Manipulation of 2nd, 3rd & 4th order tensor using Index notation

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Discussion Overview

The discussion revolves around the manipulation of higher-order tensors using index notation, specifically focusing on the representation of a tensor equation involving fourth and third rank tensors, as well as the concepts of transpose and inverse in tensor theory. Participants explore the validity of certain tensor operations and notations.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Conceptual clarification

Main Points Raised

  • One participant presents a tensor equation and seeks to express it in index notation, questioning how to denote the transpose of a third rank tensor.
  • Another participant asserts that tensor theory does not include the concept of "transpose" or "inverse" for tensors, suggesting that these concepts are specific to matrices.
  • There is a discussion about the meaning of the dot product in the context of tensors, with some participants questioning its definition and applicability.
  • One participant mentions reading about piezoelectricity and refers to specific literature, indicating a desire to understand tensor notation better.
  • Concerns are raised about the reliability of Wikipedia articles on tensor notation, with one participant expressing uncertainty about potential inaccuracies.
  • A later reply clarifies the notation used in Wikipedia, explaining that when the same letter is used for both upper and lower indices in a product, it implies summation, leading to a scalar result.
  • Another participant emphasizes that different indices must be used if one does not want to sum the terms, which would represent a matrix rather than a scalar.

Areas of Agreement / Disagreement

Participants express differing views on the validity of certain tensor operations and notations, particularly regarding the concepts of transpose and inverse in tensor theory. The discussion remains unresolved with multiple competing perspectives on these topics.

Contextual Notes

Participants highlight limitations in understanding tensor notation and the potential for inaccuracies in online resources. There is an acknowledgment of the complexity of tensor operations beyond second rank, which may not be universally defined.

chowdhury
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If I have an equation, let's say,
$$\mathbf{A} = \mathbf{B} + \mathbf{C}^{Transpose} \cdot \left( \mathbf{D}^{-1} \mathbf{C} \right),$$
1.) How would I write using index notation? Here
  • A is a 4th rank tensor
    [*]B is a 4th rank tensor
    [*]C is a 3rd rank tensor
    [*]D is a 2nd rank tensor


I wrote it as $$A_{ijkl} = B_{ijkl} + C_{ijk}^{Transpose} D_{ll}^{-1} C_{ijk} $$
$$A_{ijkl} = B_{ijkl} + C_{kij} D_{ll}^{-1} C_{ijk} $$

2.) How to denote the transpose of a third rank tensor? $$C^{Transpose}$$ or $$C^{t}$$ or is there a succinct way of writing it?
 
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Tensor theory does not include a notion of "transpose", which is a concept that applies only to matrices.
Nor does it have a notion of an inverse tensor, so I don't know what to make of your ##\mathbf D^{-1}##. Again that is a concept that applies only to matrices.
Lastly, I don't know what you mean by the dot before the parenthesis. Do you mean a dot product (inner product)? If so, that's probably not defined in this context. Alternatively, perhaps you mean the tensor product, but that's usually written with the ##\otimes## symbol.

In summary, you need to make sure first that you've written a valid tensor equation before you start trying to rewrite it in index notation.
 
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andrewkirk said:
Do you mean a dot product (inner product)?
Yes. He is reading about piezoelectricity (chapter 8) in B. A. Auld, Acoustic fields and waves in solids, vol. 1, 1973.
https://www.physicsforums.com/threads/inverse-of-a-vector.1012428/

@chowdhury You should really read those articles first:
https://en.wikipedia.org/wiki/Einstein_notation
https://en.wikipedia.org/wiki/Raising_and_lowering_indices
https://en.wikipedia.org/wiki/Tensor_contraction
https://en.wikipedia.org/wiki/Covariant_transformation
https://en.wikipedia.org/wiki/Tensor_field

Even
https://www.physicsforums.com/insights/what-is-a-tensor/
should help. And the Wikipedia article on piezoelectricity has some of those formulas, too, and written in a more modern way:
https://en.wikipedia.org/wiki/Piezoelectricity#Mathematical_description
 
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@andrewkirk and @fresh_42,

I indeed read a book of 300 pages on basic tensor notation applied to mechanics, and what I could grasp as per my understanding, I am writing here.

Just to reiterate my understanding:
  • by matrix, we mean (m x n). As a sidenote in Matlab, you can have matrices of ( m x n x L x ...), I think it is called paging.
    [*]Vector (n x 1) or (1 x n)

I learned today, from @andrewkirk, that tensor theory (more than second rank) does not include the concept of transpose and inverse. Thank you.

@fresh_42 : I indeed read few of the wikipedia articles you have provided, but you know, in wiki, many people write many things, not sure whether it is a typo or not. This is a great forum, where I can learn from expert, like you, directly. Thanks for being patient.
 
Last edited:
fresh_42 said:
Yes. He is reading about piezoelectricity (chapter 8) in B. A. Auld, Acoustic fields and waves in solids, vol. 1, 1973.
https://www.physicsforums.com/threads/inverse-of-a-vector.1012428/

@chowdhury You should really read those articles first:
https://en.wikipedia.org/wiki/Einstein_notation
https://en.wikipedia.org/wiki/Raising_and_lowering_indices
https://en.wikipedia.org/wiki/Tensor_contraction
https://en.wikipedia.org/wiki/Covariant_transformation
https://en.wikipedia.org/wiki/Tensor_field

Even
https://www.physicsforums.com/insights/what-is-a-tensor/
should help. And the Wikipedia article on piezoelectricity has some of those formulas, too, and written in a more modern way:
https://en.wikipedia.org/wiki/Piezoelectricity#Mathematical_description

@andrewkirk Is the notation in Wikipedia correct? Comparing the dyadic product, it does not seem to be correct.

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

To me, this ##v## seems not right, as it results a scalar.
$$ v = v^{i} e_{i} =
\begin{bmatrix}
e_{1} & e_{2} & \cdots & e_{n}
\end{bmatrix} \begin{bmatrix}
v^{1}\\
v^{1}\\
\vdots \\
v^{n}
\end{bmatrix}
$$

$$ w = w_{i} e^{i} =
\begin{bmatrix}
w_{1} & w_{2} & \cdots & w_{n}
\end{bmatrix} \begin{bmatrix}
e^{1}\\
e^{1}\\
\vdots \\
e^{n}
\end{bmatrix}
$$

It is mentioned in the above wikipedia article

dyadic product is ##A^{i}_{j} = u^{i} v_{j} = (uv)^{i}_{j}##
 
The notation is correct. Under the convention, when the same letter is used for a lower and an upper index in a product, we sum over that index variable, so ##u^iv_i## denotes ##\sum_i u^i v_i##, a scalar. Assuming ##\mathbf u## is a row vector and ##\mathbf v## is a column vector, that is the same as the product ##\mathbf u \mathbf v##, ie the row vector goes first.

If you don't want to add the terms, you must use different indices, ##u^i v_j## That can be represented by a matrix. Again assuming ##\mathbf u## is a row vector and ##\mathbf v## is a column vector, that is the same as the product ##\mathbf v \mathbf u##, ie the column vector goes first.
 

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