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Theory of Stochastic Processes

Module PH1006

This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.

Module version of WS 2015/6

There are historic module descriptions of this module. A module description is valid until replaced by a newer one.

available module versions
SS 2019WS 2015/6

Basic Information

PH1006 is a semester module in German language at Master’s level which is offered in summer semester.

This Module is included in the following catalogues within the study programs in physics.

  • Theory courses for condensed matter physics
  • Theory courses for Biophysics
  • Complementary catalogue of special courses for nuclear, particle, and astrophysics
  • Complementary catalogue of special courses for Applied and Engineering Physics
  • Specialization Modules in Elite-Master Program Theoretical and Mathematical Physics (TMP)

If not stated otherwise for export to a non-physics program the student workload is given in the following table.

Total workloadContact hoursCredits (ECTS)
300 h 90 h 10 CP

Responsible coordinator of the module PH1006 in the version of WS 2015/6 was Ulrich Gerland.

Content, Learning Outcome and Preconditions


The lecture develops the theory of stochastic processes and the methods for their analysis. Examples to practice the acquired methods will be chosen primarily from the area of biophysics, but the major teaching and learning content (see below) is relevant for all areas of physics.

Learning Outcome

At the end of the module students know the basic methods to handle physical systems that can be described by stochastic processes as well as the basic assumptions necessary to apply them. They are able to

  1. set up and solve Master equations, stochastic differential equations and Fokker Planck equations and know simple simulation methods.
  2. understand and apply the basic principles of stochastic thermodynamics and large devation theory.
  3. apply and adapt approximation methods for the analysis of complex stochastic processes


A solid basis in statistical physics (e.g. PH0008) is assumed.

Courses, Learning and Teaching Methods and Literature

Courses and Schedule

VO 4 Theory of Stochastic Processes Gerland, U. Wed, 12:00–14:00, PH HS3
Mon, 08:30–10:00, PH HS3
UE 2 Exercise to Theory of Stochastic Processes Altaner, B. Bojer, M. Kremser, S. Martini, L.
Responsible/Coordination: Gerland, U.
dates in groups

Learning and Teaching Methods

The modul consists of a lecture and exercise classes.

In the thematically structured lecture the theoretical contents are presented and discussed. The theoretical models for the description of stochastic processes are developed on the blackboard together with the students. Concrete physical examples are studied in-depth and compared to experimental results.

In the problem sets the students have the opportunity to apply the presented techniques to concrete problem examples and to analyze the results. In the course of this analytic calculation exercises, simple numerical simulations and conceptual questions with answers in the form of continuous text are chosen as task form. The solution proposals of the students are corrected to give the students feedback for their modeling and solution abilities and to detect and correct misconceptions as early as possible. 

In the exercises (tutor groups) additional understanding questions are answered together with the students. Furthermore, specific topics of the lecture are discussed in-depth and relevant aspects are reviewed in regular intervals. Questions of students are given a large space.


Lecture notes, problem sheets, web page


  • Crispin Gardiner: "Stochastic Methods: A Handbook for the Natural and Social Sciences" (Springer)
  • N.G. van Kampen: "Stochastic Processes in Physics and Chemistry" (North-Holland)

Module Exam

Description of exams and course work

There will be a written exam of 90 minutes duration. Therein the achievement of the competencies given in section learning outcome is tested exemplarily at least to the given cognition level using calculation problems and comprehension questions.

For example an assignment in the exam might be:

  • Modelling of a concrete example with a Master equation and solving the equation
  • Approximation of a given Master equation through a Fokker-Planck equation with the Kramers-Moyal or Van Kampen Expansion, Solution of the Fokker-Planck equation
  • Transformation of a Langevin Equation into a Fokker-Planck equation
  • Calculating the entropy production of a system obeying a Master equation

Participation in the exercise classes is strongly recommended since the exercises prepare for the problems of the exam and rehearse the specific competencies.

There will be a bonus (one intermediate stepping of "0,3" to the better grade) on passed module exams (4,3 is not upgraded to 4,0). The bonus is applicable to the exam period directly following the lecture period (not to the exam repetition) and subject to the condition that the student passes the mid-term of

  • Registration for a tutorial in TUM-Online.
  • For at least 70% of the homework problems a resonable attempt to solve the question has to be made. (A question counts as resonable attempted if your handed in homework shows that you made a substantial effort to solve the problem by using the theory presented in the lecture. The decision if a homework problem is resonable attempted is made by the correctors of the homework.)
  • One of the Homework-sheets will be replaced by a test exam, which will be held during one of the lectures. The questions of the test exam will count as a normal homework questions towards the bonus.

Exam Repetition

The exam may be repeated at the end of the semester.

Current exam dates

Currently TUMonline lists the following exam dates. In addition to the general information above please refer to the current information given during the course.

Prüfung zu Theorie stochastischer Prozesse
Fr, 16.8.2019, 13:30 bis 15:00 PH: 2502
bis 30.6.2019 (Abmeldung bis 9.8.2019)
Di, 8.10.2019, 13:30 bis 15:00 PH: 2502
bis 23.9.2019 (Abmeldung bis 1.10.2019)
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