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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. http://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 Jastrow 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.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Chemistry
Degree Grantor:California Institute of Technology
Division:Chemistry and Chemical Engineering
Major Option:Chemistry
Thesis Availability:Restricted to Caltech community only
Research Advisor(s):
  • Goddard, William A., III
Thesis Committee:
  • Unknown, Unknown
Defense Date:20 May 2002
Record Number:CaltechTHESIS:01252012-135136531
Persistent URL:http://resolver.caltech.edu/CaltechTHESIS:01252012-135136531
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:6777
Collection:CaltechTHESIS
Deposited By: Benjamin Perez
Deposited On:25 Jan 2012 22:14
Last Modified:26 Dec 2012 04:39

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