To provide the students with the basics of numerical analysis and scientific computer programming
teacher profile teaching materials
Setup of the computational environment.
Assessment of the computational environment: coding, compilation, execution, i/o, post–processing.
Linear algebra problems: matrix multiplication, linear systems.
Coding practices for performance: cache–miss minimization.
Use of external libraries. Eigenproblems.
Polynomial interpolation.
Integration of ODE: explicit/implicit methods, Liapunov stability.
Numerical integration: Newton–Cotes quadratures, Gaussian quadratures.
Systems of non–linear differential equations.
Oscillators, chaotic systems, Lorenz attractor.
Programme
Tools, software and textbooks.Setup of the computational environment.
Assessment of the computational environment: coding, compilation, execution, i/o, post–processing.
Linear algebra problems: matrix multiplication, linear systems.
Coding practices for performance: cache–miss minimization.
Use of external libraries. Eigenproblems.
Polynomial interpolation.
Integration of ODE: explicit/implicit methods, Liapunov stability.
Numerical integration: Newton–Cotes quadratures, Gaussian quadratures.
Systems of non–linear differential equations.
Oscillators, chaotic systems, Lorenz attractor.
Core Documentation
Lecture notesReference Bibliography
1) Quarteroni, Saleri, Gervasio, Calcolo Scientifico: Esercizi e problemi risolti con MATLAB e Octave. 2) Quarteroni, Sacco, Saleri, Gervasio, Matematica numerica.Attendance
optionalType of evaluation
Final project with preparation of a technical report