Tensor Algebras - Cooperstein Example 10.1

In summary, the conversation discusses Example 10.1 in Section 10.3 of Cooperstein's book on Advanced Linear Algebra. The example discusses the tensor algebra and how it is defined as a direct sum of tensor products. The questions raised pertain to the form of the general element in degree 3 and the reason for creating a direct sum to add tensors of different ranks. The answer explains that in a one-dimensional vector space, the index keeps track of the number of vectors being tensorred and the coefficients are derived from ordinary multiplication.
  • #1
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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:View attachment 5552
View attachment 5553
View attachment 5554My 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 \(\displaystyle \mathcal{T}_k (V) = \{ cv \otimes \ ... \ ... \ \otimes v \ | \ c \in \mathbb{F} \}\) ... ... "But ... \(\displaystyle \mathcal{T}_k (V)\) is defined by

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

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

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

... can someone please explain why \(\displaystyle \mathcal{T}_k (V)\) 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
The direct sum of $\bigoplus\limits_i \mathcal{T}_i(V)$ is created just so we can "add tensors of differing rank".

Let's look at a typical element of $\mathcal{T}_3(V)$ where $V = Fv_0$:

It looks like $c_1v_0 \otimes c_2v_0 \otimes c_3v_0 = c_1c_2c_3 (v_0 \otimes v_0 \otimes v_0)$ by trilinearity.

So when $V$ is one-dimensional, the index basically just keeps track of "how many vectors we're tensoring", and the coefficients are derived from ordinary multiplication.
 

FAQ: Tensor Algebras - Cooperstein Example 10.1

What is a tensor algebra?

A tensor algebra is a mathematical structure that extends the concept of vector spaces to include higher-dimensional objects called tensors. It is a powerful tool used in various areas of physics and mathematics, including differential geometry, relativity, and quantum mechanics.

How is a tensor algebra constructed?

A tensor algebra is constructed by taking a vector space V over a field F and forming the direct sum of all the tensor powers of V. This means that the algebra includes all possible combinations of tensor products of vectors from V, including scalar multiples and additions.

What is the significance of Cooperstein Example 10.1 in tensor algebra?

Cooperstein Example 10.1 is a specific example that demonstrates the construction of a tensor algebra. It shows how a tensor algebra can be built from a vector space and its dual space, and how these spaces are related to the tensor products that make up the algebra.

What applications does tensor algebra have?

Tensor algebra has a wide range of applications in physics and mathematics, including general relativity, quantum mechanics, and differential geometry. It is also used in computer science for data analysis and machine learning algorithms.

Can tensor algebra be used in other areas besides physics and mathematics?

Yes, tensor algebra has applications in various fields such as engineering, economics, and even music theory. It provides a powerful framework for analyzing and manipulating multidimensional data and can be applied to any system that can be modeled using tensors.

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