Tensor product and representations

In summary: G_{i}}=q^{I}(G_{i})_{I}^{J}(p_{j}+q^{J}_{i})_{i}^{J}First, you need to understand the connection between this and equation (4) in my previous post. In here, ( q^{I} , p_{I} ) are continuous coordinate numbers, i.e. they don’t (directly) span the index space of matrices. However, if we write |Q \rangle = \sum_{I}^{n} q_{I} \ | I \rangle , \ \Rightarrow \ q^{I} = ( q_{I
  • #1
JonnyMaddox
74
1
Hi, I that [itex]<I|M|J>=M_{I}^{J}[/itex] is just a way to define the elements of a matrix. But what is [itex]|I>M_{I}^{J}<J|=M[/itex] ? I don't know how to calculate that because the normal multiplication for matrices don't seem to work. I'm reading a book where I think this is used to get a coordinate representation of a group with a matrix representation as:
[itex]\hat{G_{i}}=q^{I}(G_{i})_{I}^{J}p_{j}[/itex] where q and p are the coordinates and the conjugate momenta.

Can someone give me an easy example? :)
 
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  • #2
JonnyMaddox said:
I'm reading a book
Which book?
 
  • #3
Nugatory said:
Which book?
The bible...no jk I'm reading "Fields" from Warren Siegel. It's free on arxiv.
 
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  • #4
JonnyMaddox said:
Hi, I that [itex]<I|M|J>=M_{I}^{J}[/itex] is just a way to define the elements of a matrix. But what is [itex]|I>M_{I}^{J}<J|=M[/itex] ? I don't know how to calculate that because the normal multiplication for matrices don't seem to work. I'm reading a book where I think this is used to get a coordinate representation of a group with a matrix representation as:
[itex]\hat{G_{i}}=q^{I}(G_{i})_{I}^{J}p_{j}[/itex] where q and p are the coordinates and the conjugate momenta.

Can someone give me an easy example? :)

Consider an abstract, n-dimensional linear vector space spanned by complete and ortho-normal basis vectors, i.e. [tex]\langle I | J \rangle = \delta_{I}^{J} , \ \ \ \ \ (1)[/tex] [tex]\sum_{K}^{n} | K \rangle \langle K | = \mathbb{I}_{n} . \ \ \ \ (2)[/tex] In this n-dimensional (index) space, a [itex]n \times n[/itex] matrix [itex]M[/itex] acts as operator: [tex]M | J \rangle = | M J \rangle = \sum_{K}^{n} M^{J}_{K} \ | K \rangle , \ \ \ (3)[/tex] where the numbers [itex]M^{J}_{I}[/itex] , i.e. the expansion coefficients, are determined from the orthonomality condition (1): [tex]\langle I | M | J \rangle = \sum_{K} M^{J}_{K} \ \delta^{K}_{I} = M^{J}_{I} .[/tex] To construct a matrix representation of operator [itex]M[/itex], we use the completeness relation (2) and the expansion (3): [tex]M \sum_{J} | J \rangle \langle J | = M_{n \times n} = \sum_{I , J} M^{J}_{I} \ | I \rangle \langle J | . \ \ \ (4)[/tex] As an example, consider 2-dimentional index space with basis vectors [tex]| 1 \rangle = \langle 1 |^{ \dagger } = ( 1 \ , \ 0 )^{T} ,[/tex] [tex]| 2 \rangle = \langle 2 |^{ \dagger } = ( 0 \ , \ 1 )^{T} .[/tex] In this case, equation (4) should give a [itex]2 \times 2[/itex] matrix representation for the operator [itex]M[/itex]: [tex]M_{ 2 \times 2 } = \sum_{I , J}^{2} M^{J}_{I} \ | I \rangle \langle J | . \ \ \ (5)[/tex] Indeed, since [tex]| 1 \rangle \langle 1 | = \left( \begin {array} {c c} 1 & 0 \\ 0 & 0 \end {array} \right) , \ \ | 1 \rangle \langle 2 | = \left( \begin{array} {c c} 0 & 1 \\ 0 & 0 \end{array} \right) , [/tex] [tex]| 2 \rangle \langle 1 | = \left( \begin{array} {c c} 0 & 0 \\ 1 & 0 \end{array} \right) , \ \ | 2 \rangle \langle 2 | = \left( \begin{array} {c c} 0 & 0 \\ 0 & 1 \end{array} \right) ,[/tex] equation (5) gives [tex]M_{2 \times 2} = \left( \begin{array} {c c} M^{1}_{1} & M^{2}_{1} \\ M^{1}_{2} & M^{2}_{2} \end{array} \right) .[/tex]

Sam
 
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  • #5
Ok thanks Sam. Could you also help me with coordinate representations? How do I apply this formula
[itex]\hat{G_{i}}=q^{I}(G_{i})_{I}^{J}p_{j}[/itex]
Is this like an inner product of the coordinates and the conjugate momentum?
Like this
[itex]\hat{G_{1}}=q^{1}(G_{1})_{1}^{1}p_{1}+q^{2}(G_{1})_{2}^{2}p_{2}+...[/itex]
 
  • #7
  • #9
JonnyMaddox said:
Ok thanks Sam. Could you also help me with coordinate representations? How do I apply this formula
[itex]\hat{G_{i}}=q^{I}(G_{i})_{I}^{J}p_{j}[/itex]
Is this like an inner product of the coordinates and the conjugate momentum?
Like this
[itex]\hat{G_{1}}=q^{1}(G_{1})_{1}^{1}p_{1}+q^{2}(G_{1})_{2}^{2}p_{2}+...[/itex]

First, you need to understand the connection between this and equation (4) in my previous post. In here, [itex]( q^{I} , p_{I} )[/itex] are continuous coordinate numbers, i.e. they don’t (directly) span the index space of matrices. However, if we write [tex]|Q \rangle = \sum_{I}^{n} q_{I} \ | I \rangle , \ \ \Rightarrow \ q^{I} = ( q_{I} )^{T} = \langle Q | I \rangle ,[/tex] [tex]| P \rangle = \sum_{J}^{n} p_{J} \ | J \rangle , \ \ \Rightarrow \ p_{J} = \langle J | P \rangle ,[/tex] then we can transform equation (4) into equation similar to the one you wrote: [tex]M ( p , q ) \equiv \langle Q | M | P \rangle = \sum_{I , J} M^{J}_{I} \ \langle Q | I \rangle \langle J | P \rangle = \sum_{I , J} M^{J}_{I} \ q^{I} \ p_{J} .[/tex] In fact (see the exercise below) [itex]G^{I}_{J} \equiv i | I \rangle \langle J |[/itex] and [itex]J^{I}_{J} \equiv q^{I} \ p_{J}[/itex] generate “isomorphic” Lie algebras.
Now, let us talk about coordinate representation. Let [itex]G_{a}[/itex] , [itex]a = 1 , 2 , \cdots , m[/itex] be basis in an m-dimensional Lie algebra [itex]\mathcal{L}^{m}[/itex] with the following Lie bracket relations [tex][ G_{a} , G_{b} ] = C_{a b}{}^{c} \ G_{c} . \ \ \ \ \ (1)[/tex] Since every Lie algebra has a faithful matrix representation, we may the [itex]G_{a}[/itex]’s to be a set of [itex](m)[/itex] matrices ([itex]n \times n[/itex]) and, therefore, realizing the Lie brackets by commutation relations [tex][ G_{a} , G_{b} ]^{J}_{I} = C_{a b}{}^{c} \ ( G_{c} )^{J}_{I} , \ \ I , J = 1 , 2 , \cdots , n . \ \ \ (2)[/tex] Now, we take n-pairs of real munbers [itex]( q^{I} , p_{I} )[/itex] and define m numbers (functionals) [itex]J_{a} ( q , p )[/itex] by [tex]J_{a} = ( G_{a} )^{J}_{I} \ q^{I} \ p_{J} , \ \ \ a = 1 , 2 , \cdots , m . \ \ \ \ (3)[/tex] Clearly, the set of numbers [itex]J_{a}[/itex] forms a representation of [itex]\mathcal{L}^{m}[/itex] , i.e. they satisfy a Lie bracket relation. To see this, take [itex]( q^{I} , p_{I} )[/itex] to be local coordinates on Poisson manifold [itex]\mathcal{P}^{2 n}[/itex] and evaluate the Poisson bracket [tex]\{ J_{a} , J_{b} \} = \sum_{K}^{n} \left( \frac{ \delta J_{a} }{ \delta q^{K} } \frac{ \delta J_{b} }{ \delta p_{K} } - \frac{ \delta J_{a} }{ \delta p_{K} } \frac{ \delta J_{b} }{ \delta q^{K} } \right) .[/tex] Using (2) and (3), we find [tex]\{ J_{a} , J_{b} \} = C_{a b}{}^{c} \ J_{c} . \ \ \ \ \ (4)[/tex] Since the structure constants of [itex]\mathcal{L}^{m}[/itex] appear on the RHS of (4), then [itex]\{ J_{a} , J_{b} \}[/itex] is a Lie bracket on [itex]\mathcal{L}^{m}[/itex]. Mathematically speaking, to every (associative) Lie algebra there corresponds a Poisson structure, i.e., the universal enveloping algebra of [itex]\mathcal{L}^{m}[/itex] is a Poisson-Lie algebra.

Okay, now I leave you with the following exercise. Define [tex]M^{I}_{J} = i \ | I \rangle \langle J | , \ \ \mbox{and} \ \ G^{I}_{J} = q^{I} \ p_{J} ,[/tex] then prove the following Lie brackets [tex][ M^{I}_{J} , M^{L}_{K} ] = \delta^{I}_{K} \ M^{L}_{J} - \delta^{L}_{J} \ M^{I}_{K} ,[/tex] [tex]\{ G^{I}_{J} , G^{L}_{K} \} = \delta^{I}_{K} \ G^{L}_{J} - \delta^{L}_{J} \ G^{I}_{K} .[/tex] What is the corresponding Lie group?


Sam
 
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  • #10
Ok I see. Now I understood this:
[itex]A_{ij}|e_{i}><e_{j}|= A_{11}|e_{1}><e_{1}|+A_{21}|e_{2}><e_{1}|+A_{12}|e_{1}><e_{2}|+A_{22}|e_{2}><e_{2}|=A_{11}\begin{pmatrix} 1 & 0 \\ 0 & 0 \end{pmatrix}+A_{21}\begin{pmatrix} 0 & 0 \\ 1 & 0 \end{pmatrix}+A_{12}\begin{pmatrix} 0 & 1 \\ 0 & 0 \end{pmatrix}+A_{22}\begin{pmatrix} 0 & 0 \\ 0 & 1 \end{pmatrix}=[/itex][itex]\begin{pmatrix} A_{11} & A_{12} \\ A_{12} & A_{22} \end{pmatrix}[/itex]
I think I have to wrap my head a little around how he (in his book) uses this in all the different ways it can be used. So when he uses [itex]|^{I}>[/itex] in the context of a vector [itex]V[/itex] it just means [itex]|^{I}>=|e_{i}>[/itex]. Then in the context of matrices or generators he uses it as [itex]|^{I}>=|e_{i}><e_{j}|[/itex]? Same with the conjugate representations and so on.
And I'm right that this equation I asked you about is analogous to this equation with which you can define a regular representation of a finite group:
[itex][D(g)]_{ij}=<e_{i}|D(g)|e_{j}>[/itex]?
Ok I think I have to play a little around with all this and then I will try to solve your exercise. Thank you Sam !
 
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  • #11
Ok I think I'm confused about what [itex]q^{I}[/itex] and [itex]p_{J}[/itex] are. Coordinates and conjugate momentum ok. But are they the basis of the space or what? If not how does this make sense [itex]\hat{G_{i}}= q^{1}(G_{1})_{1}^{1}p_{1}+...[/itex]? So it's just a number or what?
 
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  • #12
JonnyMaddox said:
Ok I think I'm confused about what [itex]q^{I}[/itex] and [itex]p_{J}[/itex] are. Coordinates and conjugate momentum ok. But are they the basis of the space or what?
Did you read the first two lines in post #9 ?
If not how does this make sense [itex]\hat{G_{i}}= q^{1}(G_{1})_{1}^{1}p_{1}+...[/itex]? So it's just a number or what?
Did you read the line just before equation (3) in post #9 ?
 

Related to Tensor product and representations

1. What is a tensor product?

A tensor product is a mathematical operation in which two vector spaces are combined to form a new vector space. It is denoted by the symbol ⊗ and is used to express the relationship between two vector spaces in terms of their basis vectors.

2. How is a tensor product different from a regular product?

A tensor product is different from a regular product in that it is not commutative. This means that the order in which the vector spaces are multiplied matters. Additionally, a tensor product results in a new vector space, while a regular product results in a scalar value.

3. What is the significance of tensor products in representations?

Tensor products are important in representations because they allow for the construction of new representations from existing ones. This is useful in many areas of mathematics and physics, such as in the study of group theory and quantum mechanics.

4. How are tensor products used in quantum mechanics?

In quantum mechanics, tensor products are used to represent composite systems, such as those involving multiple particles or multiple states of a single particle. This allows for the description of complex quantum systems and their interactions.

5. Can a tensor product be visualized?

While it may be difficult to visualize a tensor product directly, it can be thought of as a combination of the two vector spaces, with the resulting vector space containing all possible combinations of the basis vectors of the two original spaces. In some cases, a tensor product can also be represented as a matrix or higher-dimensional array.

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