I can't verify a relationship between cofactor and determinant

In summary, the cofactor of an element of a metric is derived. However, it is possible that the cofactor is a typo and the page should be updated to reflect this.
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Kisok
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In "General Relativity" by Hobson, et. al., in p. 66, we find a sentence starting "If we denote the value of the determinant ... " in the lower part of the page. I can not verify this assertion. Please help me the verification.
On that sentence, cofactor of an element of a metric is derived. But I can not verify it. Here I attached the copy of the page.
 

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It’s because the inverse of ##g_{\mu\nu}## is ##g^{\mu\nu}##, and the inverse of a matrix is given by the matrix of cofactors divided by the determinant.
 
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  • #4
Rund and Lovelock ("Tensors, Differential Forms, and Variational Principles") have a good section on this in chapter 4

I hope you are familiar with Levi-Civita pseudo-tensors (https://en.wikipedia.org/wiki/Levi-Civita_symbol)

The determinant of the n-by-n matrix ##g_{\alpha\beta}## is given by:

##g = \epsilon^{\mu_1,\dots,\mu_n}g_{1\mu_1}\dots g_{n\mu_n}##

Now consider the following object:

##\omega^{\alpha\beta}=\sum_s\delta^\beta_s \epsilon^{\mu_1,\dots,\mu_{s-1},\alpha,\mu_{s+1},\dots,\mu_n}g_{1\mu_1}\dots g_{s-1,\mu_{s-1}}g_{s+1,\mu_{s+1}}\dots g_{n\mu_n}##

##g_{\kappa,\alpha}\omega^{\alpha\beta}=\sum_s \delta^\beta_s \epsilon^{\mu_1,\dots,\mu_n}g_{1\mu_1}\dots g_{s-1,\mu_{s-1}}\: g_{\kappa,\mu_s} \:g_{s+1,\mu_{s+1}}\dots g_{n\mu_n}##

Due to anti-symmetry of Levi-Civita, the only non-zero term in the ##\sum_s## is the one with ##s=\kappa##, but thet term is only non-zero if ##s=\beta=\kappa##. Now if all of this works, then we get the earlier expression for the determinant, so:

##g_{\kappa,\alpha}\omega^{\alpha\beta}=g\delta^\beta_\kappa##

So ##\omega^{\alpha\beta}=g g^{\alpha\beta}##, the inverse times the determinant. The co-factor matrix is here somewhere, but you don't need it to proceed. Note that from the above definition of the determinant

##\partial_c g = \partial_c g_{\beta \alpha}\sum_s\delta^\beta_s \epsilon^{\mu_1,\dots,\mu_{s-1},\alpha,\mu_{s+1},\dots,\mu_n}g_{1\mu_1}\dots g_{s-1,\mu_{s-1}}g_{s+1,\mu_{s+1}}\dots g_{n\mu_n} = g g^{\beta\alpha} \partial_c g_{\alpha\beta}##

Which is what you were after (once we use ##g_{\alpha\beta}=g_{\beta\alpha}##)
 
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Thank you for all the replies there. I will study the precious information and suggestions given by all of you. :smile:
 
  • #6
Cryo said:
gαβ
Cryo said:
Rund and Lovelock ("Tensors, Differential Forms, and Variational Principles") have a good section on this in chapter 4

I hope you are familiar with Levi-Civita pseudo-tensors (https://en.wikipedia.org/wiki/Levi-Civita_symbol)

The determinant of the n-by-n matrix ##g_{\alpha\beta}## is given by:

##g = \epsilon^{\mu_1,\dots,\mu_n}g_{1\mu_1}\dots g_{n\mu_n}##

Now consider the following object:

##\omega^{\alpha\beta}=\sum_s\delta^\beta_s \epsilon^{\mu_1,\dots,\mu_{s-1},\alpha,\mu_{s+1},\dots,\mu_n}g_{1\mu_1}\dots g_{s-1,\mu_{s-1}}g_{s+1,\mu_{s+1}}\dots g_{n\mu_n}##

##g_{\kappa,\alpha}\omega^{\alpha\beta}=\sum_s \delta^\beta_s \epsilon^{\mu_1,\dots,\mu_n}g_{1\mu_1}\dots g_{s-1,\mu_{s-1}}\: g_{\kappa,\mu_s} \:g_{s+1,\mu_{s+1}}\dots g_{n\mu_n}##

Due to anti-symmetry of Levi-Civita, the only non-zero term in the ##\sum_s## is the one with ##s=\kappa##, but thet term is only non-zero if ##s=\beta=\kappa##. Now if all of this works, then we get the earlier expression for the determinant, so:

##g_{\kappa,\alpha}\omega^{\alpha\beta}=g\delta^\beta_\kappa##

So ##\omega^{\alpha\beta}=g g^{\alpha\beta}##, the inverse times the determinant. The co-factor matrix is here somewhere, but you don't need it to proceed. Note that from the above definition of the determinant

##\partial_c g = \partial_c g_{\beta \alpha}\sum_s\delta^\beta_s \epsilon^{\mu_1,\dots,\mu_{s-1},\alpha,\mu_{s+1},\dots,\mu_n}g_{1\mu_1}\dots g_{s-1,\mu_{s-1}}g_{s+1,\mu_{s+1}}\dots g_{n\mu_n} = g g^{\beta\alpha} \partial_c g_{\alpha\beta}##

Which is what you were after (once we use ##g_{\alpha\beta}=g_{\beta\alpha}##)
Thank you so much. Not being able to prove this was driving me crazy.

Oh, and I believe that ##\omega^{\alpha\beta}## is the co-factor. (I am new to this forum and may not have yet figured out how to express omega to the alpha, beta correctly.
 
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matrixbud said:
(I am new to this forum and may not have yet figured out how to express omega to the alpha, beta correctly.
You have figured it out! :smile:
 
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1. What is a cofactor?

A cofactor is a number that is multiplied by a matrix to produce another matrix. It is typically used in the calculation of the determinant of a matrix.

2. What is a determinant?

A determinant is a value that can be calculated from a square matrix. It is used to determine whether a matrix has an inverse and is also used in solving systems of linear equations.

3. How are cofactors and determinants related?

Cofactors are used in the calculation of determinants. The determinant of a matrix can be found by multiplying each element in a row or column by its corresponding cofactor and then summing the results.

4. Can a cofactor be zero?

Yes, a cofactor can be zero if the corresponding element in the matrix is zero. This can happen if there is a row or column of zeros in the matrix, or if the matrix is singular and does not have an inverse.

5. Is there always a relationship between cofactors and determinants?

No, there is not always a relationship between cofactors and determinants. This is because the calculation of cofactors and determinants depends on the size and properties of the matrix, and not all matrices have cofactors or determinants that can be easily calculated.

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