Riemannian proximal newton solver:

Add first version of the Riemannian Proximal Newton solver, as an alternative to the Trust Region Solver.
In each step of these two iterative solvers: For a given iterate x, we try to find a correction that decreases the energy of the nonlinear functional.
This correction is calculated using the Taylor expansion around x, resulting in the problem: Hessian(x) * correction = -gradient(x).
The correction only causes an energy decrease if the functional can be approximated correctly within a certain radius around x.
1) The trust-region algorithm ensures this using a trust-region.
2) The proximal newton method ensures this by "punishing" large corrections using a regularization factor.