Writing Tensor Equations in Matrix Form

In summary, the tensor equation F'^{\mu\nu}=\Lambda^{\mu}_{\sigma}\Lambda^{\nu}_{ \rho }F^{\sigma\rho} can be expressed in matrix form as F' = \Lambda F \Lambda^{\top} or F' = \Lambda^{\top} F \Lambda, depending on how the tensors are mapped to matrices. It is important to be clear about the notation used, particularly when dealing with mixed tensors.
  • #1
lugita15
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I'm trying to express the tensor equation [itex]F'^{\mu\nu}=\Lambda^{\mu}_{\sigma}\Lambda^{\nu}_{ \rho }F^{\sigma\rho}[/itex] in matrix form. Here the indices range from 0 to 3, so we need 4 by 4 matrices. Let F', F, and [itex]\Lambda[/itex] be the matrices associated with the tensors appearing in our equation. Which of the following is the correct matrix translation of the tensor equation?

[itex]F'=\Lambda F \Lambda[/itex]

[itex]F'=\Lambda \Lambda F[/itex]

[itex]F'=\Lambda^{\top} F \Lambda[/itex]

[itex]F'=\Lambda F \Lambda^{\top}[/itex]

Or something else entirely?

I tried testing some of these out on the actual four-by-four matrices, but the algebra got too cumbersome. Usually when I figure out what order to put things in and where to put the transposes, I'm in a situation where I'm dealing with matrices and vectors, so that if you put it in the wrong order then the numbers of rows and columns don't match up. But in this case everything is four-by-four, so there is plenty of room for error.

Any help would be greatly appreciated.

Thank You in Advance.
 
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  • #2
lugita15 said:
I'm trying to express the tensor equation [itex]F'^{\mu\nu}=\Lambda^{\mu}_{\sigma}\Lambda^{\nu}_{ \rho }F^{\sigma\rho}[/itex] in matrix form.

[itex]F'=\Lambda^{\top} F \Lambda[/itex]

[itex]F'=\Lambda F \Lambda^{\top}[/itex]

It will be one of these two, depending on how you decide to map your tensors to matrices.

You see, a tensor and a matrix are not quite the same thing. A matrix is most naturally thought of as a "mixed" tensor, with one index up and one down: [itex]M^a{}_b[/itex]. Then the matrix product is quite natural to write:

[itex]M^a{}_c = K^a{}_b L^b{}_c[/itex]

On the other hand, a tensor with two "up" indices is technically considered a column vector whose elements are column vectors. However, the multiplication algorithm will end up being the same as matrix multiplication. To translate it to matrices, you just need to follow the indices carefully:

[tex]\Lambda^a{}_c \Lambda^b{}_d F^{cd} = \Lambda^a{}_c F^{cd} \Lambda^b{}_d = \Lambda^a{}_c F^{cd} (\Lambda^\top)_d{}^b[/tex]
where in the last step, we take the transpose because we need to switch the order of b and d to make it look like a matrix product. So we can write

[tex]F' = \Lambda F \Lambda^\top[/tex]
provided we interpret the first index of F as a row index, and the second as a column index.

However, you should be careful with this notation to be clear what you mean. If we had a mixed tensor [itex]G^a{}_b[/itex], then in matrix notation its transformation would be

[tex]G' = \Lambda G \Lambda^{-1}[/tex]
For the pure "up" tensor [itex]F^{ab}[/itex], the most mathematically-correct way to write its transformation law is

[tex]F' = (\Lambda \otimes \Lambda) \cdot F[/tex]
where now F is unfolded into a single column vector with [itex]n \times n[/itex] entries.
 

1. What are tensor equations?

Tensor equations are mathematical equations that involve tensors, which are multi-dimensional arrays used to represent mathematical objects such as vectors and matrices. Tensors allow for the manipulation of complex data and are commonly used in fields such as physics and engineering.

2. Why is it important to write tensor equations in matrix form?

Writing tensor equations in matrix form allows for easier manipulation and computation. Matrices provide a more compact and organized way to represent and solve tensor equations, making them more efficient and practical for real-world applications.

3. How do you convert tensor equations to matrix form?

To convert a tensor equation to matrix form, you first need to identify the tensors involved and their corresponding dimensions. Then, you can create a matrix by organizing the tensors' components in a specific order according to the equation's rules. Finally, you can perform matrix operations to solve the equation.

4. Can all tensor equations be written in matrix form?

No, not all tensor equations can be written in matrix form. Some equations may involve higher-dimensional tensors or operations that cannot be represented using matrices. In these cases, other mathematical tools, such as tensor calculus, may be used to solve the equation.

5. Are there any limitations to writing tensor equations in matrix form?

While writing tensor equations in matrix form can be beneficial in many cases, there are limitations to this approach. Matrices are only suitable for representing and solving certain types of equations, and they may not be as accurate or efficient as other methods for more complex problems. It is important to understand when and how to use matrix form to avoid potential errors or inaccuracies in the solution.

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