Course syllabus for Computational materials and molecular physics

Course syllabus adopted 2021-02-26 by Head of Programme (or corresponding).

Overview

  • Swedish nameBeräkningsmetoder för material- och molekylfysik
  • CodeTIF320
  • Credits7.5 Credits
  • OwnerMPPHS
  • Education cycleSecond-cycle
  • Main field of studyEngineering Physics
  • DepartmentPHYSICS
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

  • Teaching language English
  • Application code 85114
  • Block schedule
  • Open for exchange studentsYes

Credit distribution

0119 Project 7.5 c
Grading: TH		0 c0 c7.5 c0 c0 c0 c

In programmes

Examiner

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Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

Basic undergraduate physics and mathematics, computing and numerical analysis. Computing and numerical methods at the level of the courses Learning from Data and 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)

- Comprehend and analyze different electronic structure methods, such as Hartree-Fock and Density Functional Theory - Comprehend and apply MD simulation and Monte-Carlo technique to investigate material properties with the help of computers - Use the objected-oriented scripting language Python to solve numerical problems and to steer and organize large scale computing tasks and to provide simple visualization - Write technical reports where computational results are presented and explained - Communicate results and conclusions in a clear way.

Content

- Basics of Hartree-Fock and Density Functional Theory for the electronic structure problem - Molecular dynamics and Monte-Carlo simulation technique for many-particle systems - Python and in particular modular programing in Python

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 including compulsory elements

The examination can be adjusted to previous background and interests. In general the examination consists of coding assignments, computing-lab assignments, theory assignments and more individualized projects with a report and a presentation. All examination parts will be graded.

The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.