Actions for Optimal sampling efficiency in Monte Carlo sampling with an approximate potential [electronic resource].
Optimal sampling efficiency in Monte Carlo sampling with an approximate potential [electronic resource].
- Published
- Washington, D.C. : United States. Dept. of Energy, 2009.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy. - Additional Creators
- Los Alamos National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online
- Restrictions on Access
- Free-to-read Unrestricted online access
- Summary
- Building on the work of Iftimie et al., Boltzmann sampling of an approximate potential (the 'reference' system) is used to build a Markov chain in the isothermal-isobaric ensemble. At the endpoints of the chain, the energy is evaluated at a higher level of approximation (the 'full' system) and a composite move encompassing all of the intervening steps is accepted on the basis of a modified Metropolis criterion. For reference system chains of sufficient length, consecutive full energies are statistically decorrelated and thus far fewer are required to build ensemble averages with a given variance. Without modifying the original algorithm, however, the maximum reference chain length is too short to decorrelate full configurations without dramatically lowering the acceptance probability of the composite move. This difficulty stems from the fact that the reference and full potentials sample different statistical distributions. By manipulating the thermodynamic variables characterizing the reference system (pressure and temperature, in this case), we maximize the average acceptance probability of composite moves, lengthening significantly the random walk between consecutive full energy evaluations. In this manner, the number of full energy evaluations needed to precisely characterize equilibrium properties is dramatically reduced. The method is applied to a model fluid, but implications for sampling high-dimensional systems with ab initio or density functional theory (DFT) potentials are discussed.
- Report Numbers
- E 1.99:la-ur-09-00498
E 1.99: la-ur-09-498
la-ur-09-498
la-ur-09-00498 - Other Subject(s)
- Note
- Published through SciTech Connect.
01/01/2009.
"la-ur-09-00498"
" la-ur-09-498"
Journal of Chemical Physics ISSN 0021-9606; JCPSA6 FT
Shaw, M Sam; Sewell, Thomas D; Coe, Joshua D. - Funding Information
- AC52-06NA25396
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