NDAA07012U Scientific Computing
Volume 2013/2014
Education
MSc Programme in
Physics
Content
This course focuses on
the general techniques and ideas found in professionally written
numerical software, as well as the general concepts one needs to
know for applying suitable software in a qualified manner to
computational problems. Thus, the course is aimed much more at
potential users of mathematical software than at potential creators
of such software.
Learning Outcome
The methods presented in the course enable the student to perform numerical analysis of simple mathematical models from science in order to solve concrete problems and to evaluate the results obtained. The solution will mainly be based on Matlab or similar systems.
Skills
At
course completion, the student should be able to:
- Choose an appropriate numerical method for the solution of the problem or sub-problem. The numerical method is selected among the methods presented in the course and it should be chosen with respect to the requirements of the model.
- Evaluate the numerical method with respect to potential accuracy, computational efficiency, robustness and memory requirements.
- Perform the required computation using Matlab or similar systems.
- Evaluate the quality of the solution with respect to the accuracy obtained and the sensitivity to model parameter variations.
- Estimate whether the quality of the solution is adequate relative to the desired use of the model.
- Analyse the reasons of a possible total failure of a method applied to a concrete problem.
The methods presented in the course enable the student to perform numerical analysis of simple mathematical models from science in order to solve concrete problems and to evaluate the results obtained. The solution will mainly be based on Matlab or similar systems.
Knowledge
Presentation and numerical analysis of simple mathematical models
from science. Presentation of ideas behind and motivation for
fundamental numerical methods for the solution of: linear and
nonlinear equations, linear and nonlinear optimization, eigenvalue
problems, initial value problems for ordinary differential
equations, partial differential equations and the fast Fourier
transform.
Literature
Michael T. Heath: Scientific
computing. An introductory survey, 2nd ed. from
McGraw-Hill.
Academic qualifications
Corresponding to the
courses MatIntro and LinAlg. Programming ability is also required .
Further more ability corresponding to at least one of the following
prerequisites: An1, MatF, 1st year computer science.
Teaching and learning methods
Lectures, exercises and 4
small projects. Duration 9 weeks.
Remarks
It is expected that the
student brings a laptop
Necessary software:
Windows: Xming
Xming:http://sourceforge.net/projects/xming/ & http://www.straightrunning.com/XmingNotes/
For support please contact SCIENCE IT, e-mail: it-support@science.ku.dk, 35 32 21 00
Linux:X11 runs automatically
MAC: For all systems since OS 10.5 you can use X11, which you can download for free at http://xquartz.macosforge.org/landing/.
X11 is a part of OS X in Leopard and Lion.
Necessary software:
Windows: Xming
Xming:http://sourceforge.net/projects/xming/ & http://www.straightrunning.com/XmingNotes/
For support please contact SCIENCE IT, e-mail: it-support@science.ku.dk, 35 32 21 00
Linux:X11 runs automatically
MAC: For all systems since OS 10.5 you can use X11, which you can download for free at http://xquartz.macosforge.org/landing/.
X11 is a part of OS X in Leopard and Lion.
Workload
- Category
- Hours
- Lectures
- 32
- Practical exercises
- 16
- Preparation
- 58
- Project work
- 100
- Total
- 206
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Continuous assessmentIndependent evaluation of 4 small projects. The final grade is the average of the grades of each of the 4 projects.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
More internal examiners
- Re-exam
- Same as ordinary exam. Only the not-approved reports have to be re-submitted
Criteria for exam assesment
See Skills.
Course information
- Language
- English
- Course code
- NDAA07012U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- A
- Course capacity
- No restriction to number of participants
- Continuing and further education
- Study board
- Study Board of Physics, Chemistry and Nanoscience
Contracting departments
- The Niels Bohr Institute
- Department of Chemistry
Course responsibles
- Stig Skelboe (skelboe@nbi.ku.dk)
Lecturers
Kurt Mikkelsen, e-mail: kmi@kemi.ku.dk, tlf.nr.: 3532 0251
Stephan P. A. Sauer, e-mail: sauer@kiku.dk, 3532 0268
Åke Nordlund, e-mail: aake@nbi.dk tlf.nr.: 3532 5968
Klaus Galsgaard, e-mail: kg@nbi.ku.dk, tlf.nr.: 3532 5894
Saved on the
13-12-2013