Numerical Analysis 2
A.Y. 2020/2021
Learning objectives
Presentation of the most common methods for the numerical solution of ordinary differential equations and introduction in their error analysis.
Expected learning outcomes
The ability to assess, implement, and interpret the results of numerical methods for initial value problems.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Assessment methods and critera for its result
The assessment methods and critera for its results will not been changed, except for the fact that the final oral exam will be in person or on Microsoft Teams according to the existing directives in force at the time of the exam.
Course structure
The course will employ the platform Ariel for announcements and providing material. Lectures, exercises and lab sessions will be organized on Microsoft Teams (or Zoom) and can be followed according to the timetable or by means of recordings that will be available on Microsoft Teams (or Ariel).
Syllabus
The course syllabus will not be changed.
The assessment methods and critera for its results will not been changed, except for the fact that the final oral exam will be in person or on Microsoft Teams according to the existing directives in force at the time of the exam.
Course structure
The course will employ the platform Ariel for announcements and providing material. Lectures, exercises and lab sessions will be organized on Microsoft Teams (or Zoom) and can be followed according to the timetable or by means of recordings that will be available on Microsoft Teams (or Ariel).
Syllabus
The course syllabus will not be changed.
Course syllabus
Introduction. Initial value problems, well-posedness, conditioning and regularity. One-step methods: consistency, stability, convergence, stiffness and integrals of motion. Multi-step methods.
Prerequisites for admission
Analysis and Linear Algebra. Basic knowledge of the programming language C.
Teaching methods
Lectures, exercise and lab sessions.
Teaching Resources
P. Deuflhard, F. Bornemann, Scientific computing with ordinary differential equations, Springer 2002.
E. Hairer, S. P. Norsett, G. Wanner, Solving ordinary differential equations I. Nonstiff problems, 2nd edition, Springer 1993.
E. Hairer, G. Wanner, Solving ordinary differential equations II. Stiff and differential-algebraic problems, 2nd edition, Springer, 1996.
E. Hairer, S. P. Norsett, G. Wanner, Solving ordinary differential equations I. Nonstiff problems, 2nd edition, Springer 1993.
E. Hairer, G. Wanner, Solving ordinary differential equations II. Stiff and differential-algebraic problems, 2nd edition, Springer, 1996.
Assessment methods and Criteria
The examination consists of two parts:
- the evaluation of a small project to be chosen and
- a final oral exam on personal appointment after enrollment in an "appello".
The project has to be chosen from a list that will be published at the the beginning of each exam session. The project can be realized in collaboration with another person; each member of the group has to complete its exam within the validity of the given project list. The correct submission of the project consists in a zip archive containing source codes (but no exectuable files for the antivirus) and a pdf report which summarizes the obtained results on at most 5 pages; it is recommended to write the report not in collaboration. The zip archive, together with the name of the collaborator (if present), has to be sent by email two workdays before the oral exam.
In order to arrange the date of the oral exam, the student has to be enrolled in the current "appello"; it is recommended to contact the professor at least one week before the desired date. Usually, the oral exam starts with a brief discussion on the report and lasts 45 minutes. The student is invited to present a copy of its report and to prepare for questions both concerning or not the chosen project. The exam cannot be repeated with the same project.
The complete examination is passed if the report and its discussion are evaluated positively and the oral exam is successfully passed. Final marks are given using the numerical range 0-30, and will be communicated after the oral examination.
- the evaluation of a small project to be chosen and
- a final oral exam on personal appointment after enrollment in an "appello".
The project has to be chosen from a list that will be published at the the beginning of each exam session. The project can be realized in collaboration with another person; each member of the group has to complete its exam within the validity of the given project list. The correct submission of the project consists in a zip archive containing source codes (but no exectuable files for the antivirus) and a pdf report which summarizes the obtained results on at most 5 pages; it is recommended to write the report not in collaboration. The zip archive, together with the name of the collaborator (if present), has to be sent by email two workdays before the oral exam.
In order to arrange the date of the oral exam, the student has to be enrolled in the current "appello"; it is recommended to contact the professor at least one week before the desired date. Usually, the oral exam starts with a brief discussion on the report and lasts 45 minutes. The student is invited to present a copy of its report and to prepare for questions both concerning or not the chosen project. The exam cannot be repeated with the same project.
The complete examination is passed if the report and its discussion are evaluated positively and the oral exam is successfully passed. Final marks are given using the numerical range 0-30, and will be communicated after the oral examination.
MAT/08 - NUMERICAL ANALYSIS - University credits: 9
Practicals: 36 hours
Laboratories: 24 hours
Lessons: 36 hours
Laboratories: 24 hours
Lessons: 36 hours
Professors:
Bressan Nicoletta, Veeser Andreas
Professor(s)