Statistical physics bridges microscopic particle behavior with macroscopic physical properties using probabilistic methods. It explains how systems with a vast number of particles, such as gases or solids, exhibit predictable thermodynamic behavior despite the randomness at the microscopic level. The course typically covers key concepts like the microcanonical, canonical, and grand canonical ensembles, the laws of thermodynamics, entropy, partition functions, and fluctuations. It also explores applications to ideal and real gases, phase transitions, quantum statistics (Bose-Einstein and Fermi-Dirac), and critical phenomena. Overall, statistical physics provides a fundamental framework for understanding matter in equilibrium from a microscopic point of view.
Objectives:
- To develop an understanding of how macroscopic physical properties emerge from microscopic particle interactions.
- To introduce the formalism of statistical ensembles and their application to physical systems.
- To apply probability theory and thermodynamic principles to analyze systems in equilibrium.
- To explore the statistical foundations of thermodynamic laws.
- To examine classical and quantum distributions and their implications for physical behavior.
Learning Outcomes:
- Explain the principles and assumptions underlying statistical mechanics.
- Derive and interpret key thermodynamic quantities using statistical methods.
- Distinguish between different statistical ensembles and apply them to relevant problems.
- Analyze systems of particles using classical and quantum statistical distributions (Maxwell-Boltzmann, Bose-Einstein, Fermi-Dirac).
- Apply statistical mechanics to real-world systems such as gases, magnets, and phase transitions.
- Solve problems involving entropy, energy distributions, and fluctuations in equilibrium systems.
Academic Year 2024-2025
Lecturer: Augustin SIWEGUSA
- Teacher: content creator