Computational Materials Science 2026 Q2
2026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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detailed history

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FY2026

#07 July 3, 2026 (the last day of numerical analysis): Answers to requests (リクエストへの回答), Matrix (行列), Applicagions (応用),

Course materials (Lecture slides and python programs):

5-8min audio guide:

#06 June 30, 2026: Nonlinear optimization (非線形最適化), Fourier transform (フーリエ変換), Matrix (行列), Applications (応用)

Course materials (Lecture slides and python programs):

5-8min audio guide:

#05 June 26, 2026: Solution of equations (方程式の解法), Nonlinear optimization (非線形最適化)

Course materials (Lecture slides and python programs):

5-8min audio guide:

#04 June 23, 2026: Smoothing (平滑化), Linear least-squares method (線形最小二乗法), Solusion of equation (方程式の解法)

Course materials (Lecture slides and python programs):

5-8min audio guide:

#03 June 19, 2026: Differential equation (微分方程式), Interpolation (補間), Smoothing (平滑化)

Course materials (Lecture slides and python programs):

5-8min audio guide:

#02 June 16, 2026: Numerical differentiation (数値微分), Numerical integration(数値積分), Differential equation (微分方程式)

Course materials (Lecture slides and python programs):

5-8min audio guide:

#01 June 12, 2026: Fundamentals of computer (コンピュータの基礎), Sources of error (誤差), Numerical differentiation (数値微分)

Course materials (Lecture slides and python programs):

5-8min audio guide:


python programs (everything in the course_materials.zip)

Fundamentals of computer

Sources of error

Differentiation

Numerical integration

Differential equation

Second-order differential equation

Simultaneous second-order differential equations

Interpolation

Smoothing


Linear least squares method

Numerical solution of equations

Nonlinear optimization

Fourier transorm

Matrix

Applications

資料: Crystal.pdf