Stochastic Methods for Optimization/Simulation
Field of study: Biophysics
Programme code: W4-S2BFA21.2021

Module name: | Stochastic Methods for Optimization/Simulation |
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Module code: | W4-2BF-MB-21-15 |
Programme code: | W4-S2BFA21.2021 |
Semester: | summer semester 2021/2022 |
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] |
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students will be able to devise efficient sampling methods for sampling any multi-dimensional probability distribution [MB_15_1] |
KBF_W03 [4/5] |
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] |
students will be able to perform Monte Carlo simulations of both classical and quantum systems [MB_15_3] |
KBF_W03 [4/5] |
Type | Description | Codes of the learning outcomes of the module to which assessment is related |
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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 |
Form of teaching | Student's own work | Assessment of the learning outcomes | |||
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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 |
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Module description (PDF) |
Syllabuses (USOSweb) | ||
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Semester | Module | Language of instruction |
(no information given) |