Adapting hybrid density functionals with machine learning

Danish Khan, Alastair James Arthur Price, Bing Huang, Maximilian L. Ach,, O. Anatole von Lilienfeld

Keywords: daptive hybrid functionals, exact exchange admixture, quantum machine learning, density functional theory, on-the-fly optimization, electronic structure calculations, data-efficient models, computational chemistry, machine learning in quantum mechanics, exchange-correlation functionals.

TL;DR: Adaptive hybrid functionals use machine learning to optimize exact exchange admixture, improving density functional theory accuracy.

Confirmation Of Submission Requirements: I submit a previously published paper. It was published in an archival peer–reviewed venue on or after September 8th 2024, I specify the DOI in the field below, and I submit the camera-ready version of the paper.

DOI: https://doi.org/10.1126/sciadv.adt7769

Submission Number: 89