Generators of Product Rep: t_{a}^{R_1 \otimes R_2}

So that should be fine. In summary, to write the generators of the product representation t_{a}^{R_1 \otimes R_2} in terms of t_{a}^{R_1}, t_{a}^{R_2}, we can use the tensor product of the two representations and combine the generators in a way that preserves the correct index structure, either by pairing matching generators or mapping them onto the resulting mn-dimensional representation. The direct product and tensor product are different ways of combining representations, with the direct product resulting in a reducible representation while the tensor product results in a higher rank tensor. Different choices of pairing correspond to a change of basis for the representation.
  • #1
sgd37
213
8

Homework Statement



Write the generators of the product of representation [tex] t_{a}^{R_1 \otimes R_2} [/tex] in terms of [tex] t_{a}^{R_1}, t_{a}^{R_2} [/tex]

Homework Equations



[tex] [t_{a}^{R_i} , t_{b}^{R_i}] = i f_{abc} t_{c}^{R_i} [/tex]

I don't believe that the BCH formula is relevant here since that relates elements within the same representation

The Attempt at a Solution

 
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  • #2
You can figure this out by considering the tensor product of representations as vector spaces. Suppose that [tex]\text{dim}~R_1 = n[/tex], [tex]\text{dim}~R_2 = m[/tex]. Then an element of [tex] R_1[/tex] is an n vector [tex](a_1, \cdots a_n)^T[/tex], while an element of [tex]R_2[/tex] is [tex] (b_1, \cdots b_m)^T[/tex]. To form an element of the product [tex]R_1\otimes R_2[/tex], we construct an [tex]nm[/tex] dimensional vector by replacing each [tex]b_i[/tex] by a vector in [tex]R_1[/tex]. You can determine a basis of generators on [tex]R_1\otimes R_2[/tex] by figuring out how you have to combine the generators on each space to form something that acts properly on the [tex]R_1\otimes R_2[/tex] vectors constructed above.
 
  • #3
well i guess my main hangup is whether the two sets of generators commute, if they do its quite clear that they add
 
  • #4
sgd37 said:
well i guess my main hangup is whether the two sets of generators commute, if they do its quite clear that they add

I'm not sure what you mean here. It doesn't make sense to do ordinary multiplication or addition of matrices of different dimensions.
 
  • #5
That is right (an aside what is the difference between a direct product and a tensor product). So then is it just [tex] t_{a}^{R_1} \otimes t_{a}^{R_2} = t_{a}^{R_1 \otimes R_2} [/tex] it might have the right index structure to transform a [tex] V_{R_1} \otimes V_{R_2} [/tex] tensor but I am unsure about the generator basis index 'a'
 
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  • #6
sgd37 said:
That is right (an aside what is the difference between a direct product and a tensor product). So then is it just [tex] t_{a}^{R_1} \otimes t_{a}^{R_2} = t_{a}^{R_1 \otimes R_2} [/tex] it might have the right index structure to transform a [tex] V_{R_1} \otimes V_{R_2} [/tex] tensor but I am unsure about the generator basis index 'a'

The direct product is the Cartesian product. Since this gives an m+n dimensional representation, it is the same as the direct sum of the representations. The tensor product takes the two vectors from [tex]R_1[/tex] and [tex]R_2[/tex] and forms a matrix [tex]V_{\mu\alpha} = v_\mu v_\alpha[/tex]. The construction I gave above maps this matrix into an mn dimensional vector which is in a reducible representation of the algebra.

The generators that act on [tex]V_{\mu\alpha}[/tex] can be written as

[tex](t_a^{(1)})_{\mu\nu} (t_a^{(2)})_{\alpha\beta},~~\text{no sum on}~a, [/tex]

where we use the indices in the representation spaces to show that this is a higher rank tensor. It's simplest to pair matching generators with the index a, but other choices should just correspond to a change of basis. Alternatively we can map these onto the mn representation to express the generators as ordinary matrices.
 
  • #7
cool thanks for conferring with me you've cleared some things up. But can I mix generators with different group index or am I restricted to like indices even if there is no sum
 
  • #8
sgd37 said:
cool thanks for conferring with me you've cleared some things up. But can I mix generators with different group index or am I restricted to like indices even if there is no sum

A different choices of pairing correspond to different choices of basis elements for the representation.
 

Related to Generators of Product Rep: t_{a}^{R_1 \otimes R_2}

1. What is the purpose of "Generators of Product Rep: t_{a}^{R_1 \otimes R_2}"?

The purpose of "Generators of Product Rep: t_{a}^{R_1 \otimes R_2}" is to describe the transformation of a product representation of a group element. It helps to understand how the product representation changes under a specific type of group operation.

2. How are the generators of product representations calculated?

The generators of product representations are calculated by using the tensor product of two group representations. This involves multiplying the matrices that represent the individual group elements and then finding the eigenvectors and eigenvalues of the resulting matrix.

3. What is the significance of "t_{a}^{R_1 \otimes R_2}" in group theory?

In group theory, "t_{a}^{R_1 \otimes R_2}" represents the transformation of a product representation of a group element. This is important because it allows us to understand the behavior of a group under different operations and how the group elements are related to each other.

4. Can "Generators of Product Rep: t_{a}^{R_1 \otimes R_2}" be applied to any type of group?

Yes, "Generators of Product Rep: t_{a}^{R_1 \otimes R_2}" can be applied to any type of group, as long as the group operations are well-defined and the group elements have corresponding matrices that represent their actions.

5. How does "Generators of Product Rep: t_{a}^{R_1 \otimes R_2}" relate to group representations?

"Generators of Product Rep: t_{a}^{R_1 \otimes R_2}" is related to group representations in that it helps us understand how the product representation of a group element transforms under a specific type of group operation. This information is important in determining the structure and properties of a group representation.

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