High order Chin actions in path integral Monte Carlo.

High order actions proposed by Chin have been used for the first time in path integral Monte Carlo simulations. Contrary to the Takahashi-Imada action, which is accurate to the fourth order only for the trace, the Chin action is fully fourth order, with the additional advantage that the leading fourth-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.

Higher order and infinite Trotter-number extrapolations in path integral Monte Carlo.

Improvements beyond the primitive approximation in the path integral Monte Carlo method are explored both in a model problem and in real systems. Two different strategies are studied: The Richardson extrapolation on top of the path integral Monte Carlo data and the Takahashi-Imada action. The Richardson extrapolation, mainly combined with the primitive action, always reduces the number-of-beads dependence, helps in determining the approach to the dominant power law behavior, and all without additional computational cost.