FPF:UFTF519 Numerical Methods II - Course Information
UFTF519 Numerical Methods II
Faculty of Philosophy and Science in OpavaSummer 2014
- Extent and Intensity
- 3/2/0. 6 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- prof. Ing. Peter Lichard, DrSc. (lecturer)
prof. Ing. Peter Lichard, DrSc. (seminar tutor) - Guaranteed by
- prof. Ing. Peter Lichard, DrSc.
Centrum interdisciplinárních studií – Faculty of Philosophy and Science in Opava - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Theoretical Physics (programme FPF, N1701 Fyz)
- Course objectives
- To prepare students for effective and correct numerical solution of physical problems and learn how to use computers for numerical calculations.
- Syllabus
- Monte Carlo method. Random numbers. Random number generator with uniform and Gaussian distribution. Multidimensional integrals with general integration areas. Accelerating convergence importance sampling. Estimation of statistical errors result. Modeling of physical processes using Monte Carlo.
Numerical solution of ordinary differential equations. Cauchy problem for a system of first order equations and the equation of n-th order. Euler's method. Modified and improved Euler method. General knowledge of single-knot methods. Local and accumulated error. Directional function and its structure Taylor method. Runge and Kutta. Examples of methods 1, 2, and third degree. Generalization of the first set of equations Regulations.
Method networks. Boundary value problems for ordinary differential equations. Network solutions by Gauss method. Boundary value problems for partial differential equations of elliptic type in a rectangular area.
Minimizing functions. Formulation of the problem, global and local minimum. One-dimensional problem, the method of variable step Rosenbrock method. Multivariate role. Random search method, method of variation of one parameter, the simplex method, gradient method, simulated annealing.
- Monte Carlo method. Random numbers. Random number generator with uniform and Gaussian distribution. Multidimensional integrals with general integration areas. Accelerating convergence importance sampling. Estimation of statistical errors result. Modeling of physical processes using Monte Carlo.
- Literature
- recommended literature
- Přikryl, P. Numerické metody matematické analýzy. SNTL, 1988. info
- Segethová, J. Základy numerické matematiky. Karolinum, 1988. info
- Marčuk, G.I. - Přikryl, P. - Segeth, K. Metody numerické matematiky. Academia, 1987. info
- Riečanová, Z. Numerické metódy a matematická štatistika. SNTL, 1987. info
- Ralston, A. Základy numerické matematiky. Academia, 1978. info
- Nekvinda, M. - Šrubař, J. - Vild, J. Úvod to numerické matematiky. SNTL, 1976. info
- Language of instruction
- Czech
- Further Comments
- The course can also be completed outside the examination period.
- Teacher's information
- * 60% attendance in seminars.
- Enrolment Statistics (Summer 2014, recent)
- Permalink: https://is.slu.cz/course/fpf/summer2014/UFTF519