Common workflows for computing material properties using different quantum engines
(2021) npj Computational Materials — Vol. 7, n° 136, p. 12 (2021)
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- Authors
Huber, Sebastiaan P. 
Bosoni, Emanuele Bröder, Jens Petretto, Guido Pizzi, Giovanni
- 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 nonexperts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.
- Affiliations
Citations
Huber, S. P., Bosoni, E., Bercx, M., Bröder, J., Degomme, A., Dikan, V., Eimre, K., Flage-Larsen, E., Garcia, A., Genovese, L., Gresch, D., Johnston, C., Petretto, G., Poncé, S., Rignanese, G.-M., Sewell, C. J., Smit, B., Tseplyaev, V., Uhrin, M., et al. (2021). Common workflows for computing material properties using different quantum engines. npj Computational Materials, 7(136), 12. https://doi.org/10.1038/s41524-021-00594-6 (Original work published 2021)