Search result: Catalogue data in Spring Semester 2021

Computational Science and Engineering Bachelor Information
Bachelor Studies (Programme Regulations 2018)
First Year Compulsory Courses
First Year Examination Block 2
NumberTitleTypeECTSHoursLecturers
401-0232-10LAnalysis 2 Information Restricted registration - show details O8 credits4V + 2UT. Rivière
AbstractIntroduction to differential calculus and integration in several variables.
ObjectiveEinführung in die Grundlagen der Analysis
ContentDifferentiation in several variables, maxima and minima,
the implicit function theorem, integration in several variables,
integration over submanifolds, the theorems of Gauss and Stokes.
Lecture notesChristian Blatter: Ingenieur-Analysis (Kapitel 4-6).
Konrad Koenigsberger, Analysis II.
401-0302-10LComplex Analysis Restricted registration - show details O4 credits3V + 1UA. Iozzi
AbstractBasics of complex analysis in theory and applications, in particular the global properties of analytic functions. Introduction to the integral transforms and description of some applications
ObjectiveErwerb von einigen grundlegenden Werkzeuge der komplexen Analysis.
ContentExamples of analytic functions, Cauchy‘s theorem, Taylor and Laurent series, singularities of analytic functions, residues. Fourier series and Fourier integral, Laplace transform.
LiteratureJ. Brown, R. Churchill: "Complex Analysis and Applications", McGraw-Hill 1995

T. Needham. Visual complex analysis. Clarendon Press, Oxford. 2004.

M. Ablowitz, A. Fokas: "Complex variables: introduction and applications", Cambridge Text in Applied Mathematics, Cambridge University Press 1997

E. Kreyszig: "Advanced Engineering Analysis", Wiley 1999

J. Marsden, M. Hoffman: "Basic complex analysis", W. H. Freeman 1999

P. P. G. Dyke: "An Introduction to Laplace Transforms and Fourier Series", Springer 2004

A. Oppenheim, A. Willsky: "Signals & Systems", Prentice Hall 1997

M. Spiegel: "Laplace Transforms", Schaum's Outlines, Mc Graw Hill
Prerequisites / NoticePrerequisites: Analysis I and II
402-0044-00LPhysics IIO4 credits3V + 1UT. Esslinger
AbstractIntroduction to the concepts and tools in physics with the help of demonstration experiments: electromagnetism, optics, introduction to modern physics.
ObjectiveThe concepts and tools in physics, as well as the methods of an experimental science are taught. The student should learn to identify, communicate and solve physical problems in his/her own field of science.
ContentElectromagnetism (electric current, magnetic fields, electromagnetic induction, magnetic materials, Maxwell's equations)
Optics (light, geometrical optics, interference and diffraction)
Short introduction to quantum physics
Lecture notesThe lecture follows the book "Physik" by Paul A. Tipler.
LiteraturePaul A. Tipler and Gene Mosca
Physik
Springer Spektrum Verlag
529-4000-00LChemistryO4 credits3GE. C. Meister
AbstractIntroduction to chemistry with aspects of inorganic, organic and physical chemistry.
Objective- Understanding of simple models of chemical bonding and the three-dimensional molecular structure
- Quantitative description of selected chemical systems by means of reaction equations and equilibria
- Understanding of fundamental concepts of chemical kinetics (e.g. reaction order, rate law, rate constant)
ContentPeriodic system of the elements, chemical bonding (LCAO-MO), molecular structure (VSEPR), reactions, equilibria, chemical kinetics.
Lecture notesHandouts of lecture presentations and additional supporting information will be offered.
LiteratureC.E. Housecroft, E.C. Constable, Chemistry. An Introduction to Organic, Inorganic and Physical Chemistry, 4th ed., Pearson: Harlow 2010.
C.E. Mortimer, U. Müller, Chemie, 11. Auflage, Thieme: Stuttgart 2014.
252-0002-00LData Structures and Algorithms Information O8 credits4V + 2UF. Friedrich Wicker
AbstractThe course provides the foundations for the design and analysis of algorithms.
Classical problems ranging from sorting up to problems on graphs are used to discuss common data structures, algorithms and algorithm design paradigms.
The course also comprises an introduction to parallel and concurrent programming and the programming model of C++ is discussed in some depth.
ObjectiveAn understanding of the analysis and design of fundamental and common algorithms and data structures. Deeper insight into a modern programming model by means of the programming language C++. Knowledge regarding chances, problems and limits of parallel and concurrent programming.
ContentData structures and algorithms: mathematical tools for the analysis of algorithms (asymptotic function growth, recurrence equations, recurrence trees), informal proofs of algorithm correctness (invariants and code transformation), design paradigms for the development of algorithms (induction, divide-and-conquer, backtracking and dynamic programming), classical algorithmic problems (searching, selection and sorting), data structures for different purposes (linked lists, hash tables, balanced search trees, quad trees, heaps, union-find), further tools for runtime analysis (generating functions, amortized analysis. The relationship and tight coupling between algorithms and data structures is illustrated with graph algorithms (traversals, topological sort, closure, shortest paths, minimum spanning trees, max flow).

Programming model of C++: correct and efficient memory handling, generic programming with templates, exception handling, functional approaches with functors and lambda expressions.

Parallel programming: structure of parallel architectures (multicore, vectorization, pipelining) concepts of parallel programming (Amdahl's and Gustavson's laws, task/data parallelism, scheduling), problems of concurrency (data races, bad interleavings, memory reordering), process synchronisation and communication in a shared memory system (mutual exclusion, semaphores, monitors, condition variables), progress conditions (freedom from deadlock, starvation, lock- and wait-freedom). The concepts are underpinned with examples of concurrent and parallel programs and with parallel algorithms, implemented in C++.

In general, the concepts provided in the course are motivated and illustrated with practically relevant algorithms and applications.

Exercises are carried out in Code-Expert, an online IDE and exercise management system.

All required mathematical tools above high school level are covered, including a basic introduction to graph theory.
LiteratureCormen, Leiserson, Rivest, and Stein: Introduction to Algorithms, 3rd ed., MIT Press, 2009. ISBN 978-0-262-03384-8 (recommended text)

Maurice Herlihy, Nir Shavit, The Art of Multiprocessor Programming, Elsevier, 2012.

B. Stroustrup, The C++ Programming Language (4th Edition) Addison-Wesley, 2013.
Prerequisites / NoticePrerequisites:
Lecture Series 252-0835-00L Informatik I or equivalent knowledge in programming with C++.
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