What is the Tensor Product of Vectors and How Does It Differ Across Contexts?

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The tensor product of two vectors results in a new tensor whose dimensions are the product of the original vectors' dimensions, often represented as a matrix. In the context of quantum mechanics, the tensor product of basis vectors can yield higher-dimensional vectors. While the tensor product of two type (1,0) tensors (vectors) is a (2,0) tensor, which can be represented as a matrix, it is important to note that not all tensors can be represented as matrices, especially when dealing with higher-order tensors. Higher-order tensors can represent more complex linear maps that cannot be captured by matrices alone. Understanding the distinction between tensors and matrices is crucial for grasping their applications in various fields, including physics and mathematics.
Harel
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Hey it might be a stupid question but I saw that the tensor product of 2 vectors with dim m and n gives another vector with dimension mn and in another context I saw that the tensor product of vector gives a metrix. For example from sean carroll's book: "If T is a (k,l) tensor and S is a (m, n) tensor, we define a (k + m, l + n) tensor T ⊗ S"
so the tensor product of two type 1 tensors,k=1,vectors, is a metrix
and in the context of quantum mechanic I saw
(1,0)⊗(1,0)↦(1,0,0,0) when those our basis vectors.
I'm sure I'm just getting something wrong but I am hopefull that you can explain me what.
 
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Harel said:
so the tensor product of two type 1 tensors,k=1,vectors, is a metrix
Why it would be? If one of them is dual vector, then it might be. I will give you some examples:
\begin{pmatrix} 1 \\ 2 \end{pmatrix} \otimes \begin{pmatrix} 1 & 2 \end{pmatrix} = \begin{pmatrix} 1 \times \begin{pmatrix} 1 & 2 \end{pmatrix}\\ 2 \times \begin{pmatrix} 1 & 2 \end{pmatrix} \end{pmatrix} = \begin{pmatrix} 1 & 2 \\ 2 & 4 \end{pmatrix},
\begin{pmatrix} 1 & 2 \end{pmatrix} \otimes \begin{pmatrix} 1 & 2 \end{pmatrix} = \begin{pmatrix} 1 \times \begin{pmatrix} 1 & 2 \end{pmatrix} & 2 \times \begin{pmatrix} 1 & 2 \end{pmatrix} \end{pmatrix} = \begin{pmatrix} 1 & 2 & 2 & 4 \end{pmatrix}
 
Daeho Ro said:
Why it would be? If one of them is dual vector, then it might be. I will give you some examples:
\begin{pmatrix} 1 \\ 2 \end{pmatrix} \otimes \begin{pmatrix} 1 & 2 \end{pmatrix} = \begin{pmatrix} 1 \times \begin{pmatrix} 1 & 2 \end{pmatrix}\\ 2 \times \begin{pmatrix} 1 & 2 \end{pmatrix} \end{pmatrix} = \begin{pmatrix} 1 & 2 \\ 2 & 4 \end{pmatrix},
\begin{pmatrix} 1 & 2 \end{pmatrix} \otimes \begin{pmatrix} 1 & 2 \end{pmatrix} = \begin{pmatrix} 1 \times \begin{pmatrix} 1 & 2 \end{pmatrix} & 2 \times \begin{pmatrix} 1 & 2 \end{pmatrix} \end{pmatrix} = \begin{pmatrix} 1 & 2 & 2 & 4 \end{pmatrix}
Because by the defenition of sean, let's take a type (1,0) tensor which is a vector and another (1,0) tensor which is also a vector and the product will be a (2,0) tensor, which is a metrix.
 
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Harel said:
Hey it might be a stupid question but I saw that the tensor product of 2 vectors with dim m and n gives another vector with dimension mn and in another context I saw that the tensor product of vector gives a metrix. For example from sean carroll's book: "If T is a (k,l) tensor and S is a (m, n) tensor, we define a (k + m, l + n) tensor T ⊗ S"
so the tensor product of two type 1 tensors,k=1,vectors, is a metrix
and in the context of quantum mechanic I saw
(1,0)⊗(1,0)↦(1,0,0,0) when those our basis vectors.
I'm sure I'm just getting something wrong but I am hopefull that you can explain me what.

A vector can be seen as a ## 1 \times n ## matrix.
 
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Harel said:
Because by the defenition of sean, let's take a type (1,0) tensor which is a vector and another (1,0) tensor which is also a vector and the product will be a (2,0) tensor.
That is true. But, the results of mine are matrices with the size 2 \times 2 and 1 \times 4.
 
Harel said:
Hey it might be a stupid question but I saw that the tensor product of 2 vectors with dim m and n gives another vector with dimension mn and in another context I saw that the tensor product of vector gives a metrix. For example from sean carroll's book: "If T is a (k,l) tensor and S is a (m, n) tensor, we define a (k + m, l + n) tensor T ⊗ S"
so the tensor product of two type 1 tensors,k=1,vectors, is a metrix
<Snip>.

Actually, if your map is k-linear ( in any " coordinate") for k>2 (where you may have quadratic forms), it is not representable as a matrix anymore. That is the actual point of tensors: to represent k - , or j- ( k,j pos. integers) linear maps in many variables, which is not feasible with matrices alone whenever you have an index >2.
Only linear and bilinear maps may be represented using matrices.
 
I feel compelled to point out that a tensor can be represented by a matrix in a given coordinate system, but, strictly speaking, a tensor is NOT a matrix.
 
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HallsofIvy said:
I feel compelled to point out that a tensor can be represented by a matrix in a given coordinate system, but, strictly speaking, a tensor is NOT a matrix.
How do you represent a higher-order tensor as a matrix? e.g., a 3-linear map .
 
In the same sense that a "vector" is a 1 by 3 matrix, so a higher order tensor can be represented by a "3 by 3 by 3" or higher matrix. I admit that is stretching the concept of "matrix" a bit far. My point was simply that a matrix is NOT a tensor.
 

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