Tensor Index Notation Question

In summary: Spaced indices represent non-symmetric tensors.In summary, spacing between indices in a tensor notation is crucial, especially when contracting with the metric tensor. The notation A_{\mu}^{\nu} indicates a symmetric tensor while A{^{\nu}}_{\mu} represents a non-symmetric tensor. This distinction is important for clarity and accuracy in tensor operations.
  • #1
Markus Hanke
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I am just wondering, is there a difference in meaning/definition between the indices of a tensor being right on top of each other

[tex]A_{\mu }^{\nu }[/tex]

and being "spaced" as in

[tex]A{^{\nu }}_{\mu }[/tex]

I seem to remember that I once read that there is indeed a difference, but I can't remember what it was.

Thanks in advance.
 
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  • #2
The spacing is very important if you are contracting with the metric tensor using the abstract index notation. For example if ##A^{a}{}{}_{b}## is a tensor then ##g^{bc}A^{a}{}{}_{c} = A^{ab}## but if we consider ##A_{c}{}{}^{a}## then ##g^{bc}A_{c}{}{}^{a} = A^{ba}## which will not equal ##A^{ab}## unless the tensor is symmetric. The notation ##A^{a}_{b}## makes the contraction with the metric tensor ill-defined in abstract index notation (index free notation is a different story of course).

The action of the tensor on a covector and a vector will subsequently be ambiguous if all you write down is ##A^{a}_{b}## because ##A_{b}{}{}^{a}v^{b}\omega_{a} = g^{ac}A_{bc}v^{b}\omega_{a} \neq g^{ac}A_{cb}v^{b}\omega_{a} = A^{a}{}{}_{b}v^{b}\omega_{a}## in general, so the spacing is important.
 
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Likes GaryWilbourn and Markus Hanke
  • #3
You just need a convention for the order.
$$A{_\mu }^{\nu } \\
A{^{\nu }}_{\mu } \\
A_{\mu }^{\nu }$$

So the third one can be substituted for one of the others as long as you always know which one, or that it does not matter which.
 
  • #4
Non-spaced indices represent symmetric tensor (in respective components).
 
  • #5


Yes, there is a difference in meaning between the two notations. The first notation, A_{\mu }^{\nu }, is called the "covariant" notation, while the second notation, A{^{\nu }}_{\mu }, is called the "contravariant" notation.

In the covariant notation, the upper index (superscript) represents the "contravariant" transformation of the tensor, meaning how its components change when the coordinate system is transformed. The lower index (subscript) represents the "covariant" transformation, which describes how the basis vectors of the coordinate system change.

In the contravariant notation, the upper index represents the "covariant" transformation, while the lower index represents the "contravariant" transformation.

In general, the two notations are related by the metric tensor, which is used to raise and lower indices. This metric tensor describes the relationship between the basis vectors of the coordinate system and the basis vectors of the dual coordinate system.

It is important to note that the choice of notation does not change the physical meaning of the tensor itself, but it is a matter of convenience and convention in mathematical notation. Both notations are commonly used in tensor analysis and have their own advantages in different situations.
 

1. What is Tensor Index Notation?

Tensor Index Notation is a way of representing tensors, which are mathematical objects that describe the relationship between vectors and scalars. It is a concise and powerful mathematical notation that is commonly used in physics and engineering.

2. How is Tensor Index Notation different from other notations?

Tensor Index Notation uses subscripts and superscripts to represent the indices of a tensor, which makes it more compact and easier to manipulate than other notations. It also allows for better visualization of the tensor's components and their relationships.

3. Why is Tensor Index Notation important in science?

Tensor Index Notation is important in science because it allows for the accurate and efficient representation of complex relationships between physical quantities. It is especially useful in fields such as physics, engineering, and mathematics, where tensors are commonly used to describe physical phenomena.

4. How do you perform operations on tensors using Tensor Index Notation?

In Tensor Index Notation, operations on tensors are performed by manipulating the indices according to certain rules and conventions. For example, the Einstein summation convention states that when an index appears twice in an expression, it implies a summation over all possible values of that index.

5. Are there any limitations to Tensor Index Notation?

While Tensor Index Notation is a powerful tool, it does have some limitations. For instance, it is not always easy to visualize higher-order tensors (those with more than two indices) using this notation. Additionally, it can be challenging to perform calculations involving multiple tensors with different indices.

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