Doctor of Philosophy (PhD)
Physics and Astronomy
A Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ground state energies for H2O, N2 and F2 molecules. This method has two stages. The first (learning stage) reduces the minus sign problem by optimizing the states which are used in the second (QMC stage). I test the method in Single, Double excitations (SD), Single, Double, and Triple excitations (SDT), and Full Configuration Interaction (FCI) vector spaces. I also perform exact diagonalization in those vector spaces as a benchmark. In each vector space and for each molecule, I perform SiLK QMC for different bond lengths demonstrating that the SiLK QMC is applicable to many systems.
Document Availability at the Time of Submission
Release the entire work immediately for access worldwide.
Ma, Xiaoyao, "Sign Learning Kink based Quantum Monte Carlo Applied to Multiple Large Systems H2O, N2, F2" (2014). LSU Doctoral Dissertations. 1728.