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Updated: Feb 14, 2026

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機械学習を初期計算とワークフローに実践的に統合する: 密度行列の予測を通じてSCFサイクルを加速する

Pavel Stishenko1, Chen Qian2, Julia Westermayr3,4

  • 1Cardiff Catalysis Institute, School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, United Kingdom.

The Journal of chemical physics
|February 13, 2026
PubMed
まとめ

電子構造機械学習 (ESML) モデルを組み合わせることで,初期計算を加速することができます. この"縫合"方法は,分子および材料シミュレーションの計算効率を改善します.

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