Quantum Monte Carlo: Quest to Get Bigger, Faster, and Cheaper

Citation

Feldmann, Michael Todd (2002) Quantum Monte Carlo: Quest to Get Bigger, Faster, and Cheaper. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/4D4F-WZ34. https://resolver.caltech.edu/CaltechTHESIS:01252012-135136531

Abstract

We reexamine some fundamental Quantum Monte Carlo (QMC) algorithms with the goal of making QMC more mainstream and efficient. Two major themes exist: (1) Make QMC faster and cheaper, and (2) Make QMC more robust and easier to use. A fast "on-the-fly" algorithm to extract uncorrelated estimators from serially correlated data on a huge network is presented, DDDA. A very efficient manager-worker algorithm for QMC parallelization is presented, QMC-MW. Reduced expense VMC optimization procedure is presented to better guess initial Jast row parameter sets for hydrocarbons, GJ. I also examine the formation and decomposition of aminomethanol using a variety of methods including a test of the hydrocarbon GJ set on these oxygen- and nitrogen-containing systems. The QMC program suite QMcBeaver is available from the authors in its entirety while a user's and developer's manual is attached as supplementary material.

Thesis Files