← カタログに戻る

abICS Gallery

abics-dev / abICS Gallery

電子状態計算(固体物理)機械学習Documents: CC BY 4.0, Codes: GNU General Public License v3.0 or later
更新: 2022-07-27

概要

abICS is a software framework for training a machine learning model to reproduce first-principles energies and then using the model to perform configurational sampling in disordered systems. Specific emphasis is placed on multi-component solid state systems such as metal and oxide alloys. The current version of abics can use neural network models implemented in aenet to be used as the machine learning model. As of this moment, abICS can also generate Quantum Espresso, VASP, and OpenMX input files for obtaining the reference training data for the machine learning model. This repository provides the sample data including input and output data for abICS.

URL
https://isspns-gitlab.issp.u-tokyo.ac.jp/abics-dev/abics-gallery
著者
Shusuke Kasamatsu, Kazuyoshi Yoshimi, Yuichi Motoyama
ライセンス
Documents: CC BY 4.0, Codes: GNU General Public License v3.0 or later
カテゴリ
電子状態計算(固体物理), 機械学習
関連ソフトウェア
abICS (リンク先: PASUMS ソフトウェアカタログ)
連絡先
abICS-dev__at__issp.u-tokyo.ac.jp (__at__ を @ に置き換えてください。)

リンク

README

About

abICS is a software framework for training a machine learning model to reproduce first-principles energies and then using the model to perform configurational sampling in disordered systems. Specific emphasis is placed on multi-component solid state systems such as metal and oxide alloys. The current version of abICS can use neural network models implemented in aenet to be used as the machine learning model. As of this moment, abICS can also generate Quantum Espresso, VASP, and OpenMX input files for obtaining the reference training data for the machine learning model.

License
  • Documents and data: CC BY 4.0
  • Source code: GNU General Public License v3.0 or later
Contact
  • abICS-dev__at__issp.u-tokyo.ac.jp

please replace __at__ by @.

出典: https://isspns-gitlab.issp.u-tokyo.ac.jp/abics-dev/abics-gallery の README

更新状況

更新最終更新: 2022-07-27 ()