Dataset Open Access
Inverting the Kohn-Sham equations with physics-informed machine learning
Martinetto, Vincent;
Shah, Karan;
Cangi, Attila;
Pribram-Jones, Aurora
Citation Style Language JSON Export
{
"DOI": "10.14278/rodare.2720",
"id": "2720",
"publisher": "Rodare",
"issued": {
"date-parts": [
[
2024,
2,
1
]
]
},
"author": [
{
"family": "Martinetto, Vincent"
},
{
"family": "Shah, Karan"
},
{
"family": "Cangi, Attila"
},
{
"family": "Pribram-Jones, Aurora"
}
],
"type": "dataset",
"title": "Inverting the Kohn-Sham equations with physics-informed machine learning",
"abstract": "<p>This data repository contains the datasets used in the paper "Inverting the Kohn-Sham equations with physics-informed machine learning". </p>\n\n<p>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).</p>"
}
512
53
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 512 | 512 |
| Downloads | 53 | 53 |
| Data volume | 8.2 GB | 8.2 GB |
| Unique views | 454 | 454 |
| Unique downloads | 49 | 49 |
- Publication date:
- February 1, 2024
- DOI:
-
- Keyword(s):
- density functional theory machine learning
- Related identifiers:
- Identical to:
https://www.hzdr.de/publications/Publ-38725 - Supplement to:
10.48550/arXiv.2312.15301 - Communities:
- License (for files):
- Creative Commons Attribution 4.0 International