The course provides a comprehensive introduction to the theoretical foundations of statistical physics and its connections to thermodynamics. Topics covered include the statistical definitions of temperature and entropy, microstates and macrostates, statistical ensembles and the partition function, the density matrix and Fock space, theory of free classical and quantum gases, Bose-Einstein and Fermi-Dirac statistics, phase transitions, and spin models.
Learning outcome
After completing the course, students should:
K1: Have a solid understanding of core concepts in statistical physics and thermodynamics, and comprehend the connection between microstates and macrostates in thermodynamic systems.
F1: Be able to compute thermodynamic quantities and correlation functions in equilibrium for both quantum mechanical and classical models in statistical mechanics, using various techniques and approximations.
F2: Be capable of performing simple numerical Monte Carlo simulations of basic statistical physics models.
G1: Understand the broad range of applications of statistical physics in various fields of science and in everyday life.
Required prerequisite knowledge
FYS200 Thermo- and Fluid Dynamics, STA100 Probability and Statistics 1
There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.