Let $A$ and $B$ be $n \times n$ matrices with $n$ distinct eigenvalues $\lambda_1, \ldots, \lambda_n$ and $\mu_1, \ldots, \mu_n$, respectively.
Is it possible to estimate the difference $|\lambda_i - \mu_i|$ between the eigenvalues of $A$ and $B$ in terms of the matrix norm of $A - B$? If so, which norm should be used, and how can this estimate be determined?
In particular, since all norms are equivalent in finte dimensional space, does $\|A\| \rightarrow 0$ imply $\lambda_i \rightarrow 0$?