In the context of biophysics, on the other hand, modeling ionic solutions is paramount, which makes the (linearized) Poisson-Boltzmann ((L)PB) model the de facto standard. Many numerical realizations of such a model have been implemented and are available to the community in popular software that solves the (L)PB equation using a variety of methods that include finite differences , finite elements , and boundary elements . As the modeled systems are typically large biomolecules described with a classical force field (i.e., point charges, or sometimes more sophisticated treatments including distributed multipoles and polarizabilities) and not with quantum mechanics, the treatment of solvation can become a cost-dominating factor in such computations. Therefore, much attention has been given to the numerical efficiency of the implementations, and linear scaling techniques are commonly used to afford the treatment of very large systems. Furthermore, due to the complexity of the systems studied, the use of accurate molecular surfaces, such as the Connolly also known as Solvent Excluded Surface (SES) to define the molecular cavity is common, to be compared with the simpler Van der Waals or Solvent Accessible Surfaces (SAS) used in quantum chemistry applications. On the other hand, the calculation of analytical gradients and the coupling to quantum mechanical codes have not received the same amount of attention as the models used in quantum chemistry. Despite the differences, there are several regions of overlap, from PCSM being applied to large systems treated with multiscale QM/MM methods , to the possibility of performing Molecular Dynamics simulations in a polarizable continuum solvent , that makes the possibility of bridging the gap between the two communities interesting.