Permutationally invariant polynomial representation of polarizability tensor surfaces for linear regression analysis
Author:
Affiliation:
1. Department of Chemistry & Biochemistry Kennesaw State University Kennesaw Georgia USA
2. Cherry L. Emerson Center for Scientific Computation and Department of Chemistry Emory University Atlanta Georgia USA
Funder
National Science Foundation
Publisher
Wiley
Subject
Computational Mathematics,General Chemistry
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.26952
Reference36 articles.
1. Ab initiodipole polarizability surfaces of water molecule: Static and dynamic at 514.5nm
2. Infrared and Raman Spectroscopy of Liquid Water through “First-Principles” Many-Body Molecular Dynamics
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5. Efficient and Accurate Simulations of Vibrational and Electronic Spectra with Symmetry-Preserving Neural Network Models for Tensorial Properties
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1. Fitting Potential Energy Surfaces by Learning the Charge Density Matrix with Permutationally Invariant Polynomials;Journal of Chemical Theory and Computation;2023-08-10
2. Revisiting theN(N + 1)/2‐sites‐type Gaussian charge model for permutationally invariant polynomial fitting of global molecular tensor surfaces;International Journal of Quantum Chemistry;2023-02-23
3. Accurate and Interpretable Dipole Interaction Model-Based Machine Learning for Molecular Polarizability;Journal of Chemical Theory and Computation;2023-02-08
4. A Fermi resonance and a parallel-proton-transfer overtone in the Raman spectrum of linear centrosymmetric N4H+: A polarizability-driven first principles molecular dynamics study;The Journal of Chemical Physics;2022-10-21
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