First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
Course unit
SCM0014413, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course First cycle degree in
SC1159, Degree course structure A.Y. 2008/09, A.Y. 2019/20
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Number of ECTS credits allocated 7.0
Type of assessment Mark
Course unit English denomination NUMERICAL ANALYSIS
Website of the academic structure
Department of reference Department of Mathematics
Mandatory attendance No
Language of instruction Italian
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge ALVISE SOMMARIVA MAT/08

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses MAT/08 Numerical Analysis 7.0

Course unit organization
Period Second semester
Year 3rd Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Practice 3.0 24 51.0 No turn
Laboratory 1.0 16 9.0 No turn
Lecture 3.0 24 51.0 No turn

Start of activities 02/03/2020
End of activities 12/06/2020
Show course schedule 2019/20 Reg.2008 course timetable

Examination board
Board From To Members of the board
8 Analisi Numerica - a.a. 2019/2020 01/10/2019 30/09/2020 SOMMARIVA ALVISE (Presidente)
VIANELLO MARCO (Membro Effettivo)
PUTTI MARIO (Supplente)

Prerequisites: Numerical Analysis
Target skills and knowledge: Advanced knowledge of Numerical Analysis and its applications in Applied Mathematics.
Examination methods: Written exam (theory) and oral exam (laboratory).
Assessment criteria: In the written examination we understand the theoretical knowledge obtained by the student, with particular attention to the comprehension of the algorithms, their properties, and proofs of major theorems.

In the part of lab, we evaluate how much the students have programming skills as well as understanding of the performed numerical experiments.
Course unit contents: Interpolation.
Orthogonal polynomials.
Numerical quadrature.
Iterative methods for linear algebra.
Finite differences methods for ODEs and PDEs.
Planned learning activities and teaching methods: Interpolation.
The general problem of interpolation, unisolvent sets and determinantal formula of Lagrange, the univariate and multivariate case, Lebesgue constant, fundamental estimate for interpolation error, stability, brief introduction to tensorial product interpolation and Fekete points.

Orthogonal polynomials.
Orthogonalization of the monomial basis, three-terms recurrence, the theorem of the zeros, classical orthogonal polynomials, Chebyshev polynomials.

Numerical quadrature.
Algebraic and composite rules, Gaussian rules, Polya-Steklov theorem, stability, Stieltjes theorem, brief introduction to product rules.

Numerical linear algebra.
Fundamental theorem of matrix inversion and applications (Gershgorin theorem of eigenvalues localization), iterative methods for linear systems, successive approximation theorem, preconditioning, gradient method, step and residual stop criteria, methods for the computation of eigenvalues and eigenvectors, Rayleigh quotient, power method and variants, QR method.

Numerical nonlinear algebra.
Solution of nonlinear systems of equations, fixed point iterations and Banach theorem, convergence estimates and stability, Newton method, local convergence and speed of convergence, step criterion, Newton method as fixed point iteration.

Finite difference methods for ODEs and PDEs.
Initial value problem: Euler method (explicit and implicit), convergence and stability in the Lipschitzian and dissipative case, trapezoidal method (Crank-Nicolson), stiff problems, conditional and unconditional stability; boundary problems: finite difference methods for the Poisson equations in 1D and 2D, structure of the linear system and convergence, computational issues; the lines method for the heat equation in the 1D and 2D case, relationships with the stiff problems.
Additional notes about suggested reading: Slides (as PDF files).
Textbooks (and optional supplementary readings)
  • Quarteroni, Alfio; Saleri, Fausto, Introduzione al Calcolo Scientifico. Springer Milan: --, 2006. Cerca nel catalogo
  • Epperson, James F., Introduzione all'analisi numericateoria, metodi, algoritmi. Milano [etc.]: McGraw-Hill, 2003. Cerca nel catalogo
  • Atkinson, Kendall E.; Han, Weimin, Elementary numerical analysis. New York: Wiley, 2004. Cerca nel catalogo

Innovative teaching methods: Software or applications used
  • One Note (digital ink)
  • Latex
  • Matlab
  • Slides and PDF of the lessons.

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