(in Polish) Computer simulations in physics 1100-CSP
1. Introduction: what is the benefit of using computer simulation models?
2. Crash course on Python.
3. Molecular Dynamics:
- Newtonian mechanics
- numerical integration
- simulation of noble gases
4. Probabilistic models:
- percolation
- Monte Carlo methods
- Ising model
5. Network models:
- diffusion-limited aggregation
- self-organized criticality
- Wa-Tor
Mode
Prerequisites (description)
Course coordinators
Learning outcomes
Learning outcomes – Computer Simulations in Physics (EN)
Knowledge:
The student knows and understands the role of computer simulations as a research tool in physics and the relationship between theoretical models, numerical simulations, and experiments. The student knows and understands selected classes of physical models used in computer simulations, in particular classical dynamics, molecular dynamics, probabilistic models, and network models. The student knows and understands basic numerical methods used in physical simulations as well as their limitations, sources of errors, and numerical artifacts. The student knows and understands basic elements of Python syntax and program structure necessary to implement simple physical simulations.
Skills:
The student is able to translate a physical phenomenon or theoretical model into a simulation algorithm and its computer implementation. The student is able to independently implement simple simulations of selected physical systems in Python and perform numerical computational experiments. The student is able to analyze, visualize, and interpret simulation results in a physical context, taking into account model assumptions and numerical limitations. The student is able to present selected topics or simulation results in English in the form of a short oral presentation.
Social competences:
The student is ready for independent and systematic work on computational problems and for further development of skills in numerical methods. The student is ready to critically assess the results of computer simulations and to formulate responsible physical conclusions. The student is ready to actively participate in substantive discussions on physical models and computational results. The student is ready to observe the principles of academic integrity, in particular the independent creation and understanding of computer code.
Assessment criteria
he final grade for the course consists of the assessment of continuous work during laboratory classes and the assessment of theoretical knowledge. The primary assessment method is a set of individual programming assignments carried out during computer lab sessions, which require independent implementation of physical models and analysis of simulation results. Assignments are assessed on an ongoing basis by the instructor, taking into account the physical correctness of the model, proper functioning of the code, quality of result interpretation, and the level of student independence. Tasks completed during class are graded with full credit, while tasks completed after class are graded with reduced credit according to the rules announced at the beginning of the course. Additional points may be awarded for optional advanced tasks of increased difficulty.
Theoretical knowledge is assessed through two short written tests (a midterm and a final test), covering topics discussed in the introductory lectures and during class summaries. The tests verify understanding of physical models, simulation methods, and limitations of numerical techniques.
An additional assessment component is a short oral presentation in English, in which the student presents a selected topic or model discussed during the course. The presentation is evaluated in terms of scientific correctness, clarity of presentation, and the ability to interpret simulation results.
To pass the course, the student must obtain at least 50% of the total available points and at least 50% of the points from the theoretical part. Active participation in laboratory classes is required to complete the course.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: