Preconditioners for the geometry optimisation and saddle point search of molecular systems

TL;DR

This paper introduces a new class of preconditioners that improve the efficiency of geometry optimization and saddle point search in molecular systems by leveraging the Hessian of molecular mechanical terms, applicable to various potential energy surfaces.

Contribution

The paper presents a novel sparse preconditioner derived from the Hessian's positive definite part, compatible with existing force field software and adaptable to periodic systems.

Findings

Enhanced optimization efficiency demonstrated on multiple systems

Applicable to empirical, semiempirical, and ab initio potentials

Compatible with existing force field software and periodic system preconditioners

Abstract

A class of preconditioners is introduced to enhance geometry optimisation and transition state search of molecular systems. We start from the Hessian of molecular mechanical terms, decompose it and retain only its positive definite part to construct a sparse preconditioner matrix. The construction requires only the computation of the gradient of the corresponding molecular mechanical terms that are already available in popular force field software packages. For molecular crystals, the preconditioner can be combined straightforwardly with the exponential preconditioner recently introduced for periodic systems. The efficiency is demonstrated on several systems using empirical, semiempirical and ab initio potential energy surfaces.