FYS-4096 Computational Physics, 5 cr
Lisätiedot
Suitable for postgraduate studies.
Vastuuhenkilö
Ilkka Kylänpää
Opetus
| Toteutuskerta | Periodi | Vastuuhenkilö | Suoritusvaatimukset |
| FYS-4096 2018-01 | 3 - 4 |
Ilkka Kylänpää |
No final exam. Weekly exercise assignments, two projects. |
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 supercomputers and superclusters. Vim. | |
| 3. | Data visualization 101 | Perceptually uniform colormaps | Publication-quality figures (filetypes, typography, and graphic design elements) |
| 4. | Numerical calculus | Multi-dimensional calculus | Advanced methods (FFT-based differentiation, Monte-Carlo integration) |
| 5. | Numerical solution of ordinary differential equations | Examples in classical mechanics | How to select the algorithms? |
| 6. | Numerical linear algebra 101 | Krylov subspace methods, Examples in time-independent and time-dependent quantum mechanics | Multi-dimensional linear algebra |
| 7. | Numerical solution of partial differential equations: finite difference and finite element methods | Examples in thermodynamics, electrostatics, electromagnetism, and/or time-dependent quantum mechanics | |
| 8. | Signal analysis 101 | Signal decomposition | Behind the noise |
| 9. | Machine learning 101 | 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)
Osasuoritukset:
Oppimateriaali
| Tyyppi | Nimi | Tekijä | ISBN | URL | Lisätiedot | Tenttimateriaali |
| Book | Computational Physics: Problem Solving with Python | R. H. Landau et al. | 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 | W. H. Press et al. | 978-0-521-88068-8 | No | ||
| Research | Best Practices for Scientific Computing | G. Wilson et al. | No | |||
| Research | Good enough practices in scientific computing | G. Wilson et al. | No |
Esitietovaatimukset
| Opintojakso | P/S | Selite |
| FYS-1466 Introduction to Quantum Mechanics | Advisable | 1 |
| FYS-1610 Kvanttimekaniikka I | Advisable | 1 |
| TIE-02107 Programming 1: Introduction | Mandatory | |
| TIE-02207 Programming 2: Basics | Mandatory |
1 . 1
Tietoa esitietovaatimuksista
You need basic programming skills to pass this course (but no formal education in programming is needed). Introductory linear algebra (/matrix calculus) and quantum mechanics will be useful.
Vastaavuudet
| Opintojakso | Vastaa opintojaksoa | Selite |
| FYS-4096 Computational Physics, 5 cr | FYS-4090 Computational Physics, 5 cr |