. (Contributed by NM, 11-Apr-2008) (Proof shortened by Mario Carneiro, 9-May-2014) (Revised by Mario Carneiro, 15-Oct-2015) (Proof shortened by AV, 3-Oct-2020)

Ref Expression
Hypotheses minvec.x ⊢ X = Base U
minvec.m ⊢ - ˙ = - U
minvec.n ⊢ N = norm ⁡ U
minvec.u ⊢ φ → U ∈ CPreHil
minvec.y ⊢ φ → Y ∈ LSubSp ⁡ U
minvec.w ⊢ φ → U ↾ 𝑠 Y ∈ CMetSp
minvec.a ⊢ φ → A ∈ X
Assertion minvec ⊢ φ → ∃! x ∈ Y ∀ y ∈ Y N ⁡ A - ˙ x ≤ N ⁡ A - ˙ y

Proof

Step Hyp Ref Expression
1 minvec.x ⊢ X = Base U
2 minvec.m ⊢ - ˙ = - U
3 minvec.n ⊢ N = norm ⁡ U
4 minvec.u ⊢ φ → U ∈ CPreHil
5 minvec.y ⊢ φ → Y ∈ LSubSp ⁡ U
6 minvec.w ⊢ φ → U ↾ 𝑠 Y ∈ CMetSp
7 minvec.a ⊢ φ → A ∈ X
8 eqid ⊢ TopOpen ⁡ U = TopOpen ⁡ U
9 oveq2 ⊢ j = y → A - ˙ j = A - ˙ y
10 9 fveq2d ⊢ j = y → N ⁡ A - ˙ j = N ⁡ A - ˙ y
11 10 cbvmptv ⊢ j ∈ Y ⟼ N ⁡ A - ˙ j = y ∈ Y ⟼ N ⁡ A - ˙ y
12 11 rneqi ⊢ ran ⁡ j ∈ Y ⟼ N ⁡ A - ˙ j = ran ⁡ y ∈ Y ⟼ N ⁡ A - ˙ y
13 eqid ⊢ inf ran ⁡ j ∈ Y ⟼ N ⁡ A - ˙ j ℝ < = inf ran ⁡ j ∈ Y ⟼ N ⁡ A - ˙ j ℝ <
14 eqid ⊢ dist ⁡ U ↾ X × X = dist ⁡ U ↾ X × X
15 1 2 3 4 5 6 7 8 12 13 14 minveclem7 ⊢ φ → ∃! x ∈ Y ∀ y ∈ Y N ⁡ A - ˙ x ≤ N ⁡ A - ˙ y