High order Chin actions in path integral Monte Carlo

TL;DR

This paper introduces the use of high order Chin actions in path integral Monte Carlo, achieving improved efficiency and accuracy in simulations of quantum systems by optimizing parameters to reduce the number of beads needed.

Contribution

The paper demonstrates the first application of Chin's high order actions in PIMC, optimizing parameters for sixth-order accuracy and significantly enhancing computational efficiency.

Findings

Achieved sixth-order error dependence in PIMC simulations.

Reduced the number of beads needed by a factor of ten compared to primitive approximation.

Validated the approach on harmonic oscillator, H2 drop, and superfluid helium simulations.

Abstract

High order actions proposed by Chin have been used for the first time in path integral Monte Carlo simulations. Contrarily to the Takahashi-Imada action, which is accurate to fourth order only for the trace, the Chin action is fully fourth order, with the additional advantage that the leading fourth and sixth order error coefficients are finely tunable. By optimizing two free parameters entering in the new action we show that the time step error dependence achieved is best fitted with a sixth order law. The computational effort per bead is increased but the total number of beads is greatly reduced, and the efficiency improvement with respect to the primitive approximation is approximately a factor of ten. The Chin action is tested in a one-dimensional harmonic oscillator, a H$_2$ drop, and bulk liquid $^4$He. In all cases a sixth-order law is obtained with values of the number of beads that compare well with the pair action approximation in the stringent test of superfluid $^4$He.