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
The faculty decides whether early dialogue should be conducted in all or selected groups of courses offered by the faculty. The purpose is to gather feedback from students for making changes and adjustments to the course during the current semester. In addition, a digital evaluation, students’ course evaluation, must be conducted at least once every three years. Its purpose is to collect students` experiences with the course.