Inverting the Kohn-Sham equations with physics-informed machine learning
Inverting the Kohn-Sham equations with physics-informed machine learning
Martinetto, V.; Shah, K.; Cangi, A.; Pribram-Jones, A.
This data repository contains the datasets used in the paper "Inverting the Kohn-Sham equations with physics-informed machine learning".
It contains the data generation scripts, datasets for the systems used in the paper (Single Well - 1D atom, Double Well - 1D diatomic molecule) and output potentials generated by the physics-informed machine learning models (physics-informed neural networks and Fourier neural operators).
Keywords: density functional theory; machine learning
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Related publications
- DOI: 10.48550/arXiv.2312.15301 is supplemented by this (Id 38725) publication
- DOI: 10.1088/2632-2153/ad3159 references this (Id 38725) publication
- DOI: 10.48550/arXiv.2312.15301 references this (Id 38725) publication
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Inverting the Kohn-Sham equations with physics-informed machine learning
ROBIS: 38360 has used this (Id 38725) publication of HZDR-primary research data
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Reseach data in the HZDR data repository RODARE
Publication date: 2024-02-01 Open access
DOI: 10.14278/rodare.2719
Versions: 10.14278/rodare.2720
License: CC-BY-4.0
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Permalink: https://www.hzdr.de/publications/Publ-38725
