# Python suites for high-throughput calculations of the ab-initio quantum Monte Carlo methods

https://mdr.nims.go.jp/datasets/78421622-9694-4d50-a467-58dd1297c08c

## File

- [trexio_files_to_public_repo.zip](https://mdr.nims.go.jp/filesets/d505fd63-a06e-42be-84d4-1b7303d73892/download) ([Detail](https://mdr.nims.go.jp/filesets/d505fd63-a06e-42be-84d4-1b7303d73892.md))
- [README.md](https://mdr.nims.go.jp/filesets/ef3bff86-887d-4436-be65-b34fd5f1e03c/download) ([Detail](https://mdr.nims.go.jp/filesets/ef3bff86-887d-4436-be65-b34fd5f1e03c.md))

## Id

78421622-9694-4d50-a467-58dd1297c08c

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2023-09-20T03:34:56.121239Z

## Updated at

2023-11-15T06:38:36.236164Z

## Published at

2023-11-16T04:30:12.194765Z

## Doi

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

## First published url



## Date published



## Recorded date published



## Resource type

dataset

## Manuscript type

na

## Collection



## Title

- title: Python suites for high-throughput calculations of the ab-initio quantum Monte
    Carlo methods
  title_type: original
  lang: en

## Description

- description: '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].'
  description_type: abstract
  lang: eng

## Creator

- name: NAKANO, Kosuke
  role: author
  orcid: https://orcid.org/0000-0001-7756-4355
  organization: National Institute for Materials Science (NIMS)
  department: Center for Basic Research on Materials
  ror: https://ror.org/026v1ze26
- name: Oto Kohulák
  role: author
  organization: International School for Advanced Studies (SISSA)
- name: Abhishek Raghav
  role: author
  organization: International School for Advanced Studies (SISSA)
- name: Michele Casula
  role: author
  organization: Sorbonne Université
  department: Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie
    (IMPMC)
- name: Sandro Sorella
  role: author
  organization: International School for Advanced Studies (SISSA)

## Contact agent



## Publisher

organization: National Institute for Materials Science
ror: https://ror.org/026v1ze26

## Managing organization



## Keyword

- subject: Ab initio Quantum Monte Carlo
  schema: not_defined
- subject: High-throughput calculations
  schema: not_defined
- subject: TurboRVB
  schema: not_defined
- subject: TurboGenius
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: simulation

## Embargo



## Journal



## Conference



## Related item



## Funding

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

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software

- name: TREXIO
  version: TREXIO version 2.3.2 (and the corresponding Python API version 1.3.2)
  description: 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).

## Custom property



## Fileset

- id: d505fd63-a06e-42be-84d4-1b7303d73892
  filename: trexio_files_to_public_repo.zip
  content_type: application/zip
  size: 1428664723
  md5: 6c074c68f5e10814b82d54505ac2bb8e
- id: ef3bff86-887d-4436-be65-b34fd5f1e03c
  filename: README.md
  content_type: text/markdown
  size: 447
  md5: b696968d2da697cadd0c27d0d81d6ddc

## Thumbnail

fileset_id: ef3bff86-887d-4436-be65-b34fd5f1e03c
filename: README.md