Algorithms for Scientific Computing II

What it is about

You engage with advanced numerical methods and their application in scientific computing. Depending on the lecture focus, you learn e.g. efficient procedures for sparsely populated matrices, numerical techniques for quantum systems, or methods such as molecular dynamics, sparse grids and algebraic multigrid. In the end you can apply suitable methods to demanding application problems and explain and utilize their hierarchical aspects.

What you will be able to do

• Adapt numerical methods to demanding applications
• Understand advanced problems and methods of scientific computing
• Explain and apply the hierarchical aspects of algorithms
• Familiarity with specific topics depending on the lecture (Sparse Matrices / Quantum Computing / MD, Sparse Grids, AMG)

What the module consists of

• VorlesungConveying content through lectures and presentations
• Übung/TutorialSolving concrete problems, sometimes in teamwork; deepening and examples

Teaching method

• Vorträge/PräsentationenIntroduction and explanation of the topics
• Selbststudium LiteraturDeepening and independent engagement with the content
• Übungen/TeamarbeitApplying the methods to concrete problems and discussion of examples