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FSK3898 Stochastic Methods 5.0 credits

Course offering missing for current semester as well as for previous and coming semesters
Headings with content from the Course syllabus FSK3898 (Autumn 2018–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Random numbers, optimization methods, Markov processes, Monte Carlo methods and stochastic calculus and differential equations, survey of real world examples of stochastic methods.

Intended learning outcomes

After completing the course, you should be able to:

  • List examples of different stochastic methods and judge when the methods are applicable.
  • Explain the physical principles and background of Monte Carlo methods and stochastic calculus.
  • Illustrate and discuss how Monte Carlo methods are constructed.

Course disposition

3 weeks format in line with the SeSE course format:
1 week pre-study
1 week lectures and hands-on computer exercises
1 week project assignment

Literature and preparations

Specific prerequisites

Enrolled as PhD student.
Ph. D students in computational sciences and e-science.
Basic knowledge in statistics and probability theory and basic knowledge using Matlab/Octave.

Recommended knowledge: Basic courses in programming, matematical statistics and probability theory. 

Recommended prerequisites

No information inserted


Laptop with Matlab (or Octave) installed.


C. Gardiner, Stochastic Methods- A handbook for the Natural and Social Sciences , Springer Verlag 2009, ISBN: 978-3-540-70712-7
J. C. Spall, Introduction to Stochastic Search and Optimization, Wiley 2003, ISBN: 978-0-471-33052-3
N. G. van Kampen, Stochastic Processes in Physics and Chemistry, Elsevier, ISBN:978-0-444-52965-7

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale



  • LAB1 - Computer exercises, 1.5 credits, grading scale: G
  • PRO1 - Project work, 3.5 credits, grading scale: G

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

DAT1: Computer exercises, 1.5 hp credits, grade scale: P/F
PRO1: Project work, 3.5 hp credits, grade scale: P/F

Other requirements for final grade

Examination (pass/fail):
* Passing computer exercises
* Project work with oral and written presentation

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted


Profile picture Lars Bergqvist

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course web

No information inserted

Offered by

SCI/Applied Physics

Main field of study

No information inserted

Education cycle

Third cycle

Add-on studies

No information inserted


Lars Bergqvist (

Postgraduate course

Postgraduate courses at SCI/Applied Physics