# Semiclassical vibrational spectroscopy with Hessian databases

## TL;DR

This paper introduces a Hessian database approach to significantly reduce computational costs in semiclassical vibrational spectroscopy simulations, enabling studies of larger molecules with maintained accuracy.

## Contribution

The paper presents a novel Hessian database method that accelerates semiclassical vibrational spectroscopy calculations for large systems without sacrificing accuracy.

## Key findings

- Successfully applied to methane, glycine, and a 46-atom biological molecule.
- Achieved computational speed-up while maintaining spectral accuracy.
- Enabled vibrational spectral analysis of larger, more complex molecules.

## Abstract

We report on a new approach to ease the computational overhead of ab initio on-the-fly semiclassical dynamics simulations for vibrational spectroscopy. The well known bottleneck of such computations lies in the necessity to estimate the Hessian matrix for propagating the semiclassical pre-exponential factor at each step along the dynamics. The procedure proposed here is based on the creation of a dynamical database of Hessians and associated molecular geometries able to speed up calculations while preserving the accuracy of results at a satisfactory level. This new approach can be interfaced to both analytical potential energy surfaces and on-the-fly dynamics, allowing one to study even large systems previously not achievable. We present results obtained for semiclassical vibrational power spectra of methane, glycine, and N-acetyl-L-phenylalaninyl-L-methionine-amide, a molecule of biological interest made of 46 atoms.