By the answer to this question, computing the eigenvalues of a matrix to within $2^{-n}$ precision can be done in polylogarithmic space. Is it also possible to compute the eigenvectors of a matrix to within precision $2^{-n}$ in polylogarithmic space?
We can try to find the eigenvectors from the eigenvalues, but since we only have the eigenvalues up to precision $2^{-n}$, this seems to lead to a host of numerical stability issues (in particular, if there are two nearby eigenvalues, small perturbations in the matrix can lead to large perturbations in the eigenvectors).
Any references are appreciated!
