Transfer learning for affordable and high quality tunneling splittings from instanton calculations

2022/08/02 by Käser, Silvan, Richardson, Jeremy O., Meuwly, Markus · 6 citations
#Chemical Physics (physics.chem-ph) #FOS: Physical sciences

paper · doi:10.48550/arxiv.2208.01315

Abstract

The combination of transfer learning (TL) a low level potential energy surface (PES) to a higher level of electronic structure theory together with ring-polymer instanton (RPI) theory is explored and applied to malonaldehyde. The RPI approach provides a semiclassical approximation of the tunneling splitting and depends sensitively on the accuracy of the PES. With second order Møller-Plesset perturbation theory (MP2) as the low-level (LL) model and energies and forces from coupled cluster singles, doubles and perturbative triples (CCSD(T)) as the high-level (HL) model, it is demonstrated that CCSD(T) information from only 25 to 50 judiciously selected structures along and around the instanton path suffice to reach HL-accuracy for the tunneling splitting. In addition, the global quality of the HL-PES is demonstrated through a mean average error of 0.3 kcal/mol for energies up to 40 kcal/mol above the minimum energy structure (a factor of 2 higher than the energies employed during TL) and < 2 cm^-1 for harmonic frequencies compared with computationally challenging normal mode calculations at the CCSD(T) level.

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