Question about inner product spaces

  • Context: Graduate 
  • Thread starter Thread starter AxiomOfChoice
  • Start date Start date
  • Tags Tags
    Inner product Product
Click For Summary

Discussion Overview

The discussion revolves around the properties of inner product spaces, specifically addressing whether an arbitrary vector in such a space can be decomposed into components that are parallel and perpendicular to a fixed vector. The scope includes theoretical aspects of inner product spaces and their dimensionality, including finite and infinite dimensions.

Discussion Character

  • Exploratory, Technical explanation, Conceptual clarification

Main Points Raised

  • One participant proposes that any vector \(\Psi\) in an inner product space \(V\) can be expressed as \(\Psi = \Psi^{\parallel} + \Psi^{\perp}\), where \(\Psi^{\parallel}\) is parallel to a fixed vector \(\Phi\) and \(\Psi^{\perp}\) is perpendicular to \(\Phi\).
  • Another participant asserts that if the inner product is positive definite, the decomposition can be explicitly written as \(\Psi^\parallel = \frac{(\Phi,\Psi)}{(\Phi,\Phi)}\,\Phi\) and \(\Psi^\perp=\Psi-\Psi^\parallel\).
  • A third participant mentions that this decomposition reflects the fact that \(V=<\Phi>\oplus <\Phi>^\perp\), indicating a direct sum of the span of \(\Phi\) and its orthogonal complement.
  • Another contribution references a more general theorem applicable to Hilbert spaces, stating that for any vector \(x\) in a Hilbert space \(H\) and a closed linear subspace \(K\), there exists a unique vector \(y\) in \(K\) such that \(x-y\perp K\), allowing for a similar decomposition.
  • A participant clarifies that the discussion does not assume \(V\) to be a Hilbert space, noting that it need not be complete.

Areas of Agreement / Disagreement

Participants express varying views on the conditions under which the decomposition holds, particularly regarding the completeness of the space. There is no consensus on whether the decomposition is universally applicable to all inner product spaces without additional assumptions.

Contextual Notes

The discussion highlights limitations regarding the assumptions of completeness and the nature of the inner product. The applicability of certain theorems may depend on whether the space is finite or infinite dimensional.

AxiomOfChoice
Messages
531
Reaction score
1
Suppose you have an inner product space [itex]V[/itex] (not necessarily finite dimensional; so it could be an infinite dimensional Hilbert space or something). Fix a vector [itex]\Phi[/itex] in this space. Given an arbitrary vector [itex]\Psi \in V[/itex], can I write it as
[tex] \Psi = \Psi^{\parallel} + \Psi^{\perp},[/tex]
where [itex]\Psi^{\parallel}[/itex] is parallel to the given [itex]\Phi[/itex] and [itex]\Psi^{\perp}[/itex] is perpendicular to the given [itex]\Phi[/itex]?
 
Physics news on Phys.org
If the inner product is positive definite, then you can. Just write:

[tex]\Psi^\parallel = \frac{(\Phi,\Psi)}{(\Phi,\Phi)}\,\Phi[/tex]

[tex]\Psi^\perp=\Psi-\Psi^\parallel[/tex]
 
This is just the fact that

[tex]V=<\Phi>\oplus <\Phi>^\perp[/tex]

where <> denotes the span.
 
The more general theorem says that if x is a member of a Hilbert space H, and K is a closed linear subspace of H, there's a unique y in K such that [itex]x-y\perp K[/itex]. If we define [itex]x_\parallel=y[/itex] and [itex]x_\perp=x-y[/itex], we can write [itex]x=x_\parallel+x_\perp[/itex]. The theorem also says that y is at the minimum distance from x: d(x,y)=d(x,K).

(I'm saying linear subspace to emphasize that it's a subspace of the vector space, not the Hilbert space. A closed linear subspace is a linear subspace that's also a closed set. Some authors use the term "linear subspace" only when the set is closed, and the term "linear manifold" when it may not be closed).
 
@Fredrik: V is not assumed to be a Hilbert space (i.e. need not be complete) in this topic.
 

Similar threads

  • · Replies 13 ·
Replies
13
Views
2K
  • · Replies 10 ·
Replies
10
Views
3K
  • · Replies 5 ·
Replies
5
Views
4K
  • · Replies 13 ·
Replies
13
Views
5K
  • · Replies 3 ·
Replies
3
Views
4K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 14 ·
Replies
14
Views
4K