PřF:FA045 Sel. chapt. mod. comp. meth. - Course Information
FA045 Selected chapters from modern computational methods
Faculty of ScienceSpring 2021
- Extent and Intensity
- 2/1/0. 4 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- Mgr. Filip Hroch, Ph.D. (lecturer)
Mgr. Viktor Votruba, Ph.D. (lecturer) - Guaranteed by
- prof. Mgr. Jiří Krtička, Ph.D.
Department of Theoretical Physics and Astrophysics – Physics Section – Faculty of Science
Contact Person: Mgr. Filip Hroch, Ph.D.
Supplier department: Department of Theoretical Physics and Astrophysics – Physics Section – Faculty of Science - Prerequisites (in Czech)
- We are assuming some skills in mathematics: a common function handle (derivation, integration), linear algebra. Computer skills includes a basic knowledge of programming, and usual Unix tools.
- Course Enrolment Limitations
- The course is offered to students of any study field.
- Course objectives (in Czech)
- An introduction to modern computation methods of physical problems: non-linear partial diferential equations, massive data processing, etc.
- Learning outcomes (in Czech)
- Students will be able to applicate of the methods on solution of various numerical problems.
- Syllabus (in Czech)
- Explicit methods for partial diferential equations of hyperbolic and parabolic kinds by the finnite diference methods. Applications in fluid dynamics, Kelvin-Helmholtz unstability simulations.
- Implicit methods for for partial diferential equations of hyperbolic and parabolic kinds by the finnite diference methods. Applications on difusion, heat propagation. NUmerical limits of applications, stability.
- Smooth particle hydrodynamics (SPH), Particle Mesh(PM) and Particle in Cell (PIC). Plasma process simulation, two-component unstability.
- N-particle algorithms, particle in gravitation field, methods for molecular dynamics.
- Methods for handling of large data sets, data mining.
- Machine learning, supervised and unsupervised, Support Vector Machines, K-means clustering, neural networks.
- General classification, regression. Time-series anomaly recognizing.
- Literature
- BODENHEIMER, Peter. Numerical methods in astrophysics : an introduction. New York: Taylor & Francis, 2007, 329 s. ISBN 9780750308830. info
- Teaching methods (in Czech)
- A common form of teaching will be lectures iterative presenting given topics.
- Assessment methods (in Czech)
- A final project should be prepared, and referred, for the successful complete. Homeworks may be included.
- Language of instruction
- English
- Further comments (probably available only in Czech)
- The course is taught once in two years.
The course is taught: every week.
General note: L.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/spring2021/FA045