Difference between mixed tensor notation

In summary: Both result in the same quantity, but the first is a one-form and the second is a three-form. In summary, the positioning of the covariant and contravariant indices in a tensor can indicate which index is being used, and for non-symmetric tensors it may affect the type of quantity being represented.
  • #1
blankvin
15
1
Hi,

Can someone explain the difference between, say, [itex] \Lambda_\nu^\mu, {\Lambda_\nu}^\mu [/itex] and [itex] {\Lambda^\mu}_\nu [/itex] (i.e. the positioning of the contravariant and covariant indices)?

I have found: http://books.google.ca/books?id=lLP...onepage&q=mixed tensor index position&f=false but maybe someone can shed some more light on this for me.
 
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  • #2
blankvin said:
Hi,

Can someone explain the difference between, say, [itex] \Lambda_\nu^\mu, {\Lambda_\nu}^\mu [/itex] and [itex] {\Lambda^\mu}_\nu [/itex] (i.e. the positioning of the contravariant and covariant indices)?

I have found: http://books.google.ca/books?id=lLP...onepage&q=mixed tensor index position&f=false but maybe someone can shed some more light on this for me.

I assume the issue is that you have more than one covariant/contravariant index in your tensor, and the different ## \Lambda ## tell you which index you are making use of, i.e., are you
using the 1st covariant index together with the second contravariant, or the 2nd covariant together with the third contravariant, etc.
 
  • #3
blankvin said:
Hi,

Can someone explain the difference between, say, [itex] \Lambda_\nu^\mu, {\Lambda_\nu}^\mu [/itex] and [itex] {\Lambda^\mu}_\nu [/itex] (i.e. the positioning of the contravariant and covariant indices)?

I have found: http://books.google.ca/books?id=lLP...onepage&q=mixed tensor index position&f=false but maybe someone can shed some more light on this for me.

The positions of the indices indicate to you which is the first and second. For a symmetric tensor, it wouldn't matter really, but for a non-symmetric tensor, it might matter which index you raise/lower.

For example: ##F^{\mu}_{~~\nu}=g^{\mu\rho}F_{\rho\nu}## versus ##F^{~~\mu}_\nu=g^{\mu\rho}F_{\nu\rho}##
 
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Related to Difference between mixed tensor notation

1. What is mixed tensor notation?

Mixed tensor notation is a way of representing tensors, which are mathematical objects that describe the relationship between physical quantities. In mixed tensor notation, indices are used to represent the different components of a tensor, with upper indices representing contravariant components and lower indices representing covariant components.

2. What is the difference between upper and lower indices in mixed tensor notation?

In mixed tensor notation, upper indices represent the contravariant components of a tensor, which are affected by changes in coordinate systems. Lower indices, on the other hand, represent covariant components, which are independent of coordinate systems. This distinction is important in understanding how a tensor transforms under a change of coordinates.

3. Can mixed tensor notation be used to represent tensors of any order?

Yes, mixed tensor notation can be used to represent tensors of any order. The number of indices used in the notation corresponds to the order of the tensor. For example, a tensor of order 2 would have two upper and two lower indices, while a tensor of order 3 would have three upper and three lower indices.

4. What is the advantage of using mixed tensor notation?

Mixed tensor notation is advantageous because it allows for a concise and efficient representation of tensors. It also makes it easier to perform calculations and transformations on tensors, as the indices indicate how the components of the tensor are related.

5. Are there any common mistakes made when using mixed tensor notation?

One common mistake when using mixed tensor notation is not keeping track of the indices and their positions. This can lead to errors in calculations and transformations. It is important to pay attention to the placement of indices and their corresponding contravariant or covariant components to ensure accurate results.

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