PIPFit 2022

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PIPFit 2022

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Truhlar, Donald G


Software, including Manual


The PIPFit 2022 program can be used to develop analytic representations of potential energy surfaces for three-body and four-body systems. A weighted least-squares fit is performed with permutationally invariant polynomials (PIPs) whose variables are Morse-like bond functions, Gaussians, mixed exponential–Gaussians (MEGs), or hyperbolic secant variables. Three kinds of fit can be performed with the program:
*PIPs fit to the whole potential, as originally proposed by Braams, Bowman, and Xie,
*connected PIPs fit to the whole potential after removing the unconnected terms,
*connected PIPs fit to the many-body part of the potential after removing the unconnected terms and the two-body terms.
The program can also perform a two-stage fit in which one first fits lower-level energetic data with a large number of geometries and then fits higher-level corrections with a smaller set of geometries.


Referenced by

Y. Paukku, K. R. Yang, Z. Varga, and D. G. Truhlar J. Chem. Phys. 139, 044309 (2013).
J. D. Bender, P. Valentini, I. Nompelis, Y. Paukku, Z. Varga, D. G. Truhlar, T. Schwartzentruber, G. V. Candler, J. Chem. Phys. 143, 054304 (2015).
Y. Shu, J. Kryven, A. G. S. de Oliveira-Filho, L. Zhao, G.-L. Song, S. L. Li, R. Meana-Pañeda, B. Fu, J. M. Bowman, and D. G. Truhlar, J. Chem. Phys. 151, 104311 (2019).

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Funding information

U. S. Air Force Office of Scientific Research under Grant Nos. FA9550-10-1-0563, FA9550-16-1-0161, and FA9550-19-1-0219
U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award No. DE-SC0015997




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Suggested citation

Yang, Ke R; Varga, Zoltan; Parker, Kelsey A; Shu, Yinan; Truhlar, Donald G. (2022). PIPFit 2022. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/tnzc-nt34.
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PIPFit2022.tar.gzSource code, tests, and manual7.99 MB
220213_PIPFit_2022_Manual.pdfManual, CC-BY-4.0733.66 KB

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