Schutz - A First Course in GR - Simple Summation Question

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Discussion Overview

The discussion revolves around a summation problem from "A First Course in General Relativity" by Schutz, specifically related to matrix multiplication involving a vector and a matrix. Participants explore the correct approach to compute the product of a vector and a matrix, clarifying the indices involved in the summation process.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Matt expresses confusion over the summation problem and notes discrepancies in his calculations compared to the expected results.
  • Fredrik clarifies that the calculation should involve multiplying the vector A by the matrix C, not the transpose.
  • Matt acknowledges misunderstanding and seeks further clarification on how to arrive at the correct first value of 7.
  • Altabeh explains the correct approach to obtain the first component by treating C as a column vector and performing the multiplication accordingly.
  • Another participant points out a potential discrepancy in the values of the matrix C as presented in different sources.
  • Matt realizes the importance of using the correct indices and appreciates the clarification provided by other participants.
  • A later reply discusses the definitions of matrix multiplication in relation to the dimensions of the matrices involved.

Areas of Agreement / Disagreement

Participants generally agree on the need to correctly interpret the indices in the matrix multiplication process. However, there is some disagreement regarding the specific values in the matrix C as noted by one participant.

Contextual Notes

There are unresolved issues regarding the exact values of the matrix C, as different sources provide conflicting information. Additionally, the discussion highlights the importance of understanding the notation and definitions used in matrix operations.

CFDFEAGURU
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Hello all,

In the book "A First Course in General Relativity" by Schutz (1985 Edition) in chapter 2 there is a problem concerning summation that has me confused.

Note: This is not homework, just an interest of mine.

The given quantities are:

A = (5,0,-1,-6)
B = (0,-2,4,0)

C = [ 1 0 2 3
5 -2 -2 0
4 5 2 -2
-1 -2 -2 0 ]

Find:

A (super alpha) * C (sub alpha, beta); for all beta.

As usual, I apologize for not using LaTex but I can never get it to work right.

My attempt.

The only sum is on alpha because it is the only repeated upper and lower index. I should end up with a set of 4 numbers.

I followed the example given on page 41 of the book and applied it to this problem, but I got all 4 numbers wrong.

For the first value I calculated:

(1)*(5) + (0)*(0) + (2)*(-1) + (3)*(-6) = -15

The answer is given as (7, 1, 26, 17).

Any help on what I am doing wrong would be greatly appreciated.

Thanks
Matt
 
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Matrix multiplication is defined by (AB)_{ij}=A_{ik}B_{kj} (when we write all indices downstairs), so what you're supposed to calculate is AC, not CA^T.
 
Thanks Fredrik,

I know that I am supposed to calculate AC, but I keep getting the wrong values. In the example given in the book, Schutz simply multiplies each row of the matrix (C) with the column vector (A) and then sums the values. Very easy and straightforward. What am I doing different that is causing me to calculate the wrong values.

... not CA^T .

What would make you think that I am trying to calculate A transposed times C?

Thanks
Matt
 
CFDFEAGURU said:
Hello all,

In the book "A First Course in General Relativity" by Schutz (1985 Edition) in chapter 2 there is a problem concerning summation that has me confused.

Note: This is not homework, just an interest of mine.

The given quantities are:

A = (5,0,-1,-6)
B = (0,-2,4,0)

C = [ 1 0 2 3
5 -2 -2 0
4 5 2 -2
-1 -2 -2 0 ]

Find:

A (super alpha) * C (sub alpha, beta); for all beta.

As usual, I apologize for not using LaTex but I can never get it to work right.

My attempt.

The only sum is on alpha because it is the only repeated upper and lower index. I should end up with a set of 4 numbers.

I followed the example given on page 41 of the book and applied it to this problem, but I got all 4 numbers wrong.

For the first value I calculated:

(1)*(5) + (0)*(0) + (2)*(-1) + (3)*(-6) = -15

The answer is given as (7, 1, 26, 17).

Any help on what I am doing wrong would be greatly appreciated.

Thanks
Matt

You are approaching as follows for \beta=1:

T_{\beta}=C_{\alpha\beta}A^{\alpha},

Or in the matrix notation,

T=CA=\left[ \begin {array}{cccc} 1&amp;0&amp;2&amp;3\\ \noalign{\medskip}5&amp;-2&amp;-2&amp;0<br /> \\ \noalign{\medskip}4&amp;5&amp;2&amp;-2\\ \noalign{\medskip}-1&amp;-2&amp;-2&amp;0<br /> \end {array} \right]\left[ \begin {array}{c} 5\\ \noalign{\medskip}0\\ \noalign{\medskip}<br /> -1\\ \noalign{\medskip}-6\end {array} \right] <br /> .

Now decompose the matrix C into four row vectors and select the first one from the left side and lablel it \beta=1. This will give T_1 as

T_1=(1)(5) + (0)(0) + (2)(-1) + (3)(-6) = -15.

This is wrong, because in C_{\alpha\beta}, \alpha and \beta represent, respectively, the row and column number so that C_{\alpha1}, would be a column vector, while you choose the row vector to have the matrix relation hold. While this sounds correct that the matrix representation gives the result as yours, but in tensor notation we are encountering number-by-number, i.e. component-by-component, multiplication not vector-by-vector multiplication!

AB
 
Thanks Altabeh, I understand that I am doing something wrong. Could you please show how the first value of 7 is obtained?

Thanks
Matt
 
CFDFEAGURU said:
Thanks Altabeh, I understand that I am doing something wrong. Could you please show how the first value of 7 is obtained?

Thanks
Matt

...so that, C_{\alpha1} would be a column vector...

This means that

C_{\alpha1}=\left[ \begin {array}{c} 1\\ \noalign{\medskip}5\\ \noalign{\medskip}<br /> 4\\ \noalign{\medskip}-1\end {array} \right].

Multiplying each component by the corresponding component of the vector A gives

T_1=(1)(5)+(5)(0)+(4)(-1)+(-1)(-6)=7.

Do a similar calculation to get other components of the vector T.

AB
 
The version on Google Books has C_{31}=-1 and C_{32}=-3 (exercise 2.9, 1), rather than -2 and -2.
 
Yes, you are correct. I do have the wrong values :redface:

Thanks a lot for the help. I didn't realize in the example problem you would get the same answer using the column as you would using the row.

Now it all makes sense.

Thanks a lot everyone.

Now I know why Fredrik thought I was calculating the tranpose of CA

Matt
 
I guess this is a little late, but if A is a 4×1 matrix, what we get from the definition of matrix multiplication is

(CA^T)_i=C_{ij}A^T_j=C_{ij}A_j

and

(AC)_i=A_jC_{ji}
 

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