Course syllabus

Statistisk mekanik
Statistical Mechanics

FMFN25, 7,5 credits, A (Second Cycle)

Valid for: 2020/21
Decided by: PLED F/Pi
Date of Decision: 2020-04-01

General Information

Main field: Nanoscience.
Elective for: F4, F4-tf, MNAV2, N4, Pi4
Language of instruction: The course will be given in English


The course shall provide the foundations of statistical physics that is needed both in applications and for studies in theoretical physics. A focus is set on advanced concepts and methods to describe interacting many-particle systems and critical phenomena.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must

Judgement and approach
For a passing grade the student must

decide when a quantum mechanical analysis is necessary.


Statistical methods for macroscopic systems based on a quantum mechanical description. Relation to thermodynamics. Partion function, Gibbs entroy and free energy.  Phase transitions and critical phenomena. Ising model, transfer-matrix model, mean-field theroy and renormalization. Ideal gases. Fermi-Dirac statistics, Bose-Einstein statistics and Plancks law of radiation with applications for, e.g., electron and photon gases.

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Oral exam, written presentation of a project and mandatory laboratory work.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.


Assumed prior knowledge: Quantum mechanics corresponding to FAFF10 Atomic and Nuclear Physics with Applications or FMFF15 Quantum Mechanics and Mathematical Methods.
The number of participants is limited to: No
The course overlaps following course/s: FMF150, FMFN20

Reading list

Contact and other information

Course coordinator: Jakob Bengtsson,
Course coordinator: Anders Irbäck,
Course homepage: