Relating Two Notions of Tensor Product

In summary, the tensor product of vector spaces over $\mathbb{C}$ is a special case that is explained as the space of multilinear maps on the cross product of the dual spaces. The general construction of the tensor product involves the universality of two modules in the category of middle linear maps. To understand the special case, one must relate it to the more general construction. A key step is to find a bilinear map from the tensor product to the space of bilinear maps on the dual spaces, which can be done by taking the product of evaluation maps on the dual spaces. This type of problem becomes easier with practice and the key is to find a suitable map to show isomorphism.
  • #1
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When I was first introduced to the tensor product, I was actually introduced to a special case: the tensor product of vector spaces over [tex]\mathbb{C}[/tex], which was explained to be as the space of multilinear maps on the cross product of the dual spaces, for example. At the time I wasn't aware this was a special case, but now that I'm working through chapter 4 of Hungerford's Algebra, it's clear.

I feel like I understand the general construction in terms of the universality of the tensor product of two modules in the category of middle linear maps (I think this terminology may be exclusive to Hungerford). My problem is relating this more general construction to the one above. That is, if I replace the ring [tex]R[/tex] with [tex]\mathbb{C}[/tex], and the modules with vector spaces, I don't get what I want. This probably also implies that I don't really understand the tensor product in the more general setting as much as I think I do.

So my question is this: How does one get from the more general construction to the special case mentioned above?
 
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  • #2
finite dimensional vector spaces are isomorphic to their double duals. presumably the special case you learned was the double dual of the general definition. A tensor product of spaces A,B is a space X plus a bilinear map AxB-->X such that every bilinear map out of AxB factors through this one, as composing with a linear map out of X.

In particular the dual of X is isomorphic by this construction to Bil{(AxB);k}, and hence X is itself isomorphic to the dual of Bil{(AxB);k}, which presumably is isomorphic to
Bil{(AxB)*;k}, and also to your construction Bil{(A*xB*),k}.


So your first job is to find a bilinear map from AxB to Bil{(A*xB*),k}. I suppose it takes (a,b) to the product of the evaluation maps on A* and B*. I.e. if f is in A* and g is in B*, you get f(a)g(b).

anyway this sort of nonsense becomes routine after a while. I.e. the basic thing to remember is to show things are isomorphic find a map, and in cases like this there is usually only one possible map, so whatever you can think of usually works.
 

1. What is a tensor product?

A tensor product is a mathematical operation that combines two vector spaces to create a new, larger vector space. It is used in linear algebra and other branches of mathematics to model and solve problems that involve multiple dimensions.

2. What are the two notions of tensor product?

The two notions of tensor product are the algebraic tensor product and the categorical tensor product. The algebraic tensor product is defined as the vector space generated by the elements of the two original vector spaces, while the categorical tensor product is defined in terms of universal properties and is more abstract in nature.

3. How are the two notions of tensor product related?

The two notions of tensor product are related through a universal property. This means that the algebraic tensor product can be constructed from the categorical tensor product, and vice versa. They are essentially two different ways of approaching the same mathematical concept.

4. What are some applications of tensor products in science?

Tensor products are used in a wide range of scientific fields, including physics, engineering, and computer science. They are particularly useful in quantum mechanics, where they are used to describe the state of a system with multiple particles, and in signal processing, where they are used to represent and manipulate multidimensional data.

5. How does the tensor product relate to other mathematical operations?

The tensor product is closely related to other mathematical operations such as direct sum, direct product, and inner product. It can also be extended to include more than two vector spaces, resulting in operations like tensor algebra and tensor power. Understanding the connections between these operations can provide a deeper understanding of the tensor product itself.

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