Dataset Python suites for high-throughput calculations of the ab-initio quantum Monte Carlo methods
NAKANO, Kosuke (author) (Search by this author)
ORCID https://orcid.org/0000-0001-7756-4355
Center for Basic Research on Materials, National Institute for Materials Science (NIMS)
SAMURAI NIMS Researchers Directory SAMURAI
ORCID SAMURAI ;
Oto Kohulák (author) (Search by this author)
International School for Advanced Studies (SISSA)
;
Abhishek Raghav (author) (Search by this author)
International School for Advanced Studies (SISSA)
;
Michele Casula (author) (Search by this author)
Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie (IMPMC), Sorbonne Université
;
Sandro Sorella (author) (Search by this author)
International School for Advanced Studies (SISSA)
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Citation
NAKANO, Kosuke, Oto Kohulák, Abhishek Raghav, Michele Casula, Sandro Sorella. Python suites for high-throughput calculations of the ab-initio quantum Monte Carlo methods. https://doi.org/10.48505/nims.4231
SAMURAI

Description:

(abstract)

The TREXIO files used for the validation tests in the paper entitled TurboGenius: Python suite for high-throughput calculations of ab initio quantum Monte Carlo methods. The detail about the TREXIO library is described in the JCP article [J. Chem. Phys. 158, 174801 (2023)] and the GitHub repository [https://github.com/TREX-CoE/trexio].

Data origin type: simulation

Rights:

Keyword: Ab initio Quantum Monte Carlo, High-throughput calculations, TurboRVB, TurboGenius

Date published:

Publisher: National Institute for Materials Science ROR

Journal:

Funding:

  • RIKEN HPCI System Research Projects (hp200164, hp210038, hp220060, and hp230030) (Computational resources of the supercomputer Fugaku.)
  • Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Early Career Scientists (Grant No. JP21K17752)
  • Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Scientific Re- search (Grant No. JP21K03400)
  • Japan Society for the Promotion of Science (JSPS) MEXT Leading Initiative for Excellent Young Researchers (Grant No. JPMXS0320220025)
  • Japan Society for the Promotion of Science (JSPS) SPS Overseas Research Fellowship

Manuscript type: Not a journal article

MDR DOI: https://doi.org/10.48505/nims.4231

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Updated at: 2023-11-15 15:38:36 +0900

Published on MDR: 2023-11-16 13:30:12 +0900

Software / ソフトウェア

Name / 名称 : TREXIO

Version / バージョン : TREXIO version 2.3.2 (and the corresponding Python API version 1.3.2)

Description / 説明 : The detail about the TREXIO library is described in the JCP article [J. Chem. Phys. 158, 174801 (2023)] and the GitHub repository [https://github.com/TREX-CoE/trexio]. The TREXIO files were generated using TREXIO version 2.3.2 (and the corresponding Python API version 1.3.2).

Identifier / ソフトウェアID :

Filename Size
Filename trexio_files_to_public_repo.zip
application/zip
Size 1.33 GB Detail
Filename README.md (Thumbnail)
text/markdown
Size 447 Bytes Detail