Simutanious diagonalization of 2 matrices

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Gary Roach
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Homework Statement



From Principles of Quantum Mechanics, 2nd edition by R Shankar, problem
1.8.10:

By considering the commutator, show that the following Hermitian matrices may be
simultaneously diagonalized. Find the eigenvectors common to both and verify
that under a unitary transformation to this basis, both matrices are
diagonalized.

[itex]\textbf{Theorem 13:}[/itex] If [itex]\Omega\ and\ \Lambda[/itex] are two commuting Hermitian
operators, there exists (at least) a basis of common eigenvectors that diagonalizes them
both.

Homework Equations


[itex]\Omega = \begin{vmatrix}<br /> 1 & 0 & 1 \\<br /> 0 & 0 & 0 \\<br /> 1 & 0 & 1<br /> \end{vmatrix}[/itex]

[itex]\Lambda =[/itex][itex] \begin{vmatrix}<br /> 2 & 1 & 1\\<br /> 1 & 0 & -1\\<br /> 1 & -1 & 2<br /> \end{vmatrix}[/itex]

[[itex]\Omega[/itex] , [itex]\Lambda[/itex]] = 0

The Attempt at a Solution



The two matraces definitely meet the requirements of Theorem 13. Next computer
the eigenvalues of [itex]\Omega\ and\ \Lambda[/itex]:

[itex]\Omega[/itex]= [itex]\begin{vmatrix}<br /> 1-\omega & 0 & 1 \\<br /> 0 & -\omega & 0 \\<br /> 1 & 0 & 1-\omega<br /> \end{vmatrix} <br /> \ \Rightarrow (1-\omega)^2 (-\omega) + \omega) = 0 \ \Rightarrow \omega = 0, 0,<br /> 2[/itex]

[itex]\Lambda[/itex]=[itex]\begin{vmatrix}<br /> 2-\omega & 1 & 1 \\<br /> 1 & -\omega & -1 \\<br /> 1 & -1 & 2-\omega<br /> \end{vmatrix} <br /> \ \Rightarrow (2-\omega)(\omega^2 -2\omega - 1) -2(2-\omega) = 0 \Rightarrow<br /> \omega = 2, 3, -1[/itex]

Next computer the eigenvectors:

[itex]\Lambda | \omega = 2 >[/itex]= [itex]\begin{vmatrix}<br /> 0 & 1 & 1 \\<br /> 1 & -2 & -1 \\<br /> 1 & -1 & 0<br /> \end{vmatrix}[/itex] = 0 [itex]\Rightarrow x_2 + x_3 = 0\ ;\ x_1 - x_2 = 0 \Rightarrow<br /> x_1= 1, X_2=1, x_3=-1[/itex]

[itex]\Lambda | \omega = 2 >[/itex]= [itex]\begin{vmatrix}1\\1\\-1\end{vmatrix}[/itex]

[itex]\Lambda | \omega = 3 >[/itex]= [itex]\begin{vmatrix}<br /> -1 & 1 & 1 \\<br /> 1 & -3 & -1 \\<br /> 1 & -1 &-1<br /> \end{vmatrix}[/itex] = 0 [itex]\Rightarrow -x_1 + x_2 + x_3 = 0\ ;<br /> x_1 -3x_2 - x_3 = 0\ ;\ x_1 - x_2 - x_3 = 0 \Rightarrow x_1=1, x_2=0, x_3=1[/itex]

[itex]\Lambda | \omega = 3 >[/itex]= [itex]\begin{vmatrix}1\\0\\1\end{vmatrix}[/itex]

[itex]\Lambda | \omega = -1 >[/itex]= [itex]\begin{vmatrix}<br /> 3 & 1 & 1 \\<br /> 1 & 1 & -1 \\<br /> 1 & -1 &3<br /> \end{vmatrix}[/itex] = 0 [itex]\Rightarrow 3x_1 + x_2 + x_3 = 0\ ;<br /> x_1 + x_2 - x_3 = 0\ ;\ x_1 - x_2 + 3x_3 = 0 \Rightarrow x_1=1, x_2=-2, x_3=-1[/itex]

[itex]\Lambda | \omega = -1 >[/itex]= [itex]\begin{vmatrix}1\\-2\\-1\end{vmatrix}[/itex]

And from [itex]\Omega[/itex]
[itex]\Omega | \omega = 0 >[/itex] = [itex]\begin{vmatrix}<br /> 1 & 0 & 1 \\<br /> 0 & 0 & 0 \\<br /> 1 & 0 & 1<br /> \end{vmatrix}[/itex] = 0 [itex]\Rightarrow x_1 + x_3 = 0\ ;\ x_2=0 <br /> \Rightarrow x_1=1, x_2=-0, x_3=-1[/itex]

[itex]\Omega | \omega = 0 >[/itex]= [itex]\begin{vmatrix}1\\0\\-1\end{vmatrix}[/itex] twice

[itex]\Omega | \omega = 2 >[/itex] = [itex]\begin{vmatrix}<br /> -1 & 0 & 1 \\<br /> 0 & -2 & 0 \\<br /> 1 & 0 & -1<br /> \end{vmatrix} $ = 0 [itex]\Rightarrow -x_1 + x_3 = 0\ ;\ x_2=0<br /> \Rightarrow x_1=1, x_2=-0, x_3=1[/itex]<br /> <br /> [itex]\Omega | \omega = 2 >[/itex]= [itex]\begin{vmatrix}1\\0\\1\end{vmatrix}[/itex]<br /> <br /> In summary the eigenvectors are:<br /> <br /> [itex]\begin{vmatrix}1\\1\\-1\end{vmatrix}[/itex] , [itex] \begin{vmatrix}1\\0\\1\end{vmatrix}[/itex] , [itex] \begin{vmatrix}1\\-2\\-1\end{vmatrix}[/itex] , [itex] \begin{vmatrix}1\\0\\-1\end{vmatrix}[/itex] , [itex] \begin{vmatrix}1\\0\\1\end{vmatrix}[/itex] <br /> <br /> And here is the problem. There is no way to build a unitary matrix (say<br /> [itex]\textbf{U}[/itex]) from these vectors. All possible combinations lead to non-Hemitian<br /> matrices. With out a unitary matrix the diagonalization process -<br /> [itex]\textbf{U} \varLambda \textbf{U}^\dagger[/itex]= diagonalized matrix - can not be<br /> completed.<br /> <br /> Where have I gone wrong?[/itex]
 
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For the first matrix, Ω, let's call the three eigenvectors [itex]\vert \omega=2 \rangle[/itex], [itex]\vert \omega=0_1 \rangle[/itex], and [itex]\vert \omega=0_2 \rangle[/itex]. Similarly, for the second matrix, Λ, you have the eigenvectors [itex]\vert \lambda=3 \rangle[/itex], [itex]\vert \lambda=2 \rangle[/itex], and [itex]\vert \lambda=-1 \rangle[/itex].

The first thing to note is that [itex]\vert \omega=2 \rangle[/itex] and [itex]\vert \lambda=3 \rangle[/itex] are the same vector, namely (1, 0, 1)T. That means {[itex]\vert \omega=0_1 \rangle[/itex], [itex]\vert \omega=0_2 \rangle[/itex]} and {[itex]\vert \lambda=2 \rangle[/itex], [itex]\vert \lambda=-1 \rangle[/itex]} span the same subspace. The second thing is that because Ω's vectors are degenerate, any linear combination of those two vectors is also an eigenvector with eigenvalue 0.
 
What you missed is that in getting the zero eigenvectors for Ω, x2=0 is not required. x2 can be anything. Saying "[1,0,-1] twice" makes no sense. So a basis for zero eigenvectors is [1,0,-1] and [0,1,0]. Then, as vela points out, the other eigenvectors for Λ lie in that subspace.
 
I'm still thinking about your replies (reading like crazy). I haven't disappeared. My Linear Algebra seems to be a bit rusty. I really appreciate the help.

Gary R.
 
I think I need to back up on this problem. Per Shankar:

If [itex]\Lambda[/itex] is a Hermitian matrix, there exists a unitary matrix U (built out of the eigenvectors of [itex]\Lambda[/itex] such that [itex]U^\dagger \Lambda U[/itex] is diagonalized.

So let's use Lambda from above since it is Hermitian. And we have the eigenvectors

[tex]\begin{vmatrix}1\\1\\-1\end{vmatrix}\ ,\ \begin{vmatrix}1\\0\\1\end{vmatrix}\ , \ <br /> \begin{vmatrix}1\\-2\\-1\end{vmatrix}[/tex]

Then [tex]U = \begin{vmatrix}1&1&1\\1&0&-2\\-1&1&-1\end{vmatrix}\ <br /> U^\dagger = \begin{vmatrix}1&1&-1\\1&0&1\\1&-2&-1\end{vmatrix}[/tex]

An there is the problem. Per Shankar, U is unitary and [itex]U^\dagger U = I[/itex]

This isn't. What have I done wrong.
 
Finallly. The normalization of the eigenvectors of [itex]\Lambda[/itex] fixed the problem.
[itex]U^\dagger*U now = I, U^\dagger*\Lambda * U[/itex]= diagonal with eigenvalues in the diagonal. The same with [itex]\Omega[/itex].

Question: Does this work only because the two matrices share a common eigenvector?

Gary R. and thank you all for the help
 
Gary Roach said:
Finallly. The normalization of the eigenvectors of [itex]\Lambda[/itex] fixed the problem.
[itex]U^\dagger*U now = I, U^\dagger*\Lambda * U[/itex]= diagonal with eigenvalues in the diagonal. The same with [itex]\Omega[/itex].

Question: Does this work only because the two matrices share a common eigenvector?

Gary R. and thank you all for the help

Yes, you can only simultaneously diagonalize if the matrices have a common basis of eigenvectors. Being Hermitian and commuting guarantees this.