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--- eigenvalues_and_eigenvectors [2022/10/06 20:34] – [The Spectral Theorem] admin
+++ eigenvalues_and_eigenvectors [2022/10/06 23:47] (current) – [Consequences of the Spectral Theorem] admin
@@ Line 139: / Line 139: @@
 ====== Consequences of the Spectral Theorem ======
+One of the most important consequences of the spectral theorem is that any vector can be written in an eigenbasis of a normal operator, and, in that basis, the action of the operator is easy to compute.
+Let $\ket{a_j,1},\ket{a_j,2},\cdots$ be an orthonormal basis for the eigenspace corresponding to eigenvalue $a_j$.  Orthogonality and completeness imply that $\ket{a_1,1},\ket{a_1,2},\cdots,\ket{a_2,1},\ket{a_2,2},\cdots$ is a complete orthonormal basis for the whole Hilbert space:
+\[\braket{a_j,k}{a_n,m} = \delta_{j,n}\delta_{km},\qquad\qquad\qquad \sum_{j,k} \proj{a_j,k} = \hat{I}\]
+This implies that any vector $\ket{\psi}$ can be written as
+\[\ket{\psi} = \sum_{j,k} b_{jk} \ket{a_j,k},\]
+where $b_{jk} = \braket{a_j,k}{\psi}$.
+In this basis, the action of $\hat{A}$ can be computed as follows:
+\[
+  \hat{A}\ket{\psi} = \sum_{j,k} b_{jk} \hat{A}\ket{a_j,k} = \sum_{j,k} b_{jk} a_j \ket{a_j,k}.
+\]
+Another way of saying the same thing is to note that the matrix representation of $\hat{A}$ in the $\ket{a_j,k}$ basis is diagonal.  The matrix elements are:
+\[\sand{a_j,k}{\hat{A}}{a_n,m} = a_n \braket{a_j,k}{a_n,m} = a_n \delta_{jn}\delta_{km},\]
+and if we choose the ordering of basis vectors $\ket{a_1,1},\ket{a_1,2},\cdots,\ket{a_2,1},\ket{a_2,2},\cdots$, this means that the matrix is
+\[
+\left ( \begin{array}{cccccc}
+a_1 & 0 & \cdots & 0 & 0 & \cdots \\
+& a_1 & \cdots & 0 & 0 & \cdots \\
+\vdots & \vdots & \ddots & \vdots & \vdots & \ddots \\
+& 0 & \cdots & a_2 & 0 & \cdots \\
+& 0 & \cdots & 0 & a_2 & \cdots \\
+\vdots & \vdots & \ddots & \vdots & \vdots & \ddots
+\end{array} \right )
+\]
+Finally, in section 2.iii.2, we showed that a projection operator $\hat{P}$ is Hermitian $\hat{P}^{\dagger} = \hat{P}$ and idempotent $\hat{P}^2 = \hat{P}$.  We can now use the spectral theorem to prove the converse.
+Let $\ket{\psi}$ be a nonzero eigenvector of $\hat{P}$.  Since $\hat{P}$ is Hermitian, the corresponding eigenvalue, $a$, must be real.
+\begin{equation}
+\label{proj1}
+\hat{P} \ket{\psi} = a\ket{\psi}.
+\end{equation}
+Now apply \hat{P} to both sides again
+\[\hat{P}^2 \ket{\psi} = a\hat{P}\ket{\psi}.\]
+On the left hand side, we will use idempotency $\hat{P}^2 = \hat{P}$ and on the right hand side we will use the eigenvalue equation $\hat{P} \ket{\psi} = a\ket{\psi}$ again.  This gives,
+\begin{equation}
+\label{proj2}
+\hat{P} \ket{\psi} = a^2 \ket{\psi}.
+\end{equation}
+Comparing equations \eqref{proj1} and \eqref{proj2}, we have $a^2 = a$, or $a(a-1)=0$. Since $a$ is real, this means that either $a=0$ or $a=1$.
+This means that $\hat{P}$ has (at most) two eigenspaces.  Let $\hat{P}_0$ be the projector onto the $a=0$ eigenspace and $\hat{P}_1$ the projector onto the $a=1$ eigenspace.  By the spectral decomposition:
+\[\hat{P} = 0\hat{P}_0 + 1\hat{P}_1 = \hat{P}_1.\]
+Since $\hat{P}_1$ is a projector, this implies that $\hat{P}$ is a projector.  In fact, it is the projector onto its eigenspace corresponding to the eigenvalue $1$.
+{{:question-mark.png?nolink&50|}}
+====== In Class Activities ======
+  - Show that, if $\hat{A}^{-1}$ exists and $a$ is an eigenvalue of $\hat{A}$, then $\frac{1}{a}$ is an eigenvalue of $\hat{A}^{-1}$.
+  - Show that, if $\hat{A}$ is unitary, i.e. $\hat{A}^{\dagger}\hat{A} = \hat{I}$, and $a$ and $b$ are distinct eigenvalues of $a$ with eigenvectors $\ket{a}, \ket{b}$ then $\braket{b}{a} = 0$.
+HINT: Compute $\sand{b}{\hat{A}^{\dagger}\hat{A}}{a}$ in two different ways.  Once using $\hat{A}^{\dagger}\hat{A} = \hat{I}$ and once using
+\[\hat{A}\ket{a} = a\ket{a}, \qquad\qquad \hat{A}\ket{b} = b\ket{b}.\]