Artificial Neural Networks as Mappings between Proton Potentials, Wave Functions, Densities, and Energy Levels.

ABSTRACT: Artificial neural networks (ANNs) have become important in quantum chemistry. Herein, applications to nuclear quantum effects, such as zero-point energy, vibrationally excited states, and hydrogen tunneling, are explored. ANNs are used to solve the time-independent Schrödinger equation for single- and double-well potentials representing hydrogen-bonded molecular systems capable of proton transfer. ANN mappings are trained to predict the lowest five proton vibrational energies, wave functions, and densities from the proton potentials and to predict the excited state proton vibrational energies and densities from the proton ground state density. For the inverse problem, ANN mappings are trained to predict the proton potential from the proton vibrational energy levels or the proton ground sta

SUBMITTER: Secor M 

PROVIDER: S-EPMC8021271 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature