
Stochastic dynamics
Stochastic dynamics is the study of dynamical processes that occur on sufficiently large time scales such that the fast microscopic degrees of freedom can be effectively described by stochastic noise. The paradigmatic case is the movement of a Brownian particle (e.g. a plastic bead of micrometer dimensions) in a fluid (e.g. water). Then the particle trajectory performs a random walk effected by the random forces exerted by the molecules of the fluid. The mathematical tool required to describe this situation is a stochastic differential equations, also known as the Langevin equation. Alternatively one can use the FokkerPlanck equation, which is a partial differential equation for the probability density p(x,t) of the particle to be at position x at time t. For stochastic processes with jumps, the appropriate equation is the master equation.
Stochastic dynamics has many applications, e.g. in physics, chemistry, biology and economics. In this course, we will provide an introduction into the fundamentals of this field, in particular to the three fundamental types of equations. Applications will be chosen from the fields of biophysics, finance and materials science. If time permits, we will also discuss the path integral approach to stochastic processes as well as recent developments in nonequilibrium physics and stochastic thermodynamics. The basic material for this course is covered well by the book by Honerkamp (see below).
The course is designed for physics students in advanced bachelor and beginning master semesters (students from other disciplines are also welcome). It will be given in English. A basic understanding of physics and differential equations is sufficient to attend. A background in statistical physics is helpful, but not required. The course takes place every Monday from 2.15  3.45 pm in lecture hall HS2 in KIP (INF 227). Every second week on Wednesday from 2.15  3.45 pm the solutions to the exercises will be discussed in a tutorial (seminar room 2.403 in KIP, INF 227, starting November 6). If you attend the course and solve more than 50 percent of the exercises, you earn 4 credit points. We recommend to complement this course by the one on nonlinear dynamics (Wednesday 9.15  10.45 am at Philosophenweg 12). The last lecture will take place on Jan 27.
Material for the course
 Introduction Oct 14 2013
 Notes on oscillators Oct 14 2013
 Presentation on Jarzynski equation Jan 27 2014
Exercises
 1st set Oct 28 2013
 2nd set Nov 11 2013
 3rd set Nov 25 2013
 4th set Dec 09 2013
 5th and last set Jan 13 2013
Literature
 J. Honerkamp, Stochastische Dynamische Systeme, VCH 1990
 W. Paul and J. Baschnagel, Stochastic Processes: From Physics to Finance, Springer 1999
 R. Zwanzig, Nonequilibrium Statistical Mechanics, Oxford University Press 2001
 U. Seifert, Stochastic thermodynamics, fluctuation theorems, and molecular machines, Rep. Prog. Phys. 75, 126001, 2012
 C.W. Gardiner, Handbook of stochastic methods, Springer 2004
 N.G. van Kampen, Stochastic Processes in Physics and Chemistry, Elsevier 1992
 W. Horsthemke und R. Lefever, Noiseinduced transitions. Theory and Applications in Physics, Chemistry, and Biology, Springer 1984
 H. Risken, The FokkerPlanck Equation, Springer 1996
 H. C. Berg, Random Walks in Biology, Princeton University Press 1993
 P. Nelson, Biological Physics, Freeman 2003
 R. Phillips and coworkers, Physical Biology of the Cell, 2nd edition Garland Sci. 2012