Quasirandom Diffusion Monte Carlo

Diffusion Monte Carlo is a common method for estimating the properties of quantum mechanical systems by computing averages over sets of random walk simulations. We have found that by using quasirandom sequences of points in place of random or pseudorandom points in generating the simulation paths, we are able to obtain improved convergence rates and consequently reduced Monte Carlo errors for Diffusion Monte Carlo. Computational results are presented for a three dimensional harmonic oscillator and the Helium atom.