Computational Materials Science 2025 Q2
2025年度Q2 計算材料学特論 (資料: 英語＋日本語版)

Lecture materials for numerical analyses (by Kamiya)
数値解析に関する講義資料・pythonプログラム (神谷担当分)

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• Tutorial Videos (チュートリアルビデオ) [in Japanese]

  プレゼンテーションの技術
  論文やプレゼンテーションの英語
  生成AIの利用と注意
  生成AIの利用例: 一般的な質問と画像生成
  生成AIの利用例: 翻訳
  生成AIの利用例: プログラミング
  Excel VBA
  フィッティングと誤差
  薄膜トランジスタの原理と評価
  誘電物性
  バンド理論・量子計算
  機械学習・強化学習
• Python examples (pythonプログラム例) [in Japanese]
• Computational Material Science (数値解析) (Google NotebookLM Chatbot)
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• First-princples calculation (第一原理量子計算) (Google NotebookLM Chatbot)
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• Semiconductor and Device (半導体・デバイス) (Google NotebookLM Chatbot)
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• Generative AI and programming (生成AI・プログラミング) (Google NotebookLM Chatbot)
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Update News:

• July 3 11:33 Lecture materials on July 1 have been updated (20250701FFT_Matrix.zip)
  Fourier transformation (フーリエ変換), Matrix (行列), Applications (応用)
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• June 27, 20:05 Final version of lecture materials on June 27 have been updated (20250627EquationOptimize2.zip)
  Numerical solutions of equations (方程式の数値解法), Nonlinear optimization (非線形最適化)
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• June 20, 11:06 Final version of lecture materials on June 20 have been updated (20250620InterporlateSmoothing2.zip)
  Smoothing (平滑化), Linear least-squares method (線形最小二乗法), Numerical solutions of equations (方程式の数値解法)
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• June 17, 12:10 Final version of lecture materials on June 17 have been updated (20250617Diffeq2.zip)
  Differential equation (微分方程式), Molecular dynamics (分子動力学法), Interpolation (補間), Smoothing (平滑化)
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• June 13, 14:47 Final version of lecture materials on June 13 have been updateed (20250613DifferentialIntegration.zip)
  Numerical differentiation/integration (数値微分/積分)
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• June 10, 11:46 Final version of lecture materials on June 10 have been updated (20250610ComputerAndErorrSouorces.zip)
  Fundamentals of computer, Sources of errors (コンピュータの基礎、誤差)
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Getting Started with python (pythonプログラミングを始める前に)

　本講義では、pythonは必須ではありませんが、アルゴリズムの理解と今後の研究に役に立ちますので、余裕のある人は試してみてください。
  python is not a requirement for this class, but it will help your understanding about the algorisms to be learned and also assist your future research.

• python programming (Japanese)

#01 June 10, 2025: Fundamentals of computer (コンピュータの基礎), Sources of errors (誤差)

#02 June 13, 2025: Numerical differentiation (数値微分), Numerical integration(数値積分), Interpolation (補間), Smoothing (平滑化)

#03 June 17, 2025: Differential equation (微分方程式), Molecular dynamics (分子動力学法), Smoothing (平滑化)

#04 June 20, 2025: Smoothing (平滑化), Liner least-squres method (線形最小二乗法), Numerical solutions of equations (方程式の解法)

#05 June 27, 2024: Numerical solution of equation/Optimization (Nonlinear LSQ) (方程式の数値解法/最適化 (非線形最小二乗法）)

#06 July 1, 2025: Fourier transform (フーリエ変換), Matrix (行列), Applications (その他応用)