How Is the Determinant of a 4x4 Electromagnetic Tensor Calculated?

In summary: FαβFθλ FμηFσω εαβθλ εμησω= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω= (1/8)^2 Fαβ Fμη Fθλεαβθλ Fσωεμησω= (1/8)^2 Fαβ Fμη Fθλεαβθλ Fσωεμησω= (1/8)^2 Fαβ Fμη Fθλεαβθλ Fσωεμησω= (
  • #1
zn5252
72
0
hi there,
In this wikipedia article https://en.wikipedia.org/wiki/Electromagnetic_tensor
we have the following invariant :

FαβFμη εαβμη = 8 E*B

However the determinant is the square of this quantity divided by 8, i.e. ( E*B )2 .

Now from the definition of the determinant for a 4x4 matrix , we have :

MiaMjbMkcMid εijkl = εabcd det(M) [D]

Now If I raise the expression 1/8 FαβFμη εαβμη to the power of 2, I would get :

1/8 FαβFμη εαβμη 1/8 FθλFσω εθλσω [E]

Now If I compare this expression with equation D above, I see that some indices do not fall into the right place and also in Equation D, we have the expression for the determinant , however in expression E, we see that we have the matrix F multiplied 4 times much like in expression D (or is it rows or columns that get multiplied).

We should also bear in mind that the magnetic field is the spatial part of F and that the electric field is the time part :

Fi0 = Ei and Fijεijk = Bk

How can we reconcile expression E with D then ? or is this an error perhaps ?
 
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  • #2



Hello there,

Thank you for bringing this to my attention. After reviewing the equations and information in the Wikipedia article, I believe there may be a misunderstanding in how the determinant is being applied.

In equation D, the determinant is being applied to a 4x4 matrix M, while in equation E, the determinant is being applied to a 2x2 matrix formed from the product of two 2x2 matrices (1/8 FαβFμη and 1/8 FθλFσω). This is why the indices do not match up. Additionally, the determinant in equation D is being multiplied by the Levi-Civita symbol εabcd, while in equation E, the determinant is being multiplied by εθλσω.

To reconcile expression E with D, we can rewrite equation E as:

(1/8)^2 FαβFμη FθλFσω εαβμη εθλσω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (1/8)^2 FαβFθλ FμηFσω εαβθλ εμησω

= (
 

FAQ: How Is the Determinant of a 4x4 Electromagnetic Tensor Calculated?

What is a determinant of a 4x4 tensor?

The determinant of a 4x4 tensor is a mathematical concept used to describe the size, shape, and orientation of a four-dimensional object. It is a single number that represents the scaling factor of the object when it is transformed by a linear transformation.

How is the determinant of a 4x4 tensor calculated?

The determinant of a 4x4 tensor can be calculated using the Leibniz formula, which involves multiplying the elements of the tensor by their corresponding cofactors and then summing them up. Another method is to use the Gaussian elimination method to reduce the tensor to an upper triangular form and then multiply the diagonal elements to get the determinant.

What does the determinant of a 4x4 tensor tell us?

The determinant of a 4x4 tensor provides important information about the object, such as its volume, whether it is invertible or non-invertible, and the direction of the axes after transformation. It also plays a crucial role in solving systems of linear equations and finding eigenvalues and eigenvectors.

Can the determinant of a 4x4 tensor be negative?

Yes, the determinant of a 4x4 tensor can be negative. The sign of the determinant indicates the orientation of the object after transformation. A negative determinant indicates that the transformation resulted in a reflection or a change in orientation of the axes.

What are some applications of the determinant of a 4x4 tensor?

The determinant of a 4x4 tensor has various applications in mathematics, physics, and engineering. It is used in computer graphics to manipulate 3D objects, in quantum mechanics to describe the state of a system, and in fluid dynamics to solve Navier-Stokes equations. It also has applications in robotics, control systems, and coding theory.

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