Evolutionary optimization of PAW data-sets for accurate high pressure simulations

TL;DR

This paper presents an evolutionary algorithm to optimize PAW data-sets for high-pressure electronic structure calculations, aiming for accuracy and transferability across a wide pressure range.

Contribution

It introduces an automated, evolutionary approach to generate transferable PAW data-sets that closely match all-electron calculations over high-pressure conditions.

Findings

Optimized PAW data-sets improve accuracy at high pressures.

New measure of data-set quality based on performance uniformity.

Demonstrated on elements common in planetary interiors.

Abstract

We examine the challenge of performing accurate electronic structure calculations at high pressures by comparing the results of all-electron full potential linearized augmented-plane-wave calculations with those of the projector augmented wave (PAW) method. In particular, we focus on developing an automated and consistent way of generating transferable PAW data-sets that can closely produce the all electron equation of state defined from zero to arbitrary high pressures. The technique we propose is an evolutionary search procedure that exploits the ATOMPAW code to generate atomic data-sets and the Quantum ESPRESSO software suite for total energy calculations. We demonstrate different aspects of its workability by optimizing PAW basis functions of some elements relatively abundant in planetary interiors. In addition, we introduce a new measure of atomic data-set goodness by considering their performance uniformity over an enlarged pressure range.