Tensor differentiation (element-by-element)

In summary, the proof provided is for the equation \frac{\text{d}}{\text{d}t}\left(\begin{bmatrix} I_{1,1} & I_{1,2} & I_{1,3} \\ I_{2,1} & I_{2,2} & I_{2,3} \\ I_{3,1} & I_{3,2} & I_{3,3} \end{bmatrix}\right) = \begin{bmatrix} 2\,r_2\,\omega_2 + 2\,r_3\,\omega_3 & -(r_1\,\omega_2 + r_2\,\
  • #1
TadeusPrastowo
21
0

Homework Statement



Proof the following:
[tex]\frac{\text{d}\boldsymbol\{\mathbf{I}\boldsymbol\}}{\text{d}t} \, \boldsymbol\omega = \boldsymbol\omega \times (\boldsymbol\{\mathbf{I}\boldsymbol\}\,\boldsymbol\omega)[/tex]

where [itex]\boldsymbol\{\mathbf{I}\boldsymbol\}[/itex] is a tensor: [tex]\boldsymbol\{\mathbf{I}\boldsymbol\} = \begin{bmatrix}
I_{1,1} & I_{1,2} & I_{1,3} \\
I_{2,1} & I_{2,2} & I_{2,3} \\
I_{3,1} & I_{3,2} & I_{3,3} \\
\end{bmatrix}[/tex]

with [itex]\text{I}_{i,j}[/itex] as the following:
[tex]\text{I}_{i,j} = \delta_{i,j} \sum_k r_k^2 - r_i\,r_j[/tex]

and [itex]\boldsymbol\omega[/itex] is a vector:

[tex]\begin{bmatrix}\omega_1 \\ \omega_2 \\ \omega_3\end{bmatrix}[/tex]

Homework Equations



The relevant equation should be on how to perform [itex]\frac{\text{d}}{\text{d}t}\left(\begin{bmatrix}
I_{1,1} & I_{1,2} & I_{1,3} \\
I_{2,1} & I_{2,2} & I_{2,3} \\
I_{3,1} & I_{3,2} & I_{3,3} \\
\end{bmatrix}\right)[/itex].
But, I haven't found an online resource that shows the way. Wikipedia on tensor derivative does not touch on how to perform tensor derivative element-by-element.

The Attempt at a Solution



[tex]\begin{align}
\frac{\text{d}}{\text{d}t}\left(\begin{bmatrix}
I_{1,1} & I_{1,2} & I_{1,3} \\
I_{2,1} & I_{2,2} & I_{2,3} \\
I_{3,1} & I_{3,2} & I_{3,3} \\
\end{bmatrix}\right) &= \begin{bmatrix}
\frac{\text{d}\,I_{1,1}}{\text{d}t} & \frac{\text{d}\,I_{1,2}}{\text{d}t} & \frac{\text{d}\,I_{1,3}}{\text{d}t} \\
\frac{\text{d}\,I_{2,1}}{\text{d}t} & \frac{\text{d}\,I_{2,2}}{\text{d}t} & \frac{\text{d}\,I_{2,3}}{\text{d}t} \\
\frac{\text{d}\,I_{3,1}}{\text{d}t} & \frac{\text{d}\,I_{3,2}}{\text{d}t} & \frac{\text{d}\,I_{3,3}}{\text{d}t} \\
\end{bmatrix}
\end{align}[/tex]

Then, I calculate the above one as follows:
[tex]\begin{align}
\frac{\text{d}\text{I}_{i,j}}{\text{d}t} &= \frac{\text{d}}{\text{d}t}\,(\delta_{i,j} \sum_k r_k^2 - r_i\,r_j) \\
&= \frac{\text{d}}{\text{d}t}\,\delta_{i,j} \sum_k r_k^2 - \frac{\text{d}}{\text{d}t}\,r_i\,r_j \\
&= \delta_{i,j} \frac{\text{d}}{\text{d}t}\, \sum_k r_k^2 - \frac{\text{d}}{\text{d}t}\,r_i\,r_j \\
&= \delta_{i,j} \sum_k \frac{\text{d}}{\text{d}t}\,r_k^2 - \frac{\text{d}}{\text{d}t}\,r_i\,r_j \\
&= \delta_{i,j} \sum_k \frac{\text{d}\,r_k^2}{r_k}\frac{\text{d}\,r_k}{\text{d}t} - \frac{\text{d}}{\text{d}t}\,r_i\,r_j \\
&= \delta_{i,j} \sum_k 2\,r_k\,\omega_k - (\omega_i\,r_j + r_i\,\omega_j) \\
\frac{\text{d}\text{I}_{i,j}}{\text{d}t} &= \begin{bmatrix}
2\,r_2\,\omega_2 + 2\,r_3\,\omega_3 & -(r_1\,\omega_2 + r_2\,\omega_1) & -(r_1\,\omega_3 + r_3\,\omega_1) \\
-(r_2\,\omega_1 + r_1\,\omega_2) & 2\,r_1\,\omega_1 + 2\,r_3\,\omega_3 & -(r_2\,\omega_3 + r_3\,\omega_2) \\
-(r_3\,\omega_1 + r_1\,\omega_3) & -(r_3\,\omega_2 + r_2\,\omega_3) & 2\,r_1\omega_1 + 2\,r_2\,\omega_2
\end{bmatrix}
\end{align}
[/tex]

But, multiplying the result of the differentiation with [itex]\boldsymbol\omega[/itex] does not yield [itex]\boldsymbol\omega \times (\boldsymbol\{\mathbf{I}\boldsymbol\}\,\boldsymbol\omega) = \begin{bmatrix}
0 & -\omega_3 & \omega_2 \\
\omega_3 & 0 & -\omega_1 \\
-\omega_2 & \omega_1 & 0
\end{bmatrix}\left(\begin{bmatrix}
r_2^2 + r_3^2 & -r_1 r_2 & -r_1 r_3 \\
-r_2 r_1 & r_1^2 + r_3^2 & -r_2 r_3 \\
-r_3 r_1 & -r_3 r_2 & r_1^2 + r_2^2
\end{bmatrix}\begin{bmatrix}
\omega_1 \\ \omega_2 \\ \omega_3
\end{bmatrix}\right)[/itex]:
[tex]
\begin{align}
\frac{\text{d}\text{I}_{i,j}}{\text{d}t} \, \boldsymbol\omega &= \begin{bmatrix}
2\,r_2\,\omega_2 + 2\,r_3\,\omega_3 & -(r_1\,\omega_2 + r_2\,\omega_1) & -(r_1\,\omega_3 + r_3\,\omega_1) \\
-(r_2\,\omega_1 + r_1\,\omega_2) & 2\,r_1\,\omega_1 + 2\,r_3\,\omega_3 & -(r_2\,\omega_3 + r_3\,\omega_2) \\
-(r_3\,\omega_1 + r_1\,\omega_3) & -(r_3\,\omega_2 + r_2\,\omega_3) & 2\,r_1\omega_1 + 2\,r_2\,\omega_2
\end{bmatrix}\begin{bmatrix}
\omega_1 \\ \omega_2 \\ \omega_3
\end{bmatrix} \\
&= \begin{bmatrix}
(2\,r_2\,\omega_2 + 2\,r_3\,\omega_3)\,\omega_1 - (r_1\,\omega_2 + r_2\,\omega_1)\,\omega_2 - (r_1\,\omega_3 + r_3\,\omega_1)\,\omega_3 \\
-(r_2\,\omega_1 + r_1\,\omega_2)\,\omega_1 + (2\,r_1\,\omega_1 + 2\,r_3\,\omega_3)\,\omega_2 - (r_2\,\omega_3 + r_3\,\omega_2)\,\omega_3 \\
-(r_3\,\omega_1 + r_1\,\omega_3)\,\omega_1 - (r_3\,\omega_2 + r_2\,\omega_3)\,\omega_2 + (2\,r_1\omega_1 + 2\,r_2\,\omega_2)\,\omega_3
\end{bmatrix}
\end{align}
[/tex]

I also have tried several factorizations on paper but to no avail.
But, I may miss some wonderful factorization tricks.
Or, should a tensor be differentiated element-by-element in another way?

Thank you.
 
Physics news on Phys.org
  • #2
Do you have to write it out explicitly using components?
Perhaps if you write it like $$\left(\frac{\text{d}}{\text{d}t} I_{ij} \right)w_j = \epsilon_{ijk}w_j I_{kl}w_l,$$ (summation convention understood) where ##I_{ij} = \delta_{ij}\sum_k r_k^2 - r_i r_j## and show the two sides are equivalent. Have not tried it myself, but it might save you the mess of writing out all the components.
 
  • #3
Is $$\omega$$ the time derivative of r?
 

1. What is tensor differentiation (element-by-element)?

Tensor differentiation (element-by-element) is a mathematical operation used to calculate the derivative of a tensor with respect to each element of the tensor. It is a generalization of the traditional concept of differentiation for scalar functions.

2. Why is tensor differentiation (element-by-element) important?

Tensor differentiation (element-by-element) is important because it allows us to calculate the rate of change of a tensor with respect to each element, which is useful in many scientific and engineering applications. It also helps us to understand the relationship between different elements of a tensor and how they contribute to the overall behavior of the tensor.

3. How is tensor differentiation (element-by-element) different from traditional differentiation?

Tensor differentiation (element-by-element) is different from traditional differentiation because it takes into account the multidimensional nature of tensors. Traditional differentiation is limited to scalar functions, whereas tensor differentiation allows us to calculate the derivatives of multidimensional functions.

4. What are some common applications of tensor differentiation (element-by-element)?

Tensor differentiation (element-by-element) has many applications in fields such as physics, engineering, and machine learning. Some common applications include image and signal processing, optimization, and deep learning algorithms.

5. Are there any limitations to tensor differentiation (element-by-element)?

One limitation of tensor differentiation (element-by-element) is that it can be computationally expensive, especially for large tensors. Additionally, it may not always be well-defined or feasible for certain types of tensors, such as non-differentiable or discontinuous tensors. It is important to carefully consider the properties of the tensor and the specific problem at hand before using tensor differentiation.

Similar threads

Replies
6
Views
615
  • Calculus and Beyond Homework Help
Replies
6
Views
536
  • Calculus and Beyond Homework Help
Replies
6
Views
1K
  • Advanced Physics Homework Help
Replies
2
Views
823
  • Introductory Physics Homework Help
Replies
11
Views
1K
  • Calculus and Beyond Homework Help
Replies
3
Views
572
  • Calculus and Beyond Homework Help
Replies
1
Views
1K
  • Advanced Physics Homework Help
Replies
7
Views
3K
Replies
66
Views
4K
  • Calculus and Beyond Homework Help
Replies
4
Views
2K
Back
Top