Improvement of Fourteen Coupled Global Potential Energy Surfaces of 3A′ States of O + O2

We improved the potential energy surfaces for fourteen coupled 3A′ states of O3 by using parametrically managed diabatization by deep neural network (PM-DDNN) with three improvements: (1) We use a new functional form for the parametrically managed activation function, which ensures the continuity of the coordinates used in the parametric management. (2) We used higher weighting for low-lying states to achieve smoother potential energy surfaces. (3) The asymptotic behavior of the coupled potential energy surfaces was further refined by utilizing a better low-dimensional potential. As a result of these improvements, we obtained significantly smoother potentials that are better suited for dynamics calculations. For the new version of 14 coupled 3A′ surfaces, the entire set of 532,560 adiabatic energies are fit with a mean unsigned error (MUE) of 45 meV, which is only 0.7% of the mean energy in the data set, which is 6.24 eV.