Use of component tensor product in quantum mechanics?

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The discussion focuses on the use of the tensor product in quantum mechanics, specifically analyzing the measurement operator A=diag(1,-1) and its tensor product A⊗A. The resulting components indicate that while some eigenvalues are ±1, the tensor product does not yield an isomorphism for eigenvalues, meaning the eigenvalues of the tensor product of operators are not simply the product of the individual eigenvalues. The conversation highlights the necessity of understanding the implications of tensor products in quantum mechanics, particularly in relation to eigenvalue calculations.

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jk22
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suppose we consider the measurement operator A=diag(1,-1).

Then the tensor product of A by itself is in components : A\otimes A=a_{ij}a_{kl}=c_{ijkl}

giving c_{1111}=c_{2222}=1, c_{1122}=c_{2211}=-1 and all other component 0.

to diagonalize a tensor of order 4, we write :

c_{ijkl}b_{kl}=\lambda b_{ij}

hence in matrix form : \left(\begin{array}{cc} a-d & 0\\0 & -a+d\end{array}\right)=\lambda\left(\begin{array}{cc}a & b\\c & d\end{array}\right)

we have 2 cases :

\lambda\neq 0\Rightarrow b=c=0,a=-d\Rightarrow\lambda=2

the other case has eigenvalue 0.

Hence if we use the tensor product in component (instead of Kronecker product), we don't get an isomorphism for the eigenvalue, in other words the eigenvalues of the tensor product of operators is not the product of the eigenvalues.

Does anyone know if the tensor product has any meaning in quantum mechanics ?
 
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:confused: Don't understand. The definition of the tensor product is
A \otimes B = \left( \begin{array}{cccc}a_{11}b_{11}&a_{11}b_{12}&a_{12}b_{11}&a_{12}b_{12} \\a_{11}b_{21}&a_{11}b_{22}&a_{12}b_{21}&a_{12}b_{22} \\a_{21}b_{11}&a_{21}b_{12}&a_{22}b_{11}&a_{22}b_{12} \\a_{21}b_{21}&a_{21}b_{22}&a_{22}b_{21}&a_{22}b_{22} \end{array} \right)
Substitute your form for A, and what you get is sure enough diagonal, with eigenvalues ±1.
 
Indeed. I made a mistake, the application of the tensor on the multivector is C_{ijkl}d_{jl}

Thanks for your help.
 

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