I just found some interesting question about matrix square roots and I came to think of one way to find them, or at least reduce them to a set of simpler problems.
Assume we have a matrix $\bf A$ and it can be put on some Jordan form:
$${\bf A} = {\bf SJS}^{-1}$$
Where $\bf J$ is block-diagonal consisting of famous Jordan blocks of the shape:
$${\bf J_{k}} = \begin{bmatrix} \lambda_k&1&0&\cdots&0\\0&\ddots&\ddots& & 0\\\vdots&\ddots&\ddots&\ddots&\vdots\\0&\cdots&0&\lambda_k&1\\0&\cdots&\cdots&0&\lambda_k\end{bmatrix}$$
In other words main diagonal full with eigenvalue $\lambda_k$ and first off-diagonal filled with ones.
The problem of finding some n'th root to $\bf A$ can now be written $${\bf SJ}^{1/n}{\bf S}^{-1}$$ (Why?).
So If I am correct so far.. we have reduced down to find some way of calculating square root of such Jordan blocks $\bf J_k$, and in simplest case blocks of dimensionality 1, finding some root over our scalar field (for the eigenvalues themselves).
Firstly, is this reasoning correct so far?
Secondly, how can we approach finding square root to matrices of the form $\bf J_k$. Is there some simplification or short-cut that can be done?