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Common workflows for computing material properties using different quantum engines

Abstract

The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use them. We demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and cross-verification. We introduce design rules for reusable, code-agnostic, workflow interfaces to compute well-defined material properties, which we implement for eleven quantum engines and use to compute various material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer’s expertise of the quantum engine directly available to non-experts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.
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Category

Academic article

Language

English

Author(s)

  • Sebastiaan P. Huber
  • Emanuele Bosoni
  • Marnik Bercx
  • Jens Bröder
  • Augustin Degomme
  • Vladimir Dikan
  • Kristjan Eimre
  • Espen Flage-Larsen
  • Alberto Garcia
  • Luigi Genovese
  • Dominik Gresch
  • Conrad Johnston
  • Guido Petretto
  • Samuel Poncé
  • Gian-Marco Rignanese
  • Christopher J. Sewell
  • Berend Smit
  • Vasily Tseplyaev
  • Martin Uhrin
  • Daniel Wortmann
  • Aliaksandr V. Yakutovich
  • Austin Zadoks
  • Pezhman Zarabadi-Poor
  • Bonan Zhu
  • Nicola Marzari
  • Giovanni Pizzi

Affiliation

  • SINTEF Industry / Sustainable Energy Technology
  • Université catholique de Louvain
  • Université Grenoble Alpes
  • Institute of Materials Science of Barcelona
  • United Kingdom
  • The Queen's University of Belfast
  • University College London
  • University of Bath
  • Switzerland
  • Swiss Federal Institute of Technology of Lausanne
  • RWTH Aachen University
  • Research Centre Jülich
  • University of Oslo
  • University of California

Year

2021

Published in

npj Computational Materials

Volume

7

Issue

1

View this publication at Norwegian Research Information Repository