# (2,0) tensor is not a tensor product of two vectors?

• I
• voila
In summary, this problem asks why a (2,0) tensor can't be written as a tensor product of two vectors. The answer is that a (2,0) tensor has rank 2 and can't be written as a direct product of two vectors.
voila
Hi. I'm trying to understand tensors and I've come across this problem:

"Show that, in general, a (2, 0) tensor can't be written as a tensor product of two vectors".

Well, prior to that sentence, I would have thought it could... Why not?

let a (2,0) tensor be a product of two vectors. Take a coordinate system such that one of the vectors has the form (1,0,...0)

voila
A (2,0) tensor is a linear combination of such tensor products. You must show that not all sych linear combinations are tensor products of two vectors.

voila
May I state clearly that this is not a problem I must solve for class, this was just an example written somewhere which suggested we did it (thus why I didn't provide an attempt at solving it, just asking why it is that way). I still can't see why.

Oh, I think I'm getting it. Thinking about the matrix representation, that's just like stating that there are such matrices that can't be written as the tensor product of two vectors?

voila said:
Oh, I think I'm getting it. Thinking about the matrix representation, that's just like stating that there are such matrices that can't be written as the tensor product of two vectors?
Yes. You can write all matrices as a sum of (2,0) tensors, but a single tensor ##a \otimes b## will always result in a matrix of rank 1.

voila
The tensor notation such as ##(2,0)## only applies when the tensor is made up of a number of copies of a particular vector space and its dual vector space.
##\mathbf{a} \otimes \mathbf{b}## with ##\mathbf{a},\mathbf{b}\in V## is a ##(2,0)## tensor which has total rank 2. The main point here was all ##(2,0)## tensors cannot be expressed ##\mathbf{a} \otimes \mathbf{b}## .

voila
MisterX said:
##\mathbf{a} \otimes \mathbf{b}## with ##\mathbf{a},\mathbf{b}\in V## is a ##(2,0)## tensor which has total rank 2.
Just a remark.
Rank in this context is a bit of an ill-fated notation, since it has nothing to do with the rank of linear transformations which are also part of the context. Degree is (IMO) a far better word for it.

voila and MisterX
Here is the sketch of a proof. Let ##V## be a finite dimensional real vector space with dimension greater than 2 (the statement is simply not true for ##\dim V=1##, since any real number ##a## can be written as ##a=1\cdot a##). Let ##(e_j)## be a orthonormal basis and ##T=e_1 \otimes e_2 - e_2 \otimes e_1##. Suppose ##T=a \otimes b##, for some ##a, b \in V##. By equating components, get a contradiction. So there exists ##(2,0)## tensors which cannot be written as the direct product of vectors.

Note: The counterexample above was inspired by the singlet state in Quantum Mechanics.

voila
Thank you all for your answers. I reckon it's a rather simple question, but I was just beginning to study tensors and couldn't get my mind around it.

## 1. What exactly is a (2,0) tensor?

A (2,0) tensor is a mathematical object that represents a linear mapping between two vector spaces. It has two sets of indices, indicating that it takes two vectors as inputs and produces a scalar as an output.

## 2. How is a (2,0) tensor different from a tensor product of two vectors?

A (2,0) tensor cannot be expressed as a tensor product of two vectors because it represents a different type of mathematical object. A tensor product of two vectors is a way of combining two vectors to create a new vector, while a (2,0) tensor is a linear mapping between two vector spaces.

## 3. Why can't a (2,0) tensor be expressed as a tensor product of two vectors?

This is because a (2,0) tensor has two sets of indices, while a tensor product of two vectors only has one set of indices. In order for a tensor to be expressed as a tensor product, it must have the same number of sets of indices as the number of vectors being multiplied.

## 4. What is the significance of a (2,0) tensor in physics?

(2,0) tensors are commonly used in physics to represent physical quantities that have both magnitude and direction. This includes quantities such as force, velocity, and stress.

## 5. Can a (2,0) tensor be represented graphically?

Yes, a (2,0) tensor can be represented graphically as a matrix with two rows and zero columns. Each element in the matrix represents the coefficient of the linear mapping between the two vector spaces.

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