How Do Indices Affect Tensor Notation?

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Discussion Overview

The discussion centers around the interpretation of indices in tensor notation, specifically the differences between tensors with upper and lower indices, such as ##{T^{\mu}}_{\nu}## and ##{T_{\nu}}^{\mu}##. Participants explore the implications of these indices in terms of their roles as covariant and contravariant, as well as their potential representation in matrix form.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants note that the upper index denotes contravariance and the lower index denotes covariance, rather than rows and columns.
  • Others argue that the order of indices is significant, as seen in the difference between ##{T^{\mu}}_{\nu}## and ##{T_{\nu}}^{\mu}##, which both have the same contravariant and covariant nature but differ in index order.
  • A participant expresses confusion about interpreting the indices in terms of matrix elements, questioning whether the contravariant index corresponds to rows and the covariant index to columns.
  • Some participants suggest that while tensors can be visualized as matrices, the focus should remain on the covariant and contravariant nature of the indices.
  • A later reply emphasizes a perspective from a Wiki article, stating that an (m+n)-tensor acts on m vectors and n covectors, highlighting its multilinearity.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the interpretation of indices in terms of rows and columns, with multiple competing views presented regarding the significance of the upper and lower indices.

Contextual Notes

Some limitations include the dependence on definitions of covariant and contravariant indices, as well as the unresolved nature of how these indices relate to matrix representations.

spaghetti3451
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I have learned that there is a difference between the tensors ##{T^{\mu}}_{\nu}## and ##{T_{\nu}}^{\mu}##.

Does the upper index denote the rows and the lower index the columns?
 
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They are not the same. However they are both mixed tensors. You read more about them here:

https://en.wikipedia.org/wiki/Mixed_tensor

The upper index doesn't denote a row or column similarly for the lower index, instead they denote whether its a covariant (lower) index or a contravariant (upper) index.
 
I get it: the two important properties of the indices of a tensor are its order in the list of indices and its contravariance/covariance.

For example, the tensors ##{T^{\mu}}_{\nu}## and ##{T_{\nu}}^{\mu}## differ from from each other (even though the index ##\mu## is contravariant in both cases and the index ##\nu## is covariant in both cases) since the order of the indices is different. Am I correct?
 
The u,v naming doesn't really matter as you could have written them as:

##{T^{\mu}}_{\nu}## and ##{T_{\mu}}^{\nu}##

What's important is the upper and lower order ie ##\mu##, the first index is upper and ##\nu##, the second is lower for the first mixed tensor ##{T^{\mu}}_{\nu}##.
 
Last edited:
I am still wondering, though, how to interpret the indices of ##{T^{\mu}}_{\nu}## and ##{T_{\nu}}^{\mu}## in terms of rows and columns.

For example, by convention, the vector ##A^{\mu}## is a column vector, so that the index ##\mu## denotes the row number of the vector.

On the other hand, the dual vector ##A_{\mu}## is a row vector, so that the index ##\mu## now denotes the column number of the vector.

Coming back to ##{T^{\mu}}_{\nu}##, does ##\mu##, being the contravariant index, denote the row number and ##\nu##, being the covariant index, denote the column number of the matrix?

What role does the upper and lower order of the indices serve in terms of the interpretation as matrix elements?
 
I think visually you can lay the tensor out like a matrix with rows and columns. However people tend to use the indices alone and not worry about comparing it to a matrix in that way.

Basically, you don't want to lose sight of the covariant/contravariant nature of each indice.

Here's a writeup on tensor notation where you can see that they use matrix notation for some covariant tensors:

http://www.continuummechanics.org/cm/tensornotationbasic.html

Perhaps @Mark44 can add something here too.
 
Last edited:
failexam said:
I am still wondering, though, how to interpret the indices of ##{T^{\mu}}_{\nu}## and ##{T_{\nu}}^{\mu}## in terms of rows and columns.

For example, by convention, the vector ##A^{\mu}## is a column vector, so that the index ##\mu## denotes the row number of the vector.

On the other hand, the dual vector ##A_{\mu}## is a row vector, so that the index ##\mu## now denotes the column number of the vector.

Coming back to ##{T^{\mu}}_{\nu}##, does ##\mu##, being the contravariant index, denote the row number and ##\nu##, being the covariant index, denote the column number of the matrix?

What role does the upper and lower order of the indices serve in terms of the interpretation as matrix elements?

I would say a clearer perspective is the one taken from the Wiki article: that an (m+n)-tensor acts on m vectors and n covectors (meaning differential forms), and it is multilinear, i.e., linear on each variable.
 
jedishrfu said:
I think visually you can lay the tensor out like a matrix with rows and columns. However people tend to use the indices alone and not worry about comparing it to a matrix in that way.

Basically, you don't want to lose sight of the covariant/contravariant nature of each indice.

Here's a writeup on tensor notation where you can see that they use matrix notation for some covariant tensors:

http://www.continuummechanics.org/cm/tensornotationbasic.html

Perhaps @Mark44 can add something here too.

Thanks a lot!
 

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