Individual course details
Study programme General Physics, Applied and Computational Physics
Chosen research area (module)  
Nature and level of studies  
Name of the course Foundations of Statistical Physics
Professor (lectures) Prof. Milan Knežević
Professor/associate (examples/practical)  
Professor/associate (additional)  
ECTS 4 Status (required/elective) required
Access requirements Mathematics 2
Aims of the course Learn the main concepts, laws and methods of equilibrium thermodynamics and statistical physics.
Learning outcomes Students will be able to apply the acquired knowledge and methods in studies of simple equilibrium many-body systems.
Contents of the course
Lectures Fundamental concepts and laws of equilibrium phenomenological thermodynamics; applications to simple systems. Legendre transformations and thermodynamic potentials. Response functions. Equilibrium and stability conditions. Phases and phase transitions. First and second order phase transitions. Central limit theorem of probability theory. Shannon entropy. Foundation of classical statistical physics; Liouville's equation; ergodic hypothesis. Gibbs concept of statistical enesemble.  Microcanonical ensemble; Gibbs paradox. Canonical ensemble; partition function for idel gas; Maxwell-Boltzmann distribution; fluctuation of energy. Grand canonical enesemble; fluctuations of energy and number of particles. Quantum statistics of identical particles; average occupation numbers for idel bose and fermi particles; applicability of classical statistics. Thermodynamic properties of ideal fermions. Bose-Einstein condensation.  Statistics and thermodynamics of photon gas. 
Examples/ practical classes  
Recommended books
1 H. Callen, Thermodynamics and introduction to thermostatistics 2nd ed. John Wiley (1985)
2 S. Milošević, Osnovi fenomenološke termodinamike, PFV (1979)
3 R. Patria, Statistical mechanics, 2nd ed. Butterworth-Heinemann (1996)
4 I. Živić, Statistička mehanika, PMF Kragujevac (2006)
5  R. Kubo, Statistical physics, North-Holland (1965)
Number of classes (weekly)
Lectures Examples&practicals   Student project Additional
2 2      
Teaching and learning methods Lectures, example exercises, consultations, homework assignments
Assessment (maximal 100)
assesed coursework mark examination mark
coursework   written examination 30
practicals 10 oral examination 50
papers 10    
presentations