コメントへの返信 "分数電子問題を解くことで密度関数の限界を押し広げること"
James Kirkpatrick1, Brendan McMorrow1, David H P Turban1
1DeepMind, 6 Pancras Square, London N1C 4AG, UK.
Science (New York, N.Y.)
|August 4, 2022
まとめ
この研究は,DM21モデルに関する主張を扱っています.
科学分野:
- コンピュータ化学
- 量子力学
- 科学における機械学習
背景:
- DM21モデルは,その訓練データを超えて一般化することが,その適用性にとって極めて重要です.
- ゲラシモフ ほか DM21の分量電荷 (FC) と分量スピン (FS) の能力に関する我々の以前の研究の実証を疑問視した.
- 彼らの批判は,トレーニングセットとベンチマークデータセットの重なり合い,そして一般的な例の妥当性に焦点を当てた.
研究 の 目的:
- ゲラシモフの主張を否定する DM21モデルの汎用性について
- ベンチマーク結果と一般化例の正確性と関連性を明確にする.
- DM21モデルの全体的な品質と予測力を再確認する.
主な方法:
- 訓練セットの再評価は,バンドブレッキング・ベンチマーク (BBB) と重複する.
- 論文に示された一般化の例の詳細な分析.
- ゲラシモフらによって提起された特定の点を直接反論する.
主要な成果:
- 訓練セットとBBBの間で主張された~50%の重複は不正確です.
- 一般化例は,トレーニングセットの外でのDM21の堅実なパフォーマンスを示しています.
- ゲラシモフらによる批判 欠陥のある前提に基づいていて 根本的な発見とは無関係です
結論:
- ゲラシモフらによる主張 証明されたFC/FS一般化の欠如については,根拠がありません.
- 私たちの論文はDM21の 汎用性に関する 有効な証拠を提示しています
- DM21モデルは,量子化学計算の高品質と予測精度を維持しています.
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