- We have finished code development for a
series of IMLS fitting methods that we plan to offer as free downloads.
- We have recently developed a high-order local version
of IMLS in which stored basis set expansions allow efficient use of
high-order fits.1,2
- Two main types of codes will be available
- Spectroscopy/
dynamics (coming
soon!!): we have automatic surface generators that will
generate global potentials for 3, 4, and 5+ atom systems to a
predefined accuracy in a user specified energy range. The
automatic PES generator automatically calls a prefered electronic
structure code (e.g. Gaussian) at a minimal number of configurations,
making use of 1) value, 2) value and gradient, or 3) value gradient and
Hessian data depending on the ab
initio method chosen. In a recent test we were able to
reproduce a spectroscopic quality surface for methane (9-D) at the
CCSD(T) level in less than 1 week on a single processor. We have also
developed a parallel code using MPI.
- Trajectories (still
in development): We are developing a PES interface for classical
trajectories codes that will construct an accurate and efficient ab initio PES "on
the fly". Our IMLS PES fit with automatic surface generation
will dynamically determine whether or not the trajectory is in a region
that has been fit to sufficient accuracy. Ab initio data will
be added where needed and IMLS fitted energies will be determined where
suitable.
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Automatic PES generation for HOOH (6-D) required only 1400 points with value and gradient to acheive 0.1 kcal/mol RMS accuracy over a 100 kcal energy range. Numbers in parentheses refer to the HDMR basis set described in ref 1. |
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(1) Dawes R, Thompson D.L, Guo Y, Wagner A.F, Minkoff M.
Interpolating
moving
least-squares methods for fitting potential energy surfaces: Computing
high-density potential energy surface data from low-density ab initio data points. J. Chem. Phys. 126:184108
(2007)
(2) Dawes
R, Thompson D.L, Wagner A.F, Minkoff M.
Interpolating
moving
least-squares methods for fitting potential energy surfaces: A strategy
for efficient
optimal data point placement in high dimensions. (in prep).
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Donald L. Thompson's Theoretical Chemistry Group
