Monte Carlo generation of localized particle trajectories

We introduce modifications to Monte Carlo simulations of the Feynman path integral that improve sampling of localized interactions. The algorithms generate trajectories in simple background potentials designed to concentrate them around the interaction region, reminiscent of importance sampling. This improves statistical sampling of the system and overcomes a long-time undersampling problem caused by the spatial diffusion inherent in Brownian motion. We prove the validity of our approach using previous analytic work on the distribution of values of the Wilson line over path integral trajectories and illustrate the improvements on some simple quantum mechanical systems.