Syllabus for |
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| TIF035 - Computational materials physics |
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| Syllabus adopted 2012-02-22 by Head of Programme (or corresponding) |
| Owner: MPAPP |
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7,5 Credits |
| Grading: TH - Five, Four, Three, Not passed |
| Education cycle: Second-cycle |
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Major subject: Engineering Physics |
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Department: 16 - PHYSICS
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Teaching language: English
Open for exchange students
Block schedule:
B
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Credit distribution |
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Examination dates |
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Sp1 |
Sp2 |
Sp3 |
Sp4 |
Summer course |
No Sp |
| 0105 |
Written and oral assignments |
7,5c |
Grading: TH |
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7,5c
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In programs
MPAPP APPLIED PHYSICS, MSC PROGR, Year 1 (elective)
MPCAS COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 2 (elective)
Examiner:
Docent
Anders Hellman
Course evaluation:
http://document.chalmers.se/doc/1ab30cf3-79c3-42a5-a30c-634acf9358e2
Eligibility:
For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.
Course specific prerequisites
Basic undergraduate physics and mathematics, computing and numerical analysis. Computing and numerical methods at the level of FKA121 Computational Physics is recommended. It is an advantage to have some knowledge of quantum mechanics, condensed matter physics and/or statistical physics at the advanced undergraduate level.
Aim
The aim of the course is to outline modern computational methods and schemes providing challenges for the future and to develop practical experience in carrying out high performance computing. The course introduces numerical methods and new areas of physics that can be studied with these methods. It gives examples of how physics can be applied in a much broader context than usually discussed in the traditional physics undergraduate curriculum and it teaches structured programming in the context of doing science.
Learning outcomes (after completion of the course the student should be able to)
use the objected-oriented scripting language Python to steer and organize large scale computing tasks and to provide simple visualization.
efficiently use MATLAB, Python and/or C/Fortran to solve numerical problems.
know some of the major open-source implementations of molecular dynamics (MD) simulations and the density functional theory (DFT) for the electronic structure problem.
comprehend and apply the MD simulation technique.
synthesize DFT concepts through experience in writing codes for simple systems.
comprehend and analyze DFT methods and concepts.
integrate knowledge in modeling physical systems with various numerical techniques.
write technical reports where computational results are presented and explained.
communicate results and conclusions in a clear way.
Content
introductory Python
the molecular dynamics simulation technique for many-particle systems
simplified tight-binding methods and model potentials
basics of density functional theory for the electronic structure problem
plane-wave and localized orbitals basis set methods
steering and combining results from various programming codes
Organisation
Basic theory and methods are covered by a series of lectures. The students get training by applying the theory and methods in exercises and homework problems. An important part consists of practical training of carrying out large scale computations using primarily preexisting molecular dynamics and/or electronic structure codes. This training includes also experience of using Python, an object-oriented scripting languages, as a common platform to steer and analyze and combine results from various codes.
Literature
Lecture notes will be made available.
Course book:
J.M.Thijssen,
"Computational Physics",
(2nd edition, Cambridge University Press, 2007).
Recommended additional material for numerical methods:
Willliam H. Press et al.,
"Numerical Recipes; The Art of Scientific Computing",
(3rd edition, Cambridge University Press, 2007),
Examination
The examination will be individualized and adjusted to previous background and interests. In general the examination consists of coding assignments (graded), computing-lab assignments (pass or fail), and more individualized projects with a report and a presentation (graded).