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Title: Interpolating moving least-squares methods for fitting potential energy surfaces : computing high-density potential energy surface data from low-density ab initio data points.

Journal Article · · J. Chem. Phys.
DOI:https://doi.org/10.1063/1.2730798· OSTI ID:915032

A highly accurate and efficient method for molecular global potential energy surface (PES) construction and fitting is demonstrated. An interpolating-moving-least-squares (IMLS)-based method is developed using low-density ab initio Hessian values to compute high-density PES parameters suitable for accurate and efficient PES representation. The method is automated and flexible so that a PES can be optimally generated for classical trajectories, spectroscopy, or other applications. Two important bottlenecks for fitting PESs are addressed. First, high accuracy is obtained using a minimal density of ab initio points, thus overcoming the bottleneck of ab initio point generation faced in applications of modified-Shepard-based methods. Second, high efficiency is also possible (suitable when a huge number of potential energy and gradient evaluations are required during a trajectory calculation). This overcomes the bottleneck in high-order IMLS-based methods, i.e., the high cost/accuracy ratio for potential energy evaluations. The result is a set of hybrid IMLS methods in which high-order IMLS is used with low-density ab initio Hessian data to compute a dense grid of points at which the energy, Hessian, or even high-order IMLS fitting parameters are stored. A series of hybrid methods is then possible as these data can be used for neural network fitting, modified-Shepard interpolation, or approximate IMLS. Results that are indicative of the accuracy, efficiency, and scalability are presented for one-dimensional model potentials as well as for three-dimensional (HCN) and six-dimensional (HOOH) molecular PESs

Research Organization:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
DE-AC02-06CH11357
OSTI ID:
915032
Report Number(s):
ANL/CHM/JA-59873; JCPSA6; TRN: US200817%%70
Journal Information:
J. Chem. Phys., Vol. 126, Issue May 11, 2007; ISSN 0021-9606
Country of Publication:
United States
Language:
ENGLISH