Outer product in Hilbert space

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Discussion Overview

The discussion revolves around the properties of the outer product in Hilbert spaces, particularly focusing on whether the outer product operation can generate all linear self-maps of a Hilbert space. Participants explore the implications of this operation in finite-dimensional spaces and the nature of tensor products.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions whether the outer product operation from a Hilbert space to its dual can cover all linear self-maps, suggesting that not all matrices can be formed this way.
  • Another participant rephrases the question to inquire about the nature of the outer product of a Hilbert space with its dual.
  • A different viewpoint suggests that the tensor product of two Hilbert spaces can indeed represent all linear maps, proposing that each linear map can be constructed from a superposition of outer products of basis vectors.
  • Some participants express skepticism about the claim that the entire space of matrices can be constructed from tensor products, arguing that only a subset of the tensor product space can be formed this way.
  • One participant raises the question of what the set of products of column and row vectors represents, asserting that it does not equal the full space of matrices.
  • Another participant emphasizes that while tensor products form a basis for the product space, not every element can be expressed as a simple tensor product of two vectors from the original spaces.
  • Concerns are raised about the dimensionality of the tensor product space, with participants noting that it is not simply the product of the dimensions of the original spaces.
  • One participant asks whether it is possible to identify a subset of the tensor product space that can be expressed as a tensor product of two vectors from the original spaces.

Areas of Agreement / Disagreement

Participants express differing views on the capabilities of the outer product and tensor product operations. There is no consensus on whether all linear self-maps can be formed from outer products, and the discussion remains unresolved regarding the dimensionality and structure of the resulting spaces.

Contextual Notes

Participants note limitations in their arguments, including assumptions about the nature of the spaces involved and the definitions of linear combinations versus tensor products. The discussion highlights the complexity of the relationships between these mathematical structures.

jdstokes
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A question arose to me while reading the first chapter of Sakurai's Modern Quantum Mechanics. Given a Hilbert space, is the outer product [itex]\mathcal{H}\times \mathcal{H}^\ast \to End(\mathcal{H}); (| \alpha\rangle,\langle \beta|)\mapsto | \alpha\rangle\langle \beta|[/itex] a surjection? Ie, can any linear self-map of H be formed by tacking together a suitable ket and bra?

After thinking about this a bit longer I realize the answer is no. If we think about a n-dimensional Hilbert space (n < oo), then the outer product operation corresponds to matrix multiplication of a column vector with a row vector. Clearly not all n x n matrices can be formed in this way. I'm not sure quite how many matrices you can cover in this manner, however.
 
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I'd like to rephrase my question, what is the outer product of [itex]\mathcal{H}[/itex] with [itex]\mathcal{H}^\ast[/itex] equal to, where [itex]\mathcal{H}[/itex] is any Hilbert space.
 
The simplest thing to imagine is that you take a basis of H, call it B, and you take a basis of H', call it B'. You now consider the set product B x B' (that is, all possible couples with first element in B and second element in B'). Well, B x B' is a basis of H (x) H'.

Of course, that's not the nicest mathematical definition, because you should now show that you always span the same space, independent of the choices of B and B' and so on. But it comes closest to the PHYSICAL reason of why H (x) H' is the hilbert space of a combined system.

Indeed, a basis of the hilbert space of a system gives you normally an exhaustive list of mutually exclusive states of that system, and the whole statespace is then obtained by a superposition of all of these states.

Well, the exhaustive list of mutually exclusive states of a combined system is of course the set product of the mutually exclusive states of system 1 and the mutually exclusive states of system 2 (for each state of system 1, we can have all the states of system 2).

This then constructs the basis B x B'. And applying superposition gives you the spanned vector space, H (x) H'.

EDIT: oops, I re-read your message, and what I wrote is not the answer to that...
I think that the tensor product (outer product) of H with H* IS equal to End(H). Indeed, thinking of each End(H) as a matrix, you can obtain it by a superposition of matrices which are 0 everywhere except for one single element, where they are 1, and that's nothing else but the representation of (0, 0, 0,...0,1,0,...0) x (0,0,...0,1,0,...0)' (or |alpha> < beta| if you want to, where alpha and beta are basis vectors).
 
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Are you sure about this? It seems rather strange to me that we can construct the entire [itex]M_n(\mathbb{C})[/itex] an ([itex]n^2[/itex]-dimensional space) by tensor multiplying [itex]\mathbb{C}^n[/itex] and [itex](\mathbb{C}^n)^\ast[/itex] (both n-dimensional).

I guess what you're doing is kind of forbidden by my construction [itex]\mathcal{H}\times \mathcal{H}^\ast \to End(\mathcal{H}); (| \alpha\rangle,\langle \beta|)\mapsto | \alpha\rangle\langle \beta|[/itex]. I wasn't considering the possibility of adding up various outer products of vectors (only one multiplication was allowed, no addition).
 
Another way of asking my question is:

What is the set [itex]\{ v \cdot m \in M_n(\mathbb{C}) | v\in \mathbb{C}^{n\times 1}, w \in \mathbb{C}^{1\times n} \}[/itex] equal to? It's certainly not [itex]M_n(\mathbb{C}) = End(\mathbb{C}^n)[/itex].

That notation indicates column and row vectors, respectively. The dot indicates matrix multiplication.
 
jdstokes said:
Are you sure about this? It seems rather strange to me that we can construct the entire [itex]M_n(\mathbb{C})[/itex] an ([itex]n^2[/itex]-dimensional space) by tensor multiplying [itex]\mathbb{C}^n[/itex] and [itex](\mathbb{C}^n)^\ast[/itex] (both n-dimensional).

I guess what you're doing is kind of forbidden by my construction [itex]\mathcal{H}\times \mathcal{H}^\ast \to End(\mathcal{H}); (| \alpha\rangle,\langle \beta|)\mapsto | \alpha\rangle\langle \beta|[/itex]. I wasn't considering the possibility of adding up various outer products of vectors (only one multiplication was allowed, no addition).

But the tensor product of an n-dimensional space with an m-dimensional space is an nxm dimensional space ! That is exactly because not all elements of the tensor product space are of the form a (x) b. In fact, only a small subset is, and that subset is not a linear space.
 
jdstokes said:
Another way of asking my question is:

What is the set [itex]\{ v \cdot m \in M_n(\mathbb{C}) | v\in \mathbb{C}^{n\times 1}, w \in \mathbb{C}^{1\times n} \}[/itex] equal to? It's certainly not [itex]M_n(\mathbb{C}) = End(\mathbb{C}^n)[/itex].

That notation indicates column and row vectors, respectively. The dot indicates matrix multiplication.

This set is the set of product states. It is not a linear space, as it is not closed under addition. But it spans the tensor product space. That is, the closure of this set under addition is the tensor product space.
 
It is true that all possible tensor products of the basis elements form a basis of the product space. It is not true, however, that every element of the product space can be expressed as a tensor product of two vectors from the original space. In general, elements of the product space are linear combinations of tensor products of vectors in the original space.

For example, take a 3-dimensional vector space V spanned by {i, j, k}. Clearly, VxV is spanned by the nine tensor products {ii, ij, ik, ji, jj, jk, ki, kj, kk}. But any two particular members of V have only six degrees of freedom between them: (a,b,c) and (d,e,f). Therefore, not every member of VxV can be decomposed into a tensor product between two members of V.
 
vanesch said:
But the tensor product of an n-dimensional space with an m-dimensional space is an nxm dimensional space ! That is exactly because not all elements of the tensor product space are of the form a (x) b. In fact, only a small subset is, and that subset is not a linear space.

Given, the tensor product space, can one find this subset which can be written in the form a(x)b?

I think this question makes sense when the initial two spaces ( n-dimensional space and m-dimensional space) are subspace of two larger spaces. And hence, the tensor product space is also a subspace in an larger space.

for eg. The two initial spaces are 2 dimensional subspaces in 3 dimensional space. So the tensor product will span a 4d subspace in a 9 dimensional space. Given this tensor product space, is it possible to find the subset which can be written in the form a(x)b?
 

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