Inverting the Kohn-Sham equations with physics-informed machine learning

DOI

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).

Identifier
DOI https://doi.org/10.14278/rodare.2720
Related Identifier https://doi.org/10.48550/arXiv.2312.15301
Related Identifier https://www.hzdr.de/publications/Publ-38725
Related Identifier https://doi.org/10.14278/rodare.2719
Related Identifier https://rodare.hzdr.de/communities/casus
Related Identifier https://rodare.hzdr.de/communities/matter
Related Identifier https://rodare.hzdr.de/communities/rodare
Metadata Access https://rodare.hzdr.de/oai2d?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:rodare.hzdr.de:2720
Provenance
Creator Martinetto, Vincent ORCID logo; Shah, Karan ORCID logo; Cangi, Attila (ORCID: 0000-0001-9162-262X); Pribram-Jones, Aurora ORCID logo
Publisher Rodare
Publication Year 2024
Rights Creative Commons Attribution 4.0 International; Open Access; https://creativecommons.org/licenses/by/4.0/legalcode; info:eu-repo/semantics/openAccess
OpenAccess true
Contact https://rodare.hzdr.de/support
Representation
Resource Type Dataset
Discipline Life Sciences; Natural Sciences; Engineering Sciences