Math 2.0

Functional analysis Hilbert spaces Theorem

Jordan–von Neumann theorem

Builds on Normed vector spaceInner product spaceNorm induced by an inner product

Statement

Let 𝕂\mathbb{K} be ℝ\R or ℂ\C, and let (V,∥⋅∥)(V, \norm{\cdot}) be a normed vector space over 𝕂\mathbb{K}. Then the following are equivalent.

  1. There is an inner product ⟨⋅,⋅⟩\ip{\cdot}{\cdot} on VV whose induced norm is ∥⋅∥\norm{\cdot}, that is, ∥x∥2=⟨x,x⟩\norm{x}^2 = \ip{x}{x} for all x∈Vx \in V.
  2. The norm satisfies the parallelogram law: ∥x+y∥2+∥x−y∥2=2∥x∥2+2∥y∥2\norm{x + y}^2 + \norm{x - y}^2 = 2 \norm{x}^2 + 2 \norm{y}^2 for all x,y∈Vx, y \in V.

When these hold, the inner product is unique and is given by the polarization identity. For 𝕂=ℝ\mathbb{K} = \R it is ⟨x,y⟩=14(∥x+y∥2−∥x−y∥2),\ip{x}{y} = \frac{1}{4} \left( \norm{x + y}^2 - \norm{x - y}^2 \right), and for 𝕂=ℂ\mathbb{K} = \C, with ⟨⋅,⋅⟩\ip{\cdot}{\cdot} linear in the first argument, it is ⟨x,y⟩=14∑k=03ik∥x+iky∥2.\ip{x}{y} = \frac{1}{4} \sum_{k=0}^{3} i^k \norm{x + i^k y}^2.

Remarks

The direction from 1 to 2 is the parallelogram law in an inner product space. For the converse in the real case, define ⟨x,y⟩\ip{x}{y} by the polarization formula. Symmetry and ⟨x,x⟩=∥x∥2\ip{x}{x} = \norm{x}^2 are immediate. The parallelogram law gives ⟨x+x′,y⟩=⟨x,y⟩+⟨x′,y⟩\ip{x + x'}{y} = \ip{x}{y} + \ip{x'}{y}, so t↦⟨tx,y⟩t \mapsto \ip{tx}{y} is an additive function of t∈ℝt \in \R. It is continuous, because the norm is continuous, so it equals t⟨x,y⟩t \ip{x}{y}. The norm ∣x1∣+∣x2∣\abs{x_1} + \abs{x_2} on ℝ2\R^2 fails the parallelogram law for x=(1,0)x = (1, 0), y=(0,1)y = (0, 1), since 4+4≠2+24 + 4 \ne 2 + 2, so it comes from no inner product.

Going deeper

For a student

The theorem shows that among the spaces Lp([0,1])L^p([0, 1]) with 1≤p≤∞1 \le p \le \infty, only L2([0,1])L^2([0, 1]) has a norm that comes from an inner product. For p≠2p \ne 2 the parallelogram law fails for the indicator functions of [0,1/2][0, 1/2] and (1/2,1](1/2, 1]. It is a characterization of Hilbert spaces among Banach spaces, because completeness is not affected. The proof is a functional equation argument: the parallelogram law is the quadratic functional equation for f(x)=∥x∥2f(x) = \norm{x}^2, and continuity turns additivity into linearity. The law only involves two vectors at a time, so a norm is an inner product norm as soon as its restriction to every two-dimensional subspace is.

Reading path

To understand this page from the ground up, read these 4 pages in order. The foundations come first.

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Each page uses the pages above it. The colour of the bar on a box shows how strong the evidence is, and the box also gives it as text. The list has the same pages.
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  1. Inner product space concept
  2. Norm induced by an inner product concept
  3. Normed vector space concept
  4. Jordan–von Neumann theorem statement

Further reading

  1. Web https://en.wikipedia.org/wiki/Parallelogram_law
About this page
Tag46WGVM5VS6
URIm2://46WGVM5VS6
Kindstatement, theorem
WritingW0 stub
MSC46C15, 39B52
StatusThis copy of the site has no build data. Run m2 status 46WGVM5VS6.
AboutInner product space, Normed vector space
UsesNormed vector space, Inner product space, Norm induced by an inner product

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