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The displayed matrix is an upper bidiagonal matrix. For ${\lambda }_1=1$, the right eigenvector equation $(A-I)v=0$ successively givesWe may therefore take the unit right eigenvector to be $v=e_1$.

For a left eigenvector, $(A^T-I)u=0$ givesSince ${\lambda }_i-1=-1/i$,Choosing the initial scale $u_1=1$ producesAfter normalization,The eigenvalue sensitivity is thereforewhere $n!$ is the factorial. Hence

No uniform absolute error bound of order $ϵ$ follows. Take the Jordan blockHere $\Vert B{\Vert }_2=1$ and $\Vert E{\Vert }_2=ϵ$. The exact eigenvalues of $B$ are both zero, whereasThese are admissible outputs under a backward error guarantee of size $ϵ$, yet their forward errors are $\sqrt{ϵ}$. This is the square-root splitting of a defective double eigenvalue. More generally, eigenvalue sensitivity depends on the matrix; backward stability alone does not control it. The singular value perturbation bound used in part (ii) has no equally uniform counterpart for the eigenvalues of arbitrary nonsymmetric matrices.