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Numerical Methods

General data

Course ID:	1100-3`MNum
Erasmus code / ISCED:	11.301 The subject classification code consists of three to five digits, where the first three represent the classification of the discipline according to the Discipline code list applicable to the Socrates/Erasmus program, the fourth (usually 0) - possible further specification of discipline information, the fifth - the degree of subject determined based on the year of study for which the subject is intended. / (0612) Database and network design and administration The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Numerical Methods
Name in Polish:	Metody numeryczne
Organizational unit:	Faculty of Physics
Course groups:	Astronomy (1st level); Elective courses Astronomy, individual path; elective courses Physics (1st level); elective courses Physics (2nd cycle); numerical analysis courses, Physics, individual path; elective courses
ECTS credit allocation (and other scores):	6.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Short description:	The course will be focused on basic numerical methods used in scientific computer aided computations.
Full description:	The course will be focused on basic algorithms used in scientific computations and their implementation in the form of computer programs. Program: 1. Representation of numbers in computer memory; errors, accuracy, stability of computations. 2. Polynomial interpolation and extrapolation, Neville algorithm, splines. 3. Smoothing and approximation of data. 4. Solution of large systems of linear algebraic equations. 5. Solution of nonlinear sets of equations. 6. Integration of functions. 7. Random numbers and their applications - Monte Carlo Methods. 8. Minimization. 9. Sorting and searching. 10. Finding eigenvalues and eigenvectors of large matrices. 11. Fourier transform. 12. Solution of ordinary and partial differential equations. The lecture will be accompanied by classes where students will write programs implementing the algorithms described in the lectures and will familiarize themselves with software packages, which may be helpful in scientific computations and numerical analysis of data. The final note will depend on written test (44%), notes given by assistants for class activities (44%) and presence on classes (12%). Description by Tomasz R. Werner, December 2009.
Bibliography:	1. W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery: Numerical Recipes: The Art of Scientific Computing 2. G. Dahlquist and A. Björck: Numerical Methods in Scientific Computing 3. J. Stoer and R. Bulirsch: Introduction to Numerical Analysis 4. A. Ralston: First Course in Numerical Analysis

Classes in period "Summer semester 2024/25" (past)

Time span:	2025-02-17 - 2025-06-08	Selected timetable range: weekly course term Go to timetable MO WYK TU W CW TH FR CW
Type of class:	Classes, 30 hours, 20 places more information Lecture, 30 hours more information
Coordinators:	Jakub Tworzydło
Group instructors:	Konrad Kossacki, Jakub Tworzydło
Students list:	(inaccessible to you)
Credit:	Examination

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