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401-3823-74L 3 Credits BSC , MSC D-MATH

Markov Processes

Lecturers & Examiners: Dr. Rishabh Sunil Gvalani
VVZ CR n/a

Last Updated: 2026-02-05 16:29:37

Abstract

This course is meant to serve as an introduction to the theory of Markov processes on finite or countable state spaces. We will discuss what a Markov process is along with associated concepts such as transition probabilities, recurrence, transience, ergodicity, reversibility etc. We will motivate various abstract notions introduced with concrete examples from physics and statistics.

Objective

I. Discrete-time Markov processes, i.e. Markov chains, e.g. the random walk on the integers II. Transition probabilities and Doeblin's theorem III. Stationary probabilities and ergodic properties IV. Continuous-time Markov processes. e.g. the Poisson process V. Reversibility

Resources

Literature

An Introduction to Markov Processes: Daniel W. Stroock

General Information

Language
English
Levels
BSC , MSC

Examination

Type
session examination
Mode
oral 20 minutes
The exam is only offered in the two examination sessions Winter 2025 and Summer 2025.

Course Components

Type Title Time & Place Hours
lecture Markov Processes
Takes place in the first half of the semester until mid October.
  • Tue 08:15-10:00 (HG D 7.1)
  • Wed 08:15-10:00 (HG D 7.1)
  • 03.12 Date 08:15-10:00 (HG D 7.1)
  • 04.12 Date 08:15-10:00 (HG D 7.1)
  • 10.12 Date 08:15-10:00 (HG D 7.1)
  • 11.12 Date 08:15-10:00 (HG D 7.1)
20 h semesterly

Offered In