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FSF3564 Mathematical and Computational Methods from Micro to Macro Scales 7.5 credits

Information per course offering

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Course syllabus as PDF

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Course syllabus FSF3564 (Spring 2019–)
Headings with content from the Course syllabus FSF3564 (Spring 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

The Schrödinger equation, which accurately models nuclei-electron system without unknown parameters, is the basis for condensed matter physics and computational chemistry. An important issue is its high computational complexity, e.g. already for a water molecule it means to solve a partial differential equation in 39 dimensions. Computational approximations are therefore needed and the goal of the course is to present, use and understand numerical methods for the important coarse-grained approximations.

The complexity is reduced by classical approximation of the nuclei, using Born-Oppenheimer dynamics. To computationally solve the quantum problem for the electrons the Hartree-Fock and Kohn-Sham density functional theory is important and leads to an ab initio molecular dynamics model. The ab initio molecular dynamics can be simplified by empirical potentials. Thermal fluctuations in an ensemble at constant temperature introduces stochastics into the dynamics which leads to the Langevin molecular dynamics, or variants thereof. On long time scales and  in the high friction limit this dynamics can be described without the velocities by the Smoluchowski equation. The next step in the coarse-graining process is to derive partial differential equations for the mass, momentum and energy of a continuum fluid, which determines the otherwise unspecified stress tensor and heat flux.

Intended learning outcomes

Students will be able to use, relate and critically evaluate analytical and numerical approximations on different scales.

Literature and preparations

Specific prerequisites

A Master degree including at least 30 university credits (hp) in in Mathematics (including differential equations and numerical analysis).

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

Cances E., Defranceschi M., Kutzelnigg W., LeBris C., Maday Y., Computational Chemistry: a primer, n Handbook of Numerical Analysis, X, North-Holland 2003. some pages. 
Elliott H. Lieb and Robert Seiringer, The Stability of Matter in Quantum mechanics, Cambridge University Press 2010, chapter 2 and 3. 
E Weinan, Principles of Multiscale Modeling, Cambridge University Press 2011.

Examination and completion

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

Grading scale

G

Examination

  • INL1 - Assignment, 7.5 credits, grading scale: P, F

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.

Homework problems

Computer assignments

Written exam

Other requirements for final grade

Homework and computer assignments completed
Written exam passed

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

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 room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

No information inserted

Contact

Anders Szepessy (szepessy@kth.se)

Postgraduate course

Postgraduate courses at SCI/Mathematics