New preprint

Ab initio instanton rate theory made efficient using Gaussian process regression

by Jeremy Richardson

Ab initio instanton rate theory is a computational method for rigorously including tunnelling effects into calculations of chemical reaction rates based on a potential-energy surface computed on the fly from electronic-structure theory. This approach is necessary to extend conventional transition-state theory into the deep-tunnelling regime, but is also more computationally expensive as it requires many more ab initio calculations. We propose an approach which uses Gaussian process regression to fit the potential-energy surface locally around the dominant tunnelling pathway. The method can be converged to give the same result as from an on-the-fly ab initio instanton calculation but requires far fewer electronic-structure calculations. This makes it a practical approach for obtaining accurate rate constants based on high-level electronic-structure methods. We show fast convergence to reproduce benchmark H + CH4 results and evaluate new low-temperature rates of H + C2H6 in full dimensionality at a UCCSD(T)-F12b/cc-pVTZ-F12 level.

GPR-aided instanton
The only areas of the PES which need to be accurately known are the those around the instanton pathway or the reactant minimum (in order to obtain their partition functions).  In this image, they are represented by the coloured areas, whereas those that are not built into the GPR are unshaded.  The blue points represent the beads along the instanton path, while the black points represent the reactant and the transition state.   Note that the tunnelling pathway cuts the corner to explore a space far from the transition state.
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