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Random phenomena are of paramount importance in all areas of science. In the theory of random or stochastic processes, the random evolution of time-dependent quantities is considered. Prominent examples are the Brownian motion of a particle immersed in a liquid, the evolution of a chemical reaction, the motion of charge carriers in an electrical circuit, and the price fluctuations of a security on the stock market.
This lecture starts with a concise introduction to the basic concepts of probability theory and random processes. Markov processes as particularly important class of stochastic processes are discussed and their applications to various fields is presented.
Wednesday, 10:15-12:00h, Department of Physics, seminar room 4.1
Exercise classes are held every Wednesday, 15:00-16:30h in the seminar room 4.1. The problem set which has been handed out the week before is discussed and solved together with the assistant Diego Rainis.
Per problem set, one problem has to be handed in and will be graded, the programming project counts as two problem sets. Required for obtaining the credit points are 50% of the points of those problems and regular participation in the exercise class.
|Problem set 1: Birthday paradox; Baye's theorem; Transformation of variables||2012/09/26|
|Problem set 2: Discrete-time random walk; The Poisson distribution; Compound distribution||2012/10/03|
|Problem set 3: Branching processes; Compound distribution; Box-Muller algorithm||2012/10/10|
|Problem set 4: Shot noise; Sinusoidal process with random amplitude and phase; Cauchy-Schwarz inequality||2012/10/17|
|Problem set 5: Markov Chains; Metropolis-Hastings algorithm||2012/10/24|
|Problem set 6: First-passage problems and gambler's ruin||2012/11/07|
|Problem set 7: Dichotomic noise; Wiener process||2012/11/14|
|Problem set 8: Fokker-Planck equation; No perpetuum mobile of the second kind||2012/11/21|
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Condensed Matter Theory
last updated on 2008/03/19