SylabUZ
| Course name | Modeling and simulations of physical systems |
| Course ID | 13.2-WF-FizD-MSPS-S19 |
| 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 | Computer 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 | 30 | 2 | - | - | Exam |
| Laboratory | 30 | 2 | - | - | Credit with grade |
The aim of the course is to gain a knowledge of computer simulation methods, their applications, strong and weak sides. Students should acquire skills in implementation of this knowledge by designing the proper algorithms and then interpreting the results of computer simulations.
Object oriented programming in Java or Python or C++, introduction to computer simulations, basics of MD and MC algorithms and techniques.
- Random walk – lattice and off-lattice, lattice gas model
- Percolation
- MC simulations of spin system with interactions
- Queue systems
- Computer simulations of polymers
- Basics of Molecular Dynamic – revision
- System with two atom interactions
- Molecular mechanics and force field
- NVE, NPT, NVT ensemble – MD simulations
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 practical exam.
- Laboratory: evaluation of laboratories of 30%, the assessment of the project 70%.
- Before taking the examination the student needs to obtain passing grade in the laboratory exercises.
- The final grade: the arithmetic average of the examination grade and laboratory exercises grade.
[1] D. Frenkel, B. Smit, Understanding Molecular Simulation. From Algorithms to Applications, Academic Press 2002.
[2] M. P. Allen, D. J. Tildesley, Computer Simulation of Liquids, Oxford University Press 1990.
[3] D. P. Landau, K. Binder, A guide to Monte Carlo Simulations in Statistical Physics, Cambridge University Press, 2005.
[4] K. Binder, D. W. Heerman, Monte Carlo Smulation in Statistical Physics, Springer 2010. (5th ed).
Modified by dr hab. Piotr Lubiński, prof. UZ (last modification: 05-03-2020 14:40)
