Regarding Diagonalization of Matrix by Spectral Theorem

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The spectral theorem indicates that for self-adjoint operators, a matrix P can be found such that P^{-1}AP is diagonal, with P being orthogonal. The discussion focuses on a specific symmetric matrix A structured with blocks of U and zeros, questioning if its diagonalization follows the same principles. It is suggested that the columns of P are the eigenvectors of A, contingent on A being Hermitian, which implies U must also be Hermitian. A transformation is applied to simplify A, leading to a diagonal form that allows for the diagonalization of U. This process reaffirms the applicability of the spectral theorem in this context.
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According to the spectral theorem for self-adjoint operators you can find a matrix P such that P^{-1}AP is diagonal, i.e. P^{T}AP (P can be shown to be orthogonal). I'm not sure what the result is if the same can be done for the following square (size n X n) and symmetric matrix of the form:
A=
[ U 0 U ]
[ 0 0 0 ]
[ U 0 U ]

where U is square matrix and 0 is a matrix of zeros.

If I am not mistaken the solution is that the columns of P are simply the eigenvectors of A? can anyone confirm this?
 
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First if A is Hermitian then U is also Hermitian, then use the transformation,

<br /> \left[ {\begin{array}{*{20}c}<br /> I &amp; 0 &amp; 0 \\<br /> 0 &amp; I &amp; 0 \\<br /> { - I} &amp; 0 &amp; I \\<br /> \end{array}} \right]\left[ {\begin{array}{*{20}c}<br /> U &amp; 0 &amp; U \\<br /> 0 &amp; 0 &amp; 0 \\<br /> U &amp; 0 &amp; U \\<br /> \end{array}} \right]\left[ {\begin{array}{*{20}c}<br /> I &amp; 0 &amp; { - I} \\<br /> 0 &amp; I &amp; 0 \\<br /> 0 &amp; 0 &amp; I \\<br /> \end{array}} \right] = \left[ {\begin{array}{*{20}c}<br /> U &amp; 0 &amp; 0 \\<br /> 0 &amp; 0 &amp; 0 \\<br /> 0 &amp; 0 &amp; 0 \\<br /> \end{array}} \right]<br /> <br />

Now, we are back in the business because now it is the case where you start the argument, diagonalization of a self adjoint operator where we diagonalize U now
 
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