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A Investigation of Exact Quantum Monte Carlo Methods for Small Molecules.

Bin Chen

Published Jan 1, 1994• 0 citations
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Springer eBooks•Jan 1, 2011•0 citations
A method for accelerating the rate of convergence of the long-time (or small-temperatur) limit of quantum Monte Carlo approaches is presented. To do that, a variation of the Lanczós algorithm suitable for QMC data is introduced. This algorithm allows one to extract more information from correlation functions at small times, thus avoiding large statistical fluctuations associated with large times. It is first applied to an exactly soluble system and then to the LiH molecule. Calculations using both the fixed-node and nodal-release approaches are discussed.
This work investigates the accuracy of real-space quantum Monte Carlo (QMC) methods for calculating molecular geometries. We present the equilibrium bond lengths of a test set of 30 diatomic molecules calculated using variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) methods. The effect of different trial wavefunctions is investigated using single determinants constructed from Hartree-Fock (HF) and Density Functional Theory (DFT) orbitals with LDA, PBE, and B3LYP functionals, as well as small multi-configurational self-consistent field (MCSCF) multi-determinant expansions. When compared to experimental geometries, all DMC methods exhibit smaller mean-absolute deviations (MADs) than those given by HF, DFT, and MCSCF. The most accurate MAD of 3 ± 2 × 10(-3) Å is achieved using DMC with a small multi-determinant expansion. However, the more computationally efficient multi-determinant VMC method has a similar MAD of only 4.0 ± 0.9 × 10(-3) Å, suggesting that QMC forces calculated from the relatively simple VMC algorithm may often be sufficient for accurate molecular geometries.