Accelerating Instanton Theory with the Line Integral Nudged Elastic Band Method and Gaussian Process Regression

15 April 2025, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Quantum tunneling plays a fundamental role in many chemical reactions, particularly proton transfer processes. Ring polymer instanton theory offers a practical framework for computing tunneling rates in complex molecular systems. However, applying the ring polymer instanton method with a potential energy surface generated on-the-fly using electronic structure calculations can be computationally demanding. In this work, we present a new efficient implementation of the ring polymer instanton method by combining the Line Integral Nudged Elastic Band (LI-NEB) approach with Gaussian Process Regression (GPR). We benchmarked this method on prototypical ground-state proton transfer systems, including the benchmark gas-phase hydrogen abstraction reaction H + CH$_{4}$ → H$_2$ + CH$_{3}$, malonaldehyde, and Z-3-amino-propenal (aminopropenal). Our results show that this approach is an order of magnitude faster than traditional instanton algorithms while maintaining excellent agreement with their tunneling rates. This development opens the door to studying proton transfer in larger systems and excited-state intramolecular proton transfer (ESIPT) reactions with improved efficiency.

Keywords

ring polymer instanton
machine learning
nuclear quantum effect

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Supplementary Information: Accelerating Instanton Theory with Line Integral Nudged Elastic Band Method and Gaussian Process Regression
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Supplementary Information pdf document.
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