Summation Convention for 2 Vectors

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Homework Help Overview

The discussion revolves around the summation convention applied to two vectors, X and Y, represented in matrix form. The original poster expresses confusion regarding a specific computation involving the product XiYj, particularly in the context of raising and lowering indices using a given metric signature.

Discussion Character

  • Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants explore the interpretation of the notation and the operations required, with some suggesting that the computation involves a tensor of rank 2. Questions arise about whether the notation implies a straightforward multiplication or if it requires a more complex operation.

Discussion Status

There is an ongoing exploration of the problem, with participants providing insights into how to approach the computation. Some suggest breaking down the multiplication into individual components, while others question the clarity of the problem statement itself. No consensus has been reached regarding the exact interpretation of the task.

Contextual Notes

Participants note the potential ambiguity in the problem statement and the implications of the notation used. There is also mention of the constraints imposed by the exercise set, including the use of a specific metric for index manipulation.

BHL 20
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From an exercise set on the summation convention: X and Y are given as [Xi] = \begin{pmatrix}
1\\ 0\\ 0\\ 1\end{pmatrix} and [Yi] = \begin{pmatrix} 0\\ 1\\ 1\\ 1\end{pmatrix} There are a few questions involving these vectors. The one I am stuck on asks to compute XiYj . It may be necessary to raise lower indices in the question, the book that this question comes from uses a metric with signature ( - + + + ) for doing this.
I have no attempt, I have no idea what the question actually wants. I thought there is only a summation if the indices are the same and matrix multiplication is obviously not an option
 
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BHL 20 said:
From an exercise set on the summation convention: X and Y are given as [Xi] = \begin{pmatrix}
1\\ 0\\ 0\\ 1\end{pmatrix} and [Yi] = \begin{pmatrix} 0\\ 1\\ 1\\ 1\end{pmatrix} There are a few questions involving these vectors. The one I am stuck on asks to compute XiYj .

x^iy^j is the tensor of rank 2 (square matrix) which has x^i y^j at row i, column j.
 
Last edited by a moderator:
So in other words it's a YXT operation that's required. I am quite confused by your answer, is it supposed to be evident from the notation that this is the thing to do?
 
BHL 20, please don't adorn your text with size tags.
 
BHL 20 said:
So in other words it's a YXT operation that's required. I am quite confused by your answer, is it supposed to be evident from the notation that this is the thing to do?

Maybe you should post the exact problem statement. "Compute ##X^i Y^j##" doesn't make much sense to me. Does it mean "compute ##X^iY^j## for all i,j? Then the straightforward way is to just do these multiplications one at a time: ##X^0Y^0=1\cdot 0=0##, ##X^1Y^0=0\cdot 0=0##,... The results of these 16 calculations can be arranged in a matrix, which for all i,j, has ##X^iY^j## on row i, column j (and the results can be arranged in other ways as well), but you shouldn't be required to present the result in the form of a matrix.

If you really want to, you can use the definition of matrix multiplication in the following way. For all i,j, we have
$$(XY^T)^i{}_j =\sum_{k=0}^0 X^i{}_k (Y^T)^k{}_j = X^i{}_0 Y^j{}_0 =X^i Y^j.$$
 
Thanks Fredrik, I see now.
 

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