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I Simplicity of tensor products?!

  1. Jun 14, 2016 #1
    I was just watching a video that was reviewing some linear algebra, and it said that this was the tensor product:

    Let's say you have a matrix A and a matrix B (both 2 by 2 matrices). If I want to calculate the tensor A ⊗ B, then the answer is basically just a matrix of matrices. In other words, I do this:

    The first matrix of the tensor product space is: the scalar multiplication of A11 * B
    The 2nd matrix of the tensor product space is: A12 * B
    The 3rd matrix is: A21 * B
    The last matrix is: A22 * B

    Over all, this makes a 4 by 4 matrix (which I will call C even though I know it should really be denoted A ⊗ B) with elements:

    C11 = A11 * B11
    C12 = A11 * B12
    C13 = A12 * B11
    C14 = A12 * B12
    C21 = A11 * B21
    C22 = A11 * B22
    C23 = A12 * B21
    C24 = A12 * B22

    C31 = A21 * B11
    C32 = A21 * B12
    C33 = A22 * B11
    C34 = A22 * B12
    C41 = A21 * B21
    C42 = A21 * B22
    C43 = A22 * B21
    C44 = A22 * B22

    I just want to ask: Is this really all there is to taking a tensor product? Is this really the process or is this just some simplified special case? I just ask this because I have asked on threads before about tensor products and tried to look up videos and web pages on them, and every time my source has just made it out to be some daunting process that was so difficult to explain and just about impossible to show an example of.
  2. jcsd
  3. Jun 14, 2016 #2


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    Staff: Mentor

    In coordinate form, your example is correct. An example of the tensor product of two matrices. In general there may be also sums of them to get other elements in the vector space of here ##\mathbb{M}_{2 \times 2} \otimes \mathbb{M}_{2 \times 2}##.

    Edit: One can arrange them in different ways, e.g. as four layers of ##2 \times 2## matrices: ##A_{11}B ,...##
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