Computational Physics 1, Lectures

The students will gain basic knowledge in computational physics, which will enable them to manage research projects on more specific themes. In general, the students will learn to

• perform numerical work independently as well as in a team
• analyze general results critically
• visualize and present data appropriately
• obtain and improve their knowledge on information and communication technology
• think creatively and see alternative ways for problem solving and presenting results
• organize and conduct own small projects

Core content

• Setting up your numerical experiment, i.e., "Good Enough Practices in Scientific Computing"
• Linux basics
• Data visualization
• Numerical calculus and linear algebra
• Numerical solution of ordinary and partial differential equations
  

Complementary knowledge

• "Best Practices for Scientific Computing"
• Perceptually uniform colormaps
• Multi-dimensional calculus
• Relation to computational physics
• Basics of related numerical framework
  

Specialist knowledge

• Archiving and publishing your numerical experiments
• Publication-quality figures (filetypes, typography, and graphic design elements)
• Advanced methods (Monte Carlo integration, FFT-based differentiation and analysis)
• How to select and implement algorithms
• Usage, implementation and development

Recommended Prerequisites

• Programming 1: Introduction, TIE-02107, 5 cr

Lecture and excercise notes. Thus, no need to purchase text books.

However, find below some supplementary material that you might find useful and interesting.

Material

• Type: Research
• Name: Best Practices for Scientific Computing
• Author: G. Wilson et al.
• Exam material: No
• URL: https://doi.org/10.1371/journal.pbio.1001745
• Language: English

Material

•    Type: Research
• Name: Good enough practices in scientific computing
• Author: G. Wilson et al.
• Exam material: No
• URL: https://doi.org/10.1371/journal.pcbi.1005510
• Language: English

Material

•    Type: Book
• Name: Computational Physics: Problem Solving with Python
• Author: R. H. Landau et al.
• Exam material: No
• ISBN: 978-3-527-41315-7
• URL: https://ebookcentral.proquest.com/lib/tut/detail.action?docID=4042562
• Language: English

Material

•    Type: Book
• Name: Numerical Recipes 3rd Edition: The Art of Scientific Computing
• Author: W. H. Press et al.
• Exam material: No
• ISBN: 978-0-521-88068-8
• URL: http://www.cambridge.org/fi/academic/subjects/mathematics/numerical-recipes/numerical-recipes-art-scientific-computing-3rd-edition
• Language: English

Material

•    Type: Book
• Name: Effective Computation in Physics. Field Guide to Research with Python
• Author: A. Scopatz and K. D. Huff
• Exam material: No
• ISBN: 978-1-491-90153-3
• URL: http://shop.oreilly.com/product/0636920033424.do
• Language: English

General scale, 0-5