Example of Kronecker Delta Identity in 3D Matrix R

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The discussion centers on the Kronecker Delta identity applied to a 3D rotation matrix R, specifically the expression R_{ii'}R_{jj'}\delta_{i'j'} = \delta_{ij}. Participants clarify that this involves summing over repeated indices and demonstrate the relationship between matrix multiplication and index notation. The example provided for R is a rotation matrix in 3D, represented as R = \begin{pmatrix} \cos\theta & \sin\theta & 0 \\ -\sin\theta & \cos\theta & 0 \\ 0 & 0 & 1 \end{pmatrix}, which confirms that R R^T equals the identity matrix.

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  • Understanding of Kronecker Delta notation
  • Familiarity with matrix multiplication and transposition
  • Knowledge of 3D rotation matrices
  • Proficiency in index notation and summation conventions
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Kronecker Delta expression

Please, give me an example of this identity using a 3 dimensional matrix R (maybe representing a rotation). My difficulty lies in the indices manipulation.

[tex] R_{ii'}R{jj'}\delta_{i'j'} = \delta_{ij}[/tex]

I know it is obvious, but I'm really stuck in my self-teaching. Thank you.
 
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Are you summing over repeated indices, e.g.
[tex]R_{ii'} R_{jj'} \delta_{i'j'} \text{ means } \sum_{i', j'} R_{ii'} R_{jj'} \delta_{i'j'}?[/tex]
By the definition of matrix multiplication:
[tex]R_{ij} R_{kl} \delta_{jl}= R_{ij} R_{kj} = R_{ij} R_{jk}^T = R_{ij} R_{jk}^T = (R R^T)_{ik}[/tex]
This is important, you should convince yourself of each step. If you must, write it out in matrices and compare each step to the index notation, seeing how operations like multiplying two matrices or taking a transpose translate into operations on the indices.

If this is equal to [itex]\delta_{ik}[/itex] that means that [itex]R R^T[/itex] is the identity matrix. An example of such a matrix is, such as
[tex]R = \begin{pmatrix} \cos\theta & \sin\theta & 0 \\ -\sin\theta & \cos\theta & 0 \\ 0 & 0 & 1 \end{pmatrix}[/tex]

If you want you can explicitly write out all the 9 components of the left hand side (let i and j run and sum over k), and show that you are really just multiplying R by R^T. Or if you are not sadistic, take a 2x2 matrix :)

Sorry if I am too general, but I think it is best if you work through the manipulations yourself.
 
Thank you for the answer. That's exactly what I expected. :)
 

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