Is there a setting in which finding eigenvalues/eigenvectors is computationally hard? Or at least, not known to be computationally easy?
For example, how computationally hard or easy is it to find eigenvalues/eigenvectors of matrices over finite fields? Suppose the field has size exponential in the dimension. (Does the QR algorithm still converge?)
How about finding eigenvalues/eigenvectors of sparse matrices?