Numerical implementation of some reweighted path integral methods

Abstract

The reweighted random series techniques provide finite-dimensional approximations to the quantum density matrix of a physical system that have fast asymptotic convergence. We study two special reweighted techniques that are based upon the Levy-Ciesielski and Wiener-Fourier series, respectively. In agreement with the theoretical predictions, we demonstrate by numerical examples that the asymptotic convergence of the two reweighted methods is cubic for smooth enough potentials. For each reweighted technique, we propose some minimalist quadrature techniques for the computation of the path averages. These quadrature techniques are designed to preserve the asymptotic convergence of the original methods.

15 pages, 10 figures, submitted to JCP

References in corpus (4)

• Optimal series representations for numerical path integral simulations
• Random Series and Discrete Path Integral methods: The Levy-Ciesielski implementation
• The Partial Averaging method
• Asymptotic convergence of the partial averaging technique

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