Nested Markov Chain Monte Carlo Sampling of a Density Functional Theory Potential: Equilibrium Thermodynamics of Dense Fluid Nitrogen

Abstract

An optimized variant of the nested Markov chain Monte Carlo [n(MC)2] method is applied to fluid N2. In this implementation of n(MC)2, isothermal-isobaric (NPT) ensemble sampling on the basis of a pair potential (the "reference" system) is used to enhance the efficiency of sampling based on Perdew-Burke-Ernzerhof density functional theory with a 6-31G* basis set (PBE/6-31G*, the "full" system). A long sequence of Monte Carlo steps taken in the reference system is converted into a trial step taken in the full system; for a good choice of reference potential, these trial steps have a high probability of acceptance. Using decorrelated samples drawn from the reference distribution, the pressure and temperature of the full system are varied such that its distribution overlaps maximally with that of the reference system. Optimized pressures and temperatures then serve as input parameters for n(MC)2 sampling of dense fluid N2 over a wide range of thermodynamic conditions. The simulation results are combined to construct the Hugoniot of nitrogen fluid, yielding predictions in excellent agreement with experiment.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2009
Accession Number
ADA520398

Entities

People

  • Joshua D. Coe
  • M. S. Shaw
  • Thomas D. Sewell

Organizations

  • Los Alamos National Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Chemical Reactions
  • Chemistry
  • Climate Change
  • Density Functional Theory
  • Equations
  • Ground State
  • Markov Chains
  • Materials
  • Military Research
  • Molecular Dynamics
  • Monte Carlo Method
  • New York
  • Probability
  • Sampling
  • Shock Waves
  • Three Dimensional

Readers

  • Operations Research
  • Quantum Chemistry
  • Statistical inference.