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

chowdhury
Messages
34
Reaction score
3
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?
 
Physics news on Phys.org
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.
 
  • Informative
Likes chowdhury and Klystron
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
 
@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.
 
##\textbf{Exercise 10}:## I came across the following solution online: Questions: 1. When the author states in "that ring (not sure if he is referring to ##R## or ##R/\mathfrak{p}##, but I am guessing the later) ##x_n x_{n+1}=0## for all odd $n$ and ##x_{n+1}## is invertible, so that ##x_n=0##" 2. How does ##x_nx_{n+1}=0## implies that ##x_{n+1}## is invertible and ##x_n=0##. I mean if the quotient ring ##R/\mathfrak{p}## is an integral domain, and ##x_{n+1}## is invertible then...
The following are taken from the two sources, 1) from this online page and the book An Introduction to Module Theory by: Ibrahim Assem, Flavio U. Coelho. In the Abelian Categories chapter in the module theory text on page 157, right after presenting IV.2.21 Definition, the authors states "Image and coimage may or may not exist, but if they do, then they are unique up to isomorphism (because so are kernels and cokernels). Also in the reference url page above, the authors present two...
When decomposing a representation ##\rho## of a finite group ##G## into irreducible representations, we can find the number of times the representation contains a particular irrep ##\rho_0## through the character inner product $$ \langle \chi, \chi_0\rangle = \frac{1}{|G|} \sum_{g\in G} \chi(g) \chi_0(g)^*$$ where ##\chi## and ##\chi_0## are the characters of ##\rho## and ##\rho_0##, respectively. Since all group elements in the same conjugacy class have the same characters, this may be...
Back
Top