# Molecular geometry and vibrational frequencies by parallel sampling

## TL;DR

This paper introduces a simple quantum Monte Carlo-based method that adaptively varies the trial function to accurately determine molecular geometries and vibrational frequencies, overcoming singularities of traditional fixed-trial approaches.

## Contribution

It presents a novel technique that improves the accuracy of molecular geometry and vibrational frequency calculations by dynamically adjusting the trial function in quantum Monte Carlo simulations.

## Key findings

- Enhanced accuracy in geometry and vibrational frequency estimation.
- Reduction of singularities in quantum Monte Carlo calculations.
- Applicable to small molecules for improved quantum property determination.

## Abstract

Quantum Monte Carlo is an efficient technique for finding the ground-state energy and related properties of small molecules. A major challenge remains in accurate determination of a molecule's geometry, i.e. the optimal location of its individual nuclei and the frequencies of their vibration. The aim of this article is to describe a simple technique to accurately establish such properties. This is achieved by varying the trial function to accommodate changing geometry, thereby removing a source of rather unpleasant singularities which arise when the trial function is fixed (the traditional approach).