The Tensor Algebra - Cooperstein, Example 10.1

In summary: This notation uses boldface to indicate that an operation is a tensor product.In summary, the matrix ##\mathcal{T}_k(V)## in Cooperstein's Example 10.1 is a vector space, and the general element of degree 3 is given by the sum of its homogeneous parts. The addition of these elements together with scalar multiplications of matrices in tensor notation gives you any matrix you want.
  • #1

Math Amateur

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I am reading Bruce N. Coopersteins book: Advanced Linear Algebra (Second Edition) ... ...

I am focused on Section 10.3 The Tensor Algebra ... ...

I need help in order to get a basic understanding of Example 10.1 in Section 10.3 ...Example 10.1 plus some preliminary definitions reads as follows:
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My questions related to Example 10.1 are articulated below ... ...
Question 1

In the above text from Cooperstein we read in Example 1, the following:" ... ... Then ##\mathcal{T}_k (V) = \{ cv \otimes \ ... \ ... \ \otimes v \ | \ c \in \mathbb{F} \}## ... ... "But ... ##\mathcal{T}_k (V)## is defined by

##\mathcal{T}_k (V) = V \otimes V \otimes V \ ... \ ... \ \otimes V## ... ... ... (1)

( and there are ##k## ##V##'s in the product ... )... surely then ##\mathcal{T}_k (V) = \{ v \otimes \ ... \ ... \ \otimes v \ | \ v \in V \} ##and not (as shown in Cooperstein Example 10.1 )

##\mathcal{T}_k (V) = \{ cv \otimes \ ... \ ... \ \otimes v \ | \ c \in \mathbb{F} \} ##

... can someone please explain why ##\mathcal{T}_k (V)## has the form shown by Cooperstein in Example 10.1 ...Question 2

Can someone explain how/why the general element of degree 3 is as shown in Example 10.1 ...

Does it make sense to add these elements ... they seem different in nature and form ...Hope someone can help ...

Peter
 

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  • #2
Math Amateur said:
Question 1

In the above text from Cooperstein we read in Example 1, the following:" ... ... Then ##\mathcal{T}_k (V) = \{ cv \otimes \ ... \ ... \ \otimes v \ | \ c \in \mathbb{F} \}## ... ... "But ... ##\mathcal{T}_k (V)## is defined by

##\mathcal{T}_k (V) = V \otimes V \otimes V \ ... \ ... \ \otimes V## ... ... ... (1)

( and there are ##k## ##V##'s in the product ... )... surely then ##\mathcal{T}_k (V) = \{ v \otimes \ ... \ ... \ \otimes v \ | \ v \in V \} ##and not (as shown in Cooperstein Example 10.1 )

##\mathcal{T}_k (V) = \{ cv \otimes \ ... \ ... \ \otimes v \ | \ c \in \mathbb{F} \} ##

... can someone please explain why ##\mathcal{T}_k (V)## has the form shown by Cooperstein in Example 10.1 ...

Since the [itex]\mathcal{T}_k[/itex] are vector spaces, a vector space is closed under multiplication by a constant. So if [itex]v \otimes \ ... \ ... \ \otimes v[/itex] is an element of the vector space, so is [itex]c v \otimes \ ... \ ... \ \otimes v [/itex]
 
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  • #3
Math Amateur said:
Question 2
Can someone explain how/why the general element of degree 3 is as shown in Example 10.1 ...

Does it make sense to add these elements ... they seem different in nature and form ...
The key is where the author says 'We will often abuse notation and express ##\boldsymbol x## as a sum of its homogeneous parts rather than as a function from ##\mathbb Z_{\geq 0}##'.

I note that this also explains the abuse of notation that caused you concern in your other post from yesterday. I have to retract my criticism of the author that I made there, as the excerpt you include here shows that he does explicitly acknowledge the abuse of notation. I beg your pardon, Mr Cooperstein.

The elements that are being added are functions from ##\mathbb Z_{\geq 0}## to ##\bigcup_{k\in\mathbb Z_{\geq 0}}\mathcal T_k##. Because we have the constraint ##\boldsymbol x(k)\in\mathcal T_k(V)## and ##\mathcal T_k(V)## is a vector space (and hence has well-defined addition), we have the following natural definition of addition in ##\mathcal T(V)##. For ##\boldsymbol x,\boldsymbol y\in\mathcal T(V)##, ##\boldsymbol x+\boldsymbol y## is the function from ##\mathbb Z_{\geq 0}## to ##\bigcup_{k\in\mathbb Z_{\geq 0}}\mathcal T_k## such that, for all ##k\in\mathbb Z_{\geq 0}##:
$$(\boldsymbol x+\boldsymbol y)(k)=\boldsymbol x(k)+\boldsymbol y(k)$$
 
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  • #4
Math Amateur said:
Can someone explain how/why the general element of degree 3 is as shown in Example 10.1 ...

Does it make sense to add these elements ... they seem different in nature and form ...Hope someone can help ...

Peter
To get an idea of the tensors you can write vectors in coordinates, say ##v = (v_1,...,v_n) , w = (w_1,...,w_n)##.
##\mathcal T_0 = \mathbb{F}, \mathcal T_1 = V## and ##\mathcal T_2## can be seen as all ##(n \times n)## matrices.
An element ##v\otimes w## then is the rank ##1## matrix
$$v^τ \cdot w = \begin{bmatrix} v_1 \\ \vdots \\ v_n \end{bmatrix} \cdot (w_1, \cdots, w_n) = \begin{bmatrix} v_1w_1 &&\cdots && v_1w_n \\ \vdots && \cdots && \vdots \\ v_nw_1 && \cdots && v_nw_n\end{bmatrix} $$
and addition together with scalar multiplications of those matrices give you any ##(n \times n)## matrix you want.
The same procedure on ##u\otimes v\otimes w## will deliver a ##(n \times n \times n)## cube of rank ##1## and so on.

You are right that you cannot write the sum ##c + v + v \otimes w + u \otimes v \otimes w## other than this formal sum. However, in each component (the homogeneous parts of degree ##0, 1, 2, 3,## resp.) you can add and (scalar) multiply the elements as I mentioned in the case of rank ##1## matrices.

Another picture is that of a polynomial ring micromass mentioned elsewhere. If you have ##ℝ[X,Y]## you cannot add ##X## and ##Y## other than writing ##X+Y##. Nevertheless this doesn't keep you from calculating with polynomials in two variables.
 
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  • #5
Steven, Andrew and Fresh ... thank you for your helpful and clarifying posts ...

I am reflecting on what you have said ...

Thanks again,

Peter
 

1. What is the Tensor Algebra?

The Tensor Algebra is a mathematical concept that extends the operations and properties of vectors and matrices to higher-dimensional objects called tensors. It is used in various fields of mathematics and science, including physics, engineering, and computer science.

2. Who is Cooperstein and why is Example 10.1 significant?

Cooperstein is a mathematician who wrote a textbook on linear algebra. Example 10.1 is significant because it introduces the concept of the Tensor Algebra and provides a clear and comprehensive example for readers to understand.

3. What are the key properties of the Tensor Algebra?

The key properties of the Tensor Algebra include linearity, associativity, and distributivity. These properties allow for the manipulation and transformation of tensors in a consistent and predictable manner.

4. How is the Tensor Algebra used in scientific research?

The Tensor Algebra is used in a wide range of scientific research, particularly in fields that deal with multi-dimensional data such as physics, engineering, and computer science. It is also used in machine learning and artificial intelligence to model complex relationships and make predictions.

5. Are there any real-world applications of the Tensor Algebra?

Yes, the Tensor Algebra has many real-world applications, including image and signal processing, robotics, and fluid dynamics. It is also used in the development of algorithms for data analysis and pattern recognition.

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