Is there a convention for horizontally shifting indices in tensor notation?

In summary, the conversation is about the notational device used in tensor analysis and its implications. The speaker asks for clarification on horizontally shifting indices in a (1,1) tensor and its relation to the metric. The response explains that keeping track of the horizontal positions is necessary when using the metric to raise and lower indices, and gives an example of this in special relativity. It also mentions the notations used for Lorentz transformations and their corresponding matrices.
  • #1
JohnBell5713
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Hi,

I'm teaching myself tensor analysis and am worried about a notational device I can't find any explanation of (I'm primarily using the Jeevanjee and Renteln texts).

Given that the contravariant/covariant indices of a (1,1) tensor correspond to the row/column indices of its matrix representation, what is indicated by horizontally shifting one index with respect to the other? Is this notationally redundant, or is some extra information I'm missing being encoded here? Given that this convention also applies to (n,m) tensors and even the Kronecker delta, I want to clear this up before proceeding further.

John
 
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  • #2
If you intend to use the metric to raise and lower indices, then you also need to keep track of the horizontal positions. Special relativity is a good example:

The components of the metric in an inertial coordinate system are denoted by ##\eta_{\mu\nu}##. The matrix with ##\eta_{\mu\nu}## on row ##\mu##, column ##\nu## is denoted by ##\eta##. The number on row ##\mu##, column ##\nu## of ##\eta^{-1}## is denoted by ##\eta^{\mu\nu}##. For most other linear transformations M on ##\mathbb R^4##, the number on row ##\mu##, column ##\nu## of the corresponding matrix is denoted by ##M^\mu{}_\nu##.

A Lorentz transformation is a linear operator ##\Lambda## such that the corresponding matrix (also denoted by ##\Lambda##) satisfies ##\Lambda^T\eta\Lambda=\eta##. This implies that ##\Lambda^{-1}=\eta^{-1}\Lambda^T\eta##. So we have
$$ (\Lambda^{-1})^\mu{}_\nu = (\eta^{-1}\Lambda^T\eta)^\mu{}_\nu =\eta^{\mu\rho}(\Lambda^T)^{\rho}{}_\sigma \eta_{\sigma\nu} =\eta^{\mu\rho}\Lambda^{\sigma}{}_\rho \eta_{\sigma\nu}=\Lambda_\nu{}^\mu.
$$
 
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1. What is tensor notation?

Tensor notation is a mathematical notation used to represent and manipulate tensors, which are multi-dimensional arrays of numbers that describe the relationships between different physical quantities.

2. Why is tensor notation useful?

Tensor notation is useful because it allows for a compact and efficient representation of complex mathematical equations, particularly in fields such as physics and engineering. It also makes it easier to perform calculations and transformations on tensors.

3. What are the basic elements of tensor notation?

The basic elements of tensor notation include indices, which represent the dimensions of a tensor, and the Einstein summation convention, which simplifies the notation by specifying that repeated indices are to be summed over.

4. How does tensor notation differ from other mathematical notations?

Tensor notation differs from other mathematical notations in that it specifically deals with tensors, which are distinct from scalars, vectors, and matrices. It also uses indices to represent dimensions, which is not commonly seen in other mathematical notations.

5. Are there any rules to follow when using tensor notation?

Yes, there are certain rules to follow when using tensor notation. These include the rules of index notation, such as the rule that an index can only appear twice in a term and must be summed over, as well as the rules of matrix multiplication and tensor contraction.

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