Introduction to Computational Physics 1
Code | Completion | Credits | Range | Language |
---|---|---|---|---|
812UPF1 | Z,ZK | 2 | 1P+1C | Czech |
- Course guarantor:
- Milan Kuchařík
- Lecturer:
- Pavel Eichler
- Tutor:
- Pavel Eichler
- Supervisor:
- Department of Software Engineering
- Synopsis:
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Numerical simulation and its role in physics, methodology of writing computer codes. Computer languages for physics. Numerical libraries and program libraries for physics. Computer tools for scientific visualization. Computational fluid dynamics, hydrodynamic simulations, methods for discretization of Euler equations. High-performance computing, parallel computing, software for parallel simulations. Databases of scientific information, scientist evaluation, citation analysis.
- Requirements:
- Syllabus of lectures:
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1. Computers in physics. Computer experiment. Laws of physics, mathematical models, numerical scheme.
2. Scientific databases. Electronic databases of scientific journals and reports. Evaluation of scientific journals and scientists, publications, citation analysis.
3. Computer hardware, computer memory hierarchy. Supercomputers, high-performance computing. Computer languages for physics, compilers. Numerical libraries.
4. Parallel computing, shared/distributed memory computing. Software tools and libraries for parallelization.
5. Methodology of scientific programming. Errors in scientific codes. Numerical algorithms for physics.
6. Computational fluid dynamics (CFD). Experiment versus simulation. Euler equations. Computational meshes, discretization in time and space. Verification and validation. Software tools for CFD.
7. Finite differences -finite differences, difference schemes, explicit/implicit schemes.
8. Finite volumes -integral form of the equations, flux form, numerical methods for integration.
9. Finite elements -approximation by basis functions, splitting of temporal and spatial derivatives.
10. Other methods: spectral methods, boundary elements methods, mesh-free methods, smoothed-particle hydrodynamics, lattice Boltzmann method.
11. Solving Euler equations, basic types of methods in Eulerian reference frame.
12. Scientific visualization. Types of graphs in physics. Software tools for scientific visualization.
- Syllabus of tutorials:
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following lecture
- Study Objective:
- Study materials:
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Key references:
[1] R. H. Landau, M. J. Paez, Ch. C. Bordeianu: Computational Physics: Problem Solving with Python, 3rd Edition, Wiley,2015. ISBN 978-3527413157.
[2] H. Gould, J. Tobochnik, W. Christian: An Introduction to Computer Simulation Methods: Applications to Physical Systems, CreateSpace Independent Publishing Platform; 3rd Revised edition, 2017. ISBN 978-1974427475.
Recommended references:
[3] T. Pang: An Introduction to Computational Physics, 2nd Edition, Cambridge University Press, 2006. ISBN 978-0521825696.
Tools:
UNIX computer laboratory.
- Note:
- Time-table for winter semester 2024/2025:
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06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri - Time-table for summer semester 2024/2025:
- Time-table is not available yet
- The course is a part of the following study plans:
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- Applications of Informatics in Natural Sciences (compulsory course in the program)