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Syllabus for

Academic year
TIF105 - Stochastic processes in physics, chemistry and biology
Owner: FCMAS
5,0 Credits (ECTS 7,5)
Grading: TH - Five, Four, Three, Not passed
Level: D
Department: 16 - PHYSICS

Teaching language: English

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 No Sp
0106 Examination 5,0 c Grading: TH   5,0 c   Contact examiner,  Contact examiner

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Univ lektor  Lennart Sjögren


For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

The student should have taken a course in equilibrium statistical mechanics and thermodynamics, and mathematical courses corresponding to the first three years at the Technical Physics program at Chalmers


Systems in nature are usually very complex with many degrees of freedom, and consisting of many interacting particles of different components.
Examples are colloidal dispersions, polymer solutions and melts, gels, glasses, biological systems and even financial systems and traffic jams.
Since the microscopic structure of such systems are only partially known, their time evolution is usually modelled by a stochastic process. This stochastic process describes then the fluctuations in the system and the respons to external perturbations. This course introduces the important stochastic processes and their properties,
which are used to describe various systems in nature.
This course can serve as an introduction to the course in
Nonequilibrium Statistical Physics.


In this course the student should acquire a general knowledge of stochastic processes and their use to describe the time evolution of systems in nature.

The following topics are covered:

Statistical description of a macroscopic system. Stochastic processes and basic distributions. Markov processes and master equations. Time evolution of
distribution functions. Langevin theory of Brownian motion, Fokker-Planck equation. Noise and fluctuation-dissipation theorem. Stochastic differential equations. Applications to physical, chemical and biological systems.


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Page manager Published: Thu 03 Nov 2022.