Tensors and Bilinear Functions

In summary: Yes, this matrix is used to represent all eigenvalues of the matrix \(e^1\otimes e_2\), including the eigenvalue 1.Yes, this matrix is used to represent all eigenvalues of the matrix \(e^1\otimes e_2\), including the eigenvalue 1.
  • #1
Sudharaka
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Hi everyone, :)

I don't quite get what this question means. How do we convert the expression into the bilinear form first? Hope you people can give me some insight. :)

Question:

Find the rank of the bilinear function \((e^1+e^3)\otimes (e^2+e^4) - (e^2-e^4)\otimes (e_1-e_3)\).
 
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  • #2
Sudharaka said:
Hi everyone, :)

I don't quite get what this question means. How do we convert the expression into the bilinear form first? Hope you people can give me some insight. :)

Question:

Find the rank of the bilinear function \((e^1+e^3)\otimes (e^2+e^4) - (e^2-e^4)\otimes (e_1-e_3)\).

If we simplify the tensor product expression we get has,

\((e^1\otimes e^2)+(e^1\otimes e^4)+(e^3\otimes e^2)+(e^3\otimes e^4)\)

as the fist four terms. It's these four terms that I have trouble. I know that if we have all the terms as \(e^i\otimes e_j\) then we can easily find out the rank of the bilinear function. But with terms of the form \(e^i\otimes e^j\) I don't understand how we can get the rank.

Thinking further about this question I have the feeling that there maybe a typo. The rank of the bilinear function can be found out if it's given as \((e^1+e^3)\otimes (e_\color{red}{2}+e_\color{red}{4}) - (e^2-e^4)\otimes (e_1-e_3)\).
 
  • #3
Sudharaka said:
I have the feeling that there maybe a typo. The rank of the bilinear function can be found out if it's given as \((e^1+e^3)\otimes (e_\color{red}{2}+e_\color{red}{4}) - (e^2-e^4)\otimes (e_1-e_3)\).
That seems the likeliest explanation to me. If the function is $(e^1+e^3)\otimes (e^{2}+e^{4}) - (e^2-e^4)\otimes (e_1-e_3)$ then it is not clear what its domain could be, since the two terms are operating on different spaces.
 
  • #4
Opalg said:
That seems the likeliest explanation to me. If the function is $(e^1+e^3)\otimes (e^{2}+e^{4}) - (e^2-e^4)\otimes (e_1-e_3)$ then it is not clear what its domain could be, since the two terms are operating on different spaces.

Thanks so much for the confirmation. I changed the problem and I get the answer as \(8\). Am I correct? :)
 
  • #5
Sudharaka said:
I changed the problem and I get the answer as \(8\). Am I correct? :)
As in a previous question, that depends on what is meant by "rank" here. I would take it to mean the rank of the associated matrix. I would associate each basic tensor of the form $e^i\otimes e_j$ with the $4\times4$ matrix having a $1$ in the $(i,j)$-position and zeros elsewhere. Then the bilinear form $(e^1+e^3)\otimes (e_{2}+e_{4}) - (e^2-e^4)\otimes (e_1-e_3)$ corresponds to the matrix $\begin{bmatrix}0&1&0&1 \\ -1&0&1&0 \\ 0&1&0&1 \\ 1&0&-1&0\end{bmatrix}$, which has rank $2.$
 
  • #6
Opalg said:
As in a previous question, that depends on what is meant by "rank" here. I would take it to mean the rank of the associated matrix. I would associate each basic tensor of the form $e^i\otimes e_j$ with the $4\times4$ matrix having a $1$ in the $(i,j)$-position and zeros elsewhere. Then the bilinear form $(e^1+e^3)\otimes (e_{2}+e_{4}) - (e^2-e^4)\otimes (e_1-e_3)$ corresponds to the matrix $\begin{bmatrix}0&1&0&1 \\ -1&0&1&0 \\ 0&1&0&1 \\ 1&0&-1&0\end{bmatrix}$, which has rank $2.$

I think what you meant by rank is what is meant to find in the question. Of course we used the word rank to mean different things in our linear algebra course, but in this case I think your answer makes more sense and I guess rank refers to the matrix rank. Thanks so much for helping me out. :)
 
  • #7
Hi again, :)

Our professor changed the question so as all the indices were taken as superscripts. So the the question is,

Question:

Find the rank of the bilinear function \[(e^1+e^3)\otimes (e^2+e^4) - (e^2-e^4)\otimes (e^1-e^3)\]

Now can you give me any idea as to how this can me converted into it's matrix form. :)
 
  • #8
Sudharaka said:
Hi again, :)

Our professor changed the question so as all the indices were taken as superscripts. So the the question is,

Question:

Find the rank of the bilinear function \[(e^1+e^3)\otimes (e^2+e^4) - (e^2-e^4)\otimes (e^1-e^3)\]

Now can you give me any idea as to how this can me converted into it's matrix form. :)
It should make no difference. This time, the matrix represents a map from $V^*\otimes V^*$ to itself rather than a map from $V^*\otimes V^*$ to $V\otimes V$. But the matrix entries, and therefore the rank, are the same as before.
 
  • #9
Opalg said:
It should make no difference. This time, the matrix represents a map from $V^*\otimes V^*$ to itself rather than a map from $V^*\otimes V^*$ to $V\otimes V$. But the matrix entries, and therefore the rank, are the same as before.

Thanks very much for the reply. So that means, for example, the matrix representation of \(e^1\otimes e_2\) and the matrix representation of \(e^1\otimes e^2\) is the same, given by,

\begin{pmatrix}0&1&0&0\\0&0&0&0 \\0&0&0&0\\0&0&0&0\end{pmatrix}

Am I correct? Furthermore is this same matrix used to represent \(e_1\otimes e_2\) ?
 

Related to Tensors and Bilinear Functions

1. What are tensors and bilinear functions?

Tensors are mathematical objects that generalize scalars, vectors, and matrices to higher dimensions. They are used to represent physical quantities such as forces and stresses in physics and engineering. Bilinear functions are functions that take in two inputs and produce a single output, which is linear in each of the inputs.

2. What is the difference between a tensor and a matrix?

Tensors are multi-dimensional arrays, while matrices are two-dimensional arrays. Matrices are a special case of tensors, as they are only defined in two dimensions. Tensors can have any number of dimensions, making them more flexible for representing higher-dimensional data.

3. How are tensors and bilinear functions used in machine learning?

Tensors are used to represent and manipulate multi-dimensional data in machine learning algorithms. Bilinear functions are used in various tasks such as feature extraction, dimensionality reduction, and classification. They are also used in neural networks for tasks such as image recognition and natural language processing.

4. Can tensors and bilinear functions be applied in other fields besides mathematics and machine learning?

Yes, tensors and bilinear functions have applications in various fields such as physics, engineering, and computer graphics. They are also used in economics, statistics, and signal processing.

5. What are some real-world examples of tensors and bilinear functions?

Examples of tensors include stress and strain tensors in mechanics, the electromagnetic tensor in physics, and the diffusion tensor in medical imaging. Examples of bilinear functions include the dot product and cross product in vector calculus, and the covariance function in statistics.

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