Understanding Separable Vector Spaces: The Basics Explained

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Discussion Overview

The discussion revolves around the concept of separable vector spaces, particularly in the context of tensor products and their properties. Participants explore definitions, examples, and the implications of separability in various mathematical settings, including finite-dimensional linear algebra and Hilbert spaces.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant questions whether the tensor product of vector spaces is separable, suggesting that it might be if the original spaces are separable.
  • Others clarify that a separable space must contain a countable dense subset, and the product of two vector spaces will not be separable unless both original spaces are separable.
  • There is a discussion about the need for additional structure, such as a norm or topology, to define separability properly.
  • Examples are requested to illustrate what constitutes a countable dense subset in finite-dimensional linear algebra, with references to norms and specific vector spaces like ##\mathbb{R}^3##.
  • One participant explains that in the context of Hilbert spaces, a separable space can be defined as having a countable orthonormal basis, detailing the properties of such a basis.
  • An example of an orthonormal basis in ##\mathbb{C}^3## is provided, illustrating the concept further.

Areas of Agreement / Disagreement

Participants generally agree on the definition of separability requiring a countable dense subset and the necessity of additional structure for proper definition. However, there is ongoing debate about the implications of tensor products and the conditions under which separability is preserved.

Contextual Notes

Some participants note that the notion of separability is not well defined without a topology or additional structure, indicating limitations in the discussion regarding the assumptions made about vector spaces.

Who May Find This Useful

This discussion may be useful for those studying linear algebra, functional analysis, or quantum mechanics, particularly in understanding the properties of separable vector spaces and their applications in various mathematical contexts.

fog37
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Dear forum,

I am trying to understand what a separable vector space is. I know we can perform the tensor product of two or more vector space and obtain a new vector space. Is that vector space separable because it is the product of other vector spaces?

thanks
 
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No. A separable space contains a countable dense subset. The product of two vector spaces will not be separable unless the two original vector spaces were.
 
Orodruin said:
No. A separable space contains a countable dense subset. The product of two vector spaces will not be separable unless the two original vector spaces were.

The notion of a vector space alone is not sufficient for separability to be well defined.
 
Thank you.

What would a countable dense subset be? I understand it contains a subset of vectors that has a particular property. Could you give me an example of what a countable dense subset means from ordinary finite dimensional linear algebra? Let's consider the vector space of vectors
##v=(v_{x} , v_{y}, v_{z})##...
 
fog37 said:
Thank you.

What would a countable dense subset be? I understand it contains a subset of vectors that has a particular property. Could you give me an example of what a countable dense subset means from ordinary finite dimensional linear algebra? Let's consider the vector space of vectors
##v=(v_{x} , v_{y}, v_{z})##...

Dense makes no sense on a vector space only. You'll need further structure, like a norm, a distance or a topology.

For example, the vector space ##\mathbb{R}^3## can be equipped with the norm
\|v\| = \sqrt{v_x^2 + v_y^2 + v_z^2}
A countable dense set can then be given by \{v~\vert~v_x, v_y,v_z\in \mathbb{Q}\}

But let's start with the basics, do you know what a norm is?

Also, where did you encounter the notion of separable? Seeing the context might help.
 
micromass said:
The notion of a vector space alone is not sufficient for separability to be well defined.
Obviously. This is implied by the "dense". Without some sort of topology, this is not well defined.
 
Orodruin said:
Obviously. This is implied by the "dense". Without some sort of topology, this is not well defined.

You know that. I know that. The point is that the OP might not.
 
Hi micromass,

The norm is, conceptually, the "length" of a vector. I run into the idea of separable vector space in introductory quantum mechanics where Hilbert vector space is said to be separable. this leads down to the discussion of such a space being a tensor product of other vector spaces...
 
fog37 said:
Hi micromass,

The norm is, conceptually, the "length" of a vector. I run into the idea of separable vector space in introductory quantum mechanics where Hilbert vector space is said to be separable. this leads down to the discussion of such a space being a tensor product of other vector spaces...

OK, since it's in the context of Hilbert spaces, I can give a simpler definition of separable. All it means is that there is a countable orthonormal basis. That is: there is a subset of the Hilbert space ##\{e_n~\vert~n\in I\}## with ##I## countable, which intuitively means ##I## finite or ##I=\mathbb{N}## such that
1) ##\|e_n\| = 1## for all ##n##
2) ##<e_n, e_m> = 0## for ##n\neq m##
3) Every ##x## in the Hilbert space can be written as ##x = \sum_{n\in I}\alpha_n e_n## for some ##\alpha_n\in \mathbb{C}## (it can be shown that ##\alpha_n =<x,e_n>##). Note this sum is an infinite sum (=series) when ##I=\mathbb{N}## and convergence comes into play, which makes it distinct from linear algebra where all sums are finite.
 
  • #10
As an example in ##\mathbb{C}^3##, take ##(1,0,0)##, ##(0,1,0)##, ##(0,0,1)##. These are orthonormal and form a basis.
 

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