Machine learning software to learn negligible elements of the Hamiltonian matrix-Reference-Cited by-同舟云学术

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Machine learning software to learn negligible elements of the Hamiltonian matrix

Published:2023-12 Issue:2 Volume:1 Page:100025
ISSN:2949-7477
Container-title:Artificial Intelligence Chemistry
language:en
Short-container-title:Artificial Intelligence Chemistry

Author:

Qu Chen,Houston Paul L.,Yu Qi,Pandey Priyanka,Conte Riccardo,Nandi Apurba,Bowman Joel M.

Funder

National Aeronautics and Space Administration

Università degli Studi di Milano

Publisher

Elsevier BV

Reference21 articles.

1. Machine learning classification can significantly reduce the cost of calculating the hamiltonian matrix in CI calculations;Qu;J. Chem. Phys.,2023

2. Investigations of self-consistent field, SCF CI and virtual state configuration interaction vibrational energies for a model three-mode system;Christoffel;Chem. Phys. Lett.,1982

3. MULTIMODE: acode to calculate rovibrational energies of polyatomic molecules;Bowman;Int. Rev. Phys. Chem.,2003

4. Extensions and tests of “multimode”: a code to obtain accurate vibration/rotation energies of many-mode molecules;Carter;Theor. Chem. Acc.,1998

5. Variational quantum approaches for computing vibrational energies of polyatomic molecules;Bowman;Mol. Phys.,2008

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. BUILDING LIFE CYCLE MANAGEMENT AT THE OPERATION STAGE USING ARTIFICIAL NEURAL NETWORK MODELS AND MACHINE LEARNING;Bulletin of Belgorod State Technological University named after. V. G. Shukhov;2024-01-31

2. A New A Priori Method to Avoid Calculation of Negligible Hamiltonian Matrix Elements in CI Calculation;The Journal of Physical Chemistry A;2024-01-05

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