Smart darting diffusion Monte Carlo: Applications to lithium ion-Stockmayer clusters

Area of Science:

• Computational physics
• Quantum chemistry
• Statistical mechanics

Background:

• Diffusion Monte Carlo (DMC) simulations are crucial for studying bosonic systems.
• Traditional DMC can face sampling challenges with complex potentials, leading to quasiergodicity.
• Smart darting moves were previously introduced to enhance DMC sampling efficiency.

Purpose of the Study:

• To systematically characterize the bias introduced by smart darting moves in DMC.
• To develop and test a method for eliminating this bias in ground state energy estimations.
• To investigate the impact of smart darting moves on mixed-distributions for lithium ion-n-dipoles clusters.

Main Methods:

• Characterization of bias in Diffusion Monte Carlo (DMC) using smart darting moves.
• Application of a bias-elimination approach to ground state energy calculations.
• Simulation of lithium ion-n-dipoles clusters (n = 8-20) using modified DMC.

Main Results:

• Smart darting moves introduce a bias in the estimation of ground state energy for bosonic systems.
• A novel approach successfully eliminates the bias associated with smart darting moves.
• For lithium ion-n-dipoles clusters, ground state energies match traditional DMC for n < 14.
• Larger clusters show quantitative agreement in ground state energies but differing mixed-distributions.

Conclusions:

• The developed method effectively removes bias from smart darting DMC simulations.
• Smart darting moves may yield more reliable ground state mixed-distributions compared to traditional DMC.
• This work advances the accuracy of quantum simulations for complex systems.