Hilbert space, orthonormal basis

In summary, the conversation discusses the concept of orthonormal bases in Hilbert spaces and the idea of maximality. The quote suggests that a countable orthonormal system in a Hilbert space can be represented as the closure of the span of countably many elements. The context is that this orthonormal system is maximal, meaning that every element in the space can be written as an infinite sum of the orthonormal system's elements. This is a desirable condition and is used to define an orthonormal basis instead of using a convergence condition on finite linear combinations. However, this does not mean that the space is equal to the union of these finite span sets, as shown in the example of the canonical Hilbert space l2
  • #1
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My book says that "the countability of the ONS in a hilbert space H entails that H can be represented as closure of the span of countably many elements". I must admit my english is probably not that good. At least the above quote does not make sense to me. What is it trying to say?
Previously it was talking about orthonormal bases in Hilbert spaces and the idea of maximiality:
<g,e_k> = 0 for al k => g=0 (definition of maximality)
Why is it we use this definition to characterize and orthonormal basis (e_k) and not that H=span(e_k) and how does it relate to the quote above?
 
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  • #2
If you just take a span of an orthonormal system, you are only allowed to have finite linear combinations. Usually H is the closure of the span - which means you can take infinite linear combinations as long as the sums converge.

The quote by itself is a little odd as usually an orthonormal system just means you have a collection of vectors which are pairwise orthogonal and unit length - is the context that you have a countable orthonormal system which is maximal? Because then the quote makes more sense.
 
  • #3
it is. Can you elaborate? I am not sure I understand the idea of maximality. Why use this to define an ONB and not some kind of convergence condition on finite linear combinations?
 
  • #4
The point is that a maximal ONS has that every element of H is an infinite sum of your ONS elementals, which is a really nice thing to have. But we want to prove that we can do this without talking about the topology of the space, so it's really good to have a condition which is just a linear algebra condition.
 
  • #5
Not sure I understand yet:
For an ONS is:
ONS is maximal <=> for all g in H, g=Ʃ<g,e_k>e_k
But not in general H=lim_n->∞[span{(e_k)}] - or does this last statement even make sense?
 
  • #6
By
[tex] \lim_{n\to \infty} span( \{ e_1,...,e_n \}) [/tex]
what you really want to write is
[tex] \bigcup_{n=1}^{\infty} span(\{e_1,...,e_n \} ) [/tex].

And H will not be equal to this in general. Let's take the canonical Hilbert space l2 of sequences [itex](a_1,...,a_n,...)[/itex] such
[tex] \sum_{n=1}^{\infty} a_n^2 [/tex]
converges.

Then a maximal orthonormal system is
[itex] e_1 = (1,0,0,...),\ e_2 = (0,1,0,...),\ e_3 = (0,0,1,0,0,...) [/itex] etc. There are countably many of these. The inner product of [itex] (a_1,a_2,...)[/itex] and [itex] (b_1,b_2,...)[/itex] is
[tex] \sum_{n=1}^{\infty} a_n b_n [/tex].

It should be clear that the en are an orthonormal system, and that <g,en> = 0 for all n implies that g = (0,0,0,...,0,...) is the zero vector. However almost none of the vectors in l2 are in
[tex] \bigcup_{n=1}^{\infty} span( \{e_1,...,e_n \} ) [/tex]
because to be in this set, you have to be a linear combination of finitely many of the en. So for example the vector (1,1/2,1/4,1/8,...) is in l2 but not in that above union, because it is writable as only an infinite linear combination of the ens.
 

1. What is Hilbert space?

Hilbert space is a mathematical concept that represents an infinite-dimensional vector space in which the inner product of two vectors is defined. It is named after the German mathematician David Hilbert.

2. What is an orthonormal basis in Hilbert space?

An orthonormal basis in Hilbert space is a set of vectors that are both orthogonal (perpendicular to each other) and normalized (have a length of 1). This basis is used to represent any vector in the space by taking linear combinations of these basis vectors.

3. How is an orthonormal basis related to the concept of completeness in Hilbert space?

In Hilbert space, a set of vectors is considered complete if any vector in the space can be expressed as a linear combination of those vectors. An orthonormal basis is a complete set of vectors in Hilbert space, meaning that any vector in the space can be represented by a unique linear combination of the basis vectors.

4. Can Hilbert space have a finite or infinite number of dimensions?

Hilbert space can have both finite and infinite dimensions. In the case of a finite-dimensional Hilbert space, the basis vectors are finite and the space can be visualized as a traditional Euclidean space. In contrast, an infinite-dimensional Hilbert space has an infinite number of basis vectors and cannot be visualized in the same way.

5. What are some applications of Hilbert space and orthonormal basis?

Hilbert space and orthonormal basis have various applications in physics, engineering, and mathematics. They are commonly used in quantum mechanics and signal processing to model and analyze systems with infinite degrees of freedom. They are also used in functional analysis, harmonic analysis, and approximation theory.

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