Stochastic Methods for Optimization and Simulation Field of study: Biophysics
Programme code: W4-S2BFA21.2022

Module name: Stochastic Methods for Optimization and Simulation
Module code: W4-2BF-MB-21-15
Programme code: W4-S2BFA21.2022
Semester:
  • summer semester 2024/2025
  • summer semester 2023/2024
  • summer semester 2022/2023
Language of instruction: English
Form of verification: course work
ECTS credits: 4
Description:
This course will give students an operative knowledge of computational simulation and optimization techniques based on stochastic methods. Course syllabus: (1) Monte-Carlo Integration. Sampling techniques and variance reduction. (2) Stochastic optimization: simulated annealing and genetic algorithms. (3) Dynamic Monte Carlo: random walks and the diffusion equation. (4) Classical Monte Carlo simulations: from simple to molecular systems and biomolecules. (5) Application of Monte Carlo methods to quantum systems.
Prerequisites:
(no information given)
Key reading:
(no information given)
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
students will be able to devise efficient sampling methods for sampling any multi-dimensional probability distribution [MB_15_1]
 KBF_W03 [4/5] KBF_W08 [4/5] KBF_U01 [4/5] KBF_U02 [5/5] KBF_U14 [5/5] KBF_K02 [3/5]
students will be able to use of stochastic methods for the optimization of complex problems with arbitrary model functions [MB_15_2]
 KBF_W03 [4/5] KBF_W08 [4/5] KBF_U01 [4/5] KBF_U02 [5/5] KBF_U14 [5/5] KBF_K02 [3/5]
students will be able to perform Monte Carlo simulations of both classical and quantum systems [MB_15_3]
 KBF_W03 [4/5] KBF_W08 [4/5] KBF_U01 [4/5] KBF_U02 [5/5] KBF_U14 [5/5] KBF_K02 [3/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
credit [MB_15_w_1]
the final mark for this course is computed as 0.4 a + 0.4 b + 0.2 c, where a is the mean grade of each practical homework, b is the grade of the final project and c is the rating of written questions concerning the final project
 MB_15_1 MB_15_2 MB_15_3
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [MB_15_fs_1]
Detailed discussion by the lecturer of the issues listed in the table "module description" using the table and/or multimedia presentations
 24
Supplementary reading, working with the textbook, doing homework
 44 credit [MB_15_w_1]
laboratory classes [MB_15_fs_2]
Performance of exercises on the subject consistent with the issues listed in the table "module description"
 12
Acquiring knowledge in the scope of the exercise, preparation of the final report on a given exercise
 20 credit [MB_15_w_1]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)