Publication date: Dec 23, 2020
The article presents a series of methods that boost the speed of Wannier interpolation by several orders of magnitude, as well as their implementation in the WannierBerri code. The present dataset contains input files, scripts, and the resulting data, which allow to reproduce the examples and figures published in the article. The current version of the code is also included.
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File name | Size | Description |
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wannierberri.tar.gz
MD5md5:aa51d395e6def180567ebc4963c16b04
|
64.8 KiB | the current version of the code v0.7.6 ( 16.12.2020 ) |
run_calc.py
MD5md5:629ac69172eaf96b6d20dadfa62f8c02
|
4.5 KiB | a Python script to run the calculations |
input.tar.gz
MD5md5:5c2ddff8701f6d576d70220564061487
|
99.4 KiB | the input files' templates for the calculations |
results.tar.gz
MD5md5:1a0896c1ded93bb57a5d27069d5fb1c0
|
86.2 MiB | the results of calculations |
reference.tar.gz
MD5md5:3b4254f35b3ef4d34828265b7c20c1b9
|
215.2 MiB | the intermediate files for a reference, or to start a calculation skipping the PWSCF calculations |
kmesh.pl
MD5md5:900131388110c29edcf9c35e800e6d89
|
1.2 KiB | generator of kpoint lists - copied from Wannier90 |
2020.171 (version v1) [This version] | Dec 23, 2020 | DOI10.24435/materialscloud:1r-8w |