Semiclassically Based Monte Carlo Evaluation of Path Integrals

Abstract

The semiclassical approximation serves as an ideal basis for Monte Carlo evaluation of Euclidean path integrals. When the semiclassical approximation is good, the averaging converges rapidly. Comparison with conventional techniques shows a great advantage in computational efficiency. A simple one-dimensional example is presented, along with a discussion of how the technique is extended to several degrees of freedom.