On the fly nodal searches in importance sampled fixed-node diffusion Monte Carlo using a parallel, fine-grained, genetic algorithm

A method for finding nodal surfaces on the fly in importance-sampled, fixed-node diffusion Monte Carlo calculations is described. The procedure relies on minimizing the difference between the nodal functions of the guiding wave function, ΨT, and H ˆ Ψ T , where H ˆ is the Hamiltonian. This is done by allowing the trial function to depend on a set of parameters whose values are then optimized using a parallel genetic algorithm (e.g., the Pikaia code developed in astrophysics). Application is made to the calculation of several excited states of a non-integrable two-dimensional quartic oscillator and to excited states of the He–C2H2 complex.