Headings denoted with an asterisk ( * ) is retrieved from the course syllabus version Spring 2022
Content and learning outcomes
Course contents
The Monte Carlo and molecular dynamics methods. Simulations in different statistical mechanical ensembles. Computation of free energies. Stochastic dynamics. Applications to spin systems, fluids, polymers and biological macromolecules.
Intended learning outcomes
To give an introduction to computational physics, which is a third area of physics beside experimental and theoretical physics. The goal is that the students should be able to:
To understand the difference between simulations and other approximative and analytical methods
To perform simulations and computations with available programs.
Be able to write simple programs and make modifications of available programs.
To understand the importance and limitations of a number of basic models with very broad applicability
Be able to critically judge published results taking into account the limitations of the models and the statistical nature of several of the methods.
Learning activities
Course activities
9 Lectures covering theoretical ideas
5 computer labs giving hands on experience of several types of simulations
1 larger project exercise
See the schedule and Canvas page for detailed information.
Preparations before course start
Recommended prerequisites
Statistical mechanics and quantum mechanics corresponding to SI1161 quantum physics and some familiarity with computers and computer programming.
Literature
Lecture notes, articles and parts of books. See Canvas for details.
Support for students with disabilities
Students at KTH with a permanent disability can get support during studies from Funka:
INL1 - Assignment, 4.5 credits, Grading scale: A, B, C, D, E, FX, F
LAB1 - Laboratory Work, 3.0 credits, Grading scale: P, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
The section below is not retrieved from the course syllabus:
Requirements
Written reports for the labs and the project.
LAB1 - Laboratory Work, 3.0 credits 5 computer labs, graded with P/F. Hand in individually written lab reports on Canvas. Deadline: 1 week after the computer lab.
INL1 - Assignment, 4.5 credits Individual project, graded A-F (or P/F for PhD students taking SI3080). May be submitted only after completion of the computer labs. Deadline: End of semester.
Other requirements for final grade
Computer assignments (LAB1; 3 university credits) Written exercises (INL1; 4,5 university credits).
Ethical approach
All members of a group are responsible for the group's work.
In any assessment, every student shall honestly disclose any help received and sources used.
In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.