Course - Stochastic processes and transport theory - TFY4275
Stochastic processes and transport theory
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About the course
Course content
The course focuses on central concepts in classical transport theory and their applications. The following topics are treated: Stochastic variables, stochastic processes, Markov processes, Langevin-equation. Correlation functions, Wiener-Khinchin theorem, fluctuation-dissipation theorem, Chapman-Kolomogorov-Smoluchowski equations, the Master equation, Fokker-Planck Equation, moment-equations. The Boltzmann equation, analogies to the Master Equation. Kinetic theory and the Boltzmann-equation, linearized Boltzmann-equation, eigenvalue-problem, hydrodynamic and kinetic modes. An exactly solved model: The Lorentz-gas. Semiclassical Boltzmann equation. Quantum transport in mesoscopic system, Landauer-Buttiker formalism. Emphasis will be placed on the physical contents and applications of transport theory.
Learning outcome
The course provides a general introduction to the fundamental concepts and principles of classical and quantum transport theory, together with some modern applications.
Learning methods and activities
Lectures and exercises. Lectures and lecture material are in English. Expected workload in the course is 225 hours.
Further on evaluation
The final grade in the course is based on written exam, which counts 100% of the final grade. Re-sit exam may be changed from written to oral.
Recommended previous knowledge
Good basic skills in physics, mathematics and statistics.
Course materials
Reading material will be distributed at the start of the semester.
Credit reductions
Course code | Reduction | From |
---|---|---|
SIF4074 | 7.5 sp | |
FY8907 | 7.5 sp | Autumn 2010 |
Subject areas
- Physics
Contact information
Course coordinator
Lecturers
Department with academic responsibility
Examination
Examination
Ordinary examination - Autumn 2024
School exam
The specified room can be changed and the final location will be ready no later than 3 days before the exam. You can find your room location on Studentweb.