SylabUZ
| Course name | Computer simulations |
| Course ID | 13.2-WF-FizD-CS- 17 |
| Faculty | Faculty of Physics and Astronomy |
| Field of study | Physics |
| Education profile | academic |
| Level of studies | Second-cycle studies leading to MS degree |
| Beginning semester | winter term 2019/2020 |
| Semester | 2 |
| ECTS credits to win | 6 |
| Available in specialities | Theoretical physics |
| Course type | obligatory |
| Teaching language | english |
| Author of syllabus |
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| The class form | Hours per semester (full-time) | Hours per week (full-time) | Hours per semester (part-time) | Hours per week (part-time) | Form of assignment |
| Lecture | 15 | 1 | - | - | Exam |
| Laboratory | 30 | 2 | - | - | Credit with grade |
The aim of the course is to gain basic knowledge of computer simulation methods and the ability to choose the appropriate simulation model to the considered problem. Students should acquire skills in implementation of this knowledge by designing the proper algorithms and then interpreting the results of computer simulations.
Ability to use some programming language.
- Representation of numbers, excess and underflow errors, truncation error (finite difference method), the stability of numerical algorithms.
- Algorithms for solving the equations of motion: Euler, Verlet, velocity Verlet, numerical solution of the harmonic oscillator.
- Monte Carlo algorithms (random number generators, random variables with different probability distributions, Metropolis algorithm, stochastic equations).
- Selected examples of applications (simulation of phase transitions, relaxation of the electric dipole)
Lectures and laboratory exercises, discussions, independent work with a specialized scientific literature in Polish and English, and work with the technical documentation and search for information on the Internet.
| Outcome description | Outcome symbols | Methods of verification | The class form |
Lecture: positive evaluation of the test.
Laboratory: positive evaluation of the tests, the execution of the project.
The final evaluation of the laboratory: evaluation of tests of 60%, the assessment of the project 40%.
Before taking the exam the student must be credited with the exercises.
Final grade: arithmetic mean of the completion of the lecture and in excersises.
[1] J.C. Berendsen and W.F. Van Gunsteren, Practical Algorithms for Dynamic Simulations in Molecular dynamics simulations of statistical mechanical systems, Proceedings of the Enrico Fermi Summer School, p. 43 - 45, Soc. Italinana de Fisica, Bologna 1985.
[2] Stephen Wolfram, Statistical mechanics of cellular automata, Rev. Mod. Phys. 55, 601 - 644 (1983).
[3] Tao Pang, An Introduction to Computational Physics, Cambridge University Press (2006).
[1] William H. Press, Saul A. Teukolsky, William T. Vetterling, Brian P. Flannery, Numerical recipes, The art of scientific computing, third edition 2007.
Modified by dr hab. Piotr Lubiński, prof. UZ (last modification: 05-03-2020 15:43)
