FYS-4096 Computational Physics, 5 cr
Lisätiedot
Suitable for postgraduate studies.
Vastuuhenkilö
Janne Solanpää, Esa Räsänen
Opetus
| Toteutuskerta | Periodi | Vastuuhenkilö | Suoritusvaatimukset |
| FYS-4096 2017-01 | 3 - 4 |
Esa Räsänen Janne Solanpää |
No final exam. Weekly exercise assignments, two project works. |
Osaamistavoitteet
The students will gain basic knowledge in computational physics which will enable them to continue research projects on more specific themes. The students have to be able to perform numerical work independently, analyse the results critically, and visualise them in an appropriate manner.
Sisältö
| Sisältö | Ydinsisältö | Täydentävä tietämys | Erityistietämys |
| 1. | Setting up your numerical experiment a.k.a. "Good Enough Practices in Scientific Computing" | "Best Practices for Scientific Computing" | Archiving and publishing your numerical experiments |
| 2. | Linux basics | Working with remote servers | Working with supercomputers and computing clusters, Vim |
| 3. | Scientific visualization 101 | Perceptually uniform colormaps | Publication-quality figures |
| 4. | Numerical calculus | Multi-dimensional calculus | Advanced methods |
| 5. | Numerical solution of ordinary differential equations | Examples in classical mechanics | How to select the algorithms? |
| 6. | Numerical linear algebra | Multi-dimensional linear algebra, Preconditioning, Examples in time-independent quantum mechanics | Calculating matrix functions |
| 7. | Numerical solution of partial differential equations | Examples in thermodynamics, acoustics, electrostatics, and time-dependent quantum mechanics | Finite element method |
| 8. | Numerical solution of integral equations | Examples in time-dependent quantum mechanics and acoustics | Boundary element method |
| 9. | Correlations and spectral analysis | Signal decomposition | Behind the noise |
| 10. | Machine learning | Neural networks | Pitfalls and catastrophic failures |
Ohjeita opiskelijalle osaamisen tasojen saavuttamiseksi
The only way to learn the topics of the course is to do the (compulsory) weekly exercises.
Arvosteluasteikko:
Numerical evaluation scale (0-5)
Oppimateriaali
| Tyyppi | Nimi | Tekijä | ISBN | URL | Lisätiedot | Tenttimateriaali |
| Book | Computational Physics: Problem Solving with Python | Rubin H. Landau, Manuel J Páez, and Cristian C. Bordeianu | 978-3-527-41315-7 | No | ||
| Book | Effective Computation in Physics. Field Guide to Research with Python | A. Scopatz and K. D. Huff | 978-1-491-90153-3 | No | ||
| Book | Numerical Recipes 3rd Edition: The Art of Scientific Computing | William H. Press, Saul A. Teukolsky, William T. Vetterlin, and Brian P. Flannery | 978-0-521-88068-8 | No |
Esitietovaatimukset
| Opintojakso | P/S | Selite |
| FYS-1466 Introduction to Quantum Mechanics | Advisable | 1 |
| FYS-1610 Kvanttimekaniikka I | Advisable | 1 |
| TIE-02106 Introduction to Programming | Advisable | |
| TIE-02206 Basic Course on Programming | Advisable |
1 . 1
Tietoa esitietovaatimuksista
You need basic programming skills to pass this course (but no formal education in programming is needed).
Vastaavuudet
| Opintojakso | Vastaa opintojaksoa | Selite |
| FYS-4096 Computational Physics, 5 cr | FYS-4090 Computational Physics, 5 cr |