Eigenvalue Problems
a) Let \(A\) be a real \(n\times n\) matrix with simple eigenvalue \(\lambda \), right eigenvector \(x\) (i.e., \(Ax=\lambda x\)), and left eigenvector \(y\) (i.e., \(y^*A=\lambda y^*\)). Assume that \(\lVert x\rVert _2=\lVert y\rVert _2=1\). Show that the condition number for \(\lambda \) to changes in \(A\) is given by \(s(\lambda )=1/\lvert y^*x\rvert \). Give an example of a matrix \(A\) which has a badly conditioned eigenvalue, and another matrix \(A\) which has only well-conditioned eigenvalues.
b) Consider the problem of computing an eigenvalue/eigenvector pair of a real symmetric \(m\times m\) matrix \(A\) with eigenvalues of distinct magnitudes. One algorithm for trying to do this is Rayleigh Quotient Iteration:
Guess \(v^{(0)}\) with \(\lVert v^{(0)}\rVert _2=1\).
Set \(\lambda ^{(0)}=(v^{(0)})^TAv^{(0)}\).
For \(k=1,2,3,\ldots \): \[ \text {Solve }(A-\lambda ^{(k-1)}I)w=v^{(k-1)}\text { for }w, \] \[ v^{(k)}=\frac {w}{\lVert w\rVert _2}, \] \[ \lambda ^{(k)}=(v^{(k)})^TAv^{(k)}. \] Until convergence.
Suppose that the Rayleigh Quotient Iteration iterates \(\lambda ^{(k)}\) converge to a simple eigenvalue \(\lambda \) of \(A\). Analyze the speed of convergence of \(\lambda ^{(k)}\) to \(\lambda \).