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Advanced Discretization Methods

Description

COURSE OBJECTIVES

At the end of the course, the student will be able to: - use the major concepts and results of spectral methods theory - plan and write computer code

 

COURSE DESCRIPTION
The course examines the development and analysis of spectral methods for the solution of time-dependent partial differential equations. Topics include key elements of approximation and stability theory for Fourier and polynomial spectral methods, as well as temporal integration and numerical aspects.

 

LEARNING METHODS
The course will use lectures, homework and reading assignments.

 

EXAMINATION INFORMATION
The course will be evaluated through homework, midterm and final exams

 

REFERENCES

  • Spectral methods for time-dependent problems implementation, post-processing and error estimates; J. Hesthaven, S. Gottlieb, D. Gottlieb

People

 

Pivkin I.

Course director

Additional information

Semester
Spring
Academic year
2020-2021
ECTS
6
Language
English
Education
Master of Science in Computational Science, Core course, Lecture, 1st year
PhD programme of the Faculty of Informatics, Elective course, Lecture, 1st year (4 ECTS)
PhD programme of the Faculty of Informatics, Elective course, Lecture, 2nd year (4 ECTS)