Check the spectral theorem for this matrix

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The discussion focuses on proving properties related to the spectral theorem for a matrix with three projection operators, P1, P2, and P3. The user expresses difficulty in understanding specific conditions (ii, iii, and iv) when transitioning from continuous to discrete eigenvalue scenarios. It is clarified that E(λ) represents a projection operator-valued function, which behaves as a step function for discrete eigenvalues. The derivative dE(λ)/dλ exhibits delta function spikes at each eigenvalue, allowing for the integration to yield the discrete eigenvalues. The conversation emphasizes the challenges of interpreting these mathematical concepts in discrete contexts.
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Homework Statement
.
Relevant Equations
.
1615235843259.png

I found three projection operators
$$P_{1}=
\begin{pmatrix}
1/2 & & \\
& -\sqrt{2}/2 & \\
& & 1/2
\end{pmatrix}$$
$$P_{2}=
\begin{pmatrix}
1/2 & & \\
& \sqrt{2}/2 & \\
& & 1/2
\end{pmatrix}$$
$$P_{3}=
\begin{pmatrix}
-1/\sqrt{2} & & \\
& & \\
& & 1/\sqrt{2}
\end{pmatrix}$$

From this five properties
1615235980298.png
, i am having trouble to prove the ii, iii, and iv. I mean, i could understand this conditions in the continuous situation, in which we can make the "eigenvalue tends to" something. But how to interpret it when we are dealing with discrete conditions? In which we have really just three eigenvalues.
 

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What is the definition of E in those statements?
 
##E(\lambda)## is an projection (operator) valued function. In the case of discrete eigenvalues it is a step function which has a step at each eigenvalue . ##dE(\lambda)/d\lambda## has a ##\delta## function spike at each eigenvalue, which gives you the discrete eigenvalue when you integrate.
 

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