Computation of nodal surfaces in fixed-node diffusion Monte Carlo calculations using a genetic algorithm
Abstract
The fixed-node diffusion Monte Carlo (DMC) algorithm is a powerful way of computing excited state energies in a remarkably diverse number of contexts in quantum chemistry and physics. The main difficulty in implementing the procedure lies in obtaining a good estimate of the nodal surface of the excited state in question. Although the nodal surface can sometimes be obtained from symmetry or by making approximations this is not always the case. In any event, nodal surfaces are usually obtained in an ad hoc way. In fact, the search for nodal surfaces can be formulated as an optimization problem within the DMC procedure itself. Here we investigate the use of a genetic algorithm to systematically and automatically compute nodal surfaces. Application is made to the computation of excited states of the