Interpolating Moving Least-squares Methods for Fitting Potential Energy Surfaces: Using Classical Trajectories to Explore Configuration Space
We develop two approaches for growing a fitted potential energy surface (PES) by the interpolating moving least-squares (IMLS) technique using classical trajectories. We illustrate both approaches by calculating nitrous acid (HONO) cis→trans isomerization trajectories under the control of ab initio forces from low-level HF/cc-pVDZ electronic structure calculations. In this illustrative example, as few as 300 ab initio energy/gradient calculations are required to converge the isomerization rate constant at a fixed energy to ∼ 10%. Neither approach requires any preliminary electronic structure calculations or initial approximate representation of the PES (beyond information required for trajectory initial conditions). Hessians are not required. Both approaches rely on the fitting error estimation properties of IMLS fits. The first approach, called IMLS-accelerated direct dynamics, propagates individual trajectories directly with no preliminary exploratory trajectories. The PES is grown “on the fly” with the computation of new ab initio data only when a fitting error estimate exceeds a prescribed tight tolerance. The second approach, called dynamics-driven IMLS fitting, uses relatively inexpensive exploratory trajectories to both determine and fit the dynamically accessible configuration space. Once exploratory trajectories no longer find configurations with fitting error estimates higher than the designated accuracy, the IMLS fit is considered to be complete and usable in classical trajectory calculations or other applications.
R. Dawes et al., "Interpolating Moving Least-squares Methods for Fitting Potential Energy Surfaces: Using Classical Trajectories to Explore Configuration Space," Journal of Chemical Physics, vol. 130, no. 14, American Institute of Physics (AIP), Apr 2009.
The definitive version is available at http://dx.doi.org/10.1063/1.3111261
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