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New Quantum Monte Carlo Algorithms to Efficiently Utilize Massively Parallel Computers


Kent, David Randall, IV (2003) New Quantum Monte Carlo Algorithms to Efficiently Utilize Massively Parallel Computers. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/V64A-V618.


The exponential growth in computer power over the past few decades has been a huge boon to computational chemistry, physics, biology, and materials science. Now, a standard workstation or Linux cluster can calculate semi-quantitative properties of moderately sized systems. The next step in computational science is developing better algorithms which allow quantitative calculations of a system's properties.

A relatively new class of algorithms, known collectively as Quantum Monte Carlo (QMC), has the potential to quantitatively calculate the properties of molecular systems. Furthermore, QMC scales as O(N³) or better. This makes possible very high-level calculations on systems that are too large to be examined using standard high-level methods.

This thesis develops (1) an efficient algorithm for determining "on-the-fly" the statistical error in serially correlated data, (2) a manager-worker parallelization algorithm for QMC that allows calculations to run on heterogeneous parallel computers and computational grids, (3) a robust algorithm for optimizing Jastrow functions which have singularities for some parameter values, and (4) a proof-of-concept demonstrating that it is possible to find transferable parameter sets for large classes of compounds.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:correlation; diffusion; DMC; hydrocarbon; Jastrow; Monte Carlo; optimization; parallel; parallel correlation; QMC; quantum; quantum Monte Carlo; RDX; serial correlation; statistical analysis; statistics; supercomputing; variational; VMC
Degree Grantor:California Institute of Technology
Division:Chemistry and Chemical Engineering
Major Option:Chemistry
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Gray, Harry B. (advisor)
  • Goddard, William A., III (co-advisor)
Thesis Committee:
  • Blake, Geoffrey A. (chair)
  • Gray, Harry B.
  • Bruck, Jehoshua
  • Lewis, Nathan Saul
  • Goddard, William A., III
Defense Date:10 March 2003
Non-Caltech Author Email:drkent (AT)
Funding AgencyGrant Number
Fannie and John Hertz Foundation fellowshipUNSPECIFIED
Welch FoundationUNSPECIFIED
Record Number:CaltechETD:etd-02252003-134943
Persistent URL:
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:748
Deposited By: Imported from ETD-db
Deposited On:27 Feb 2003
Last Modified:19 Feb 2021 00:16

Thesis Files

PDF (david_randall_kent_iv-dissertation.pdf) - Final Version
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