Search result: Catalogue data in Spring Semester 2023
Computational Science and Engineering Bachelor  
First Year Compulsory Courses  
First Year Examination Block 1 Offered in the Autumn Semester  
First Year Examination Block 2  
Number  Title  Type  ECTS  Hours  Lecturers  

401023210L  Analysis 2  O  8 credits  4V + 2U  T. Rivière  
Abstract  Introduction to differential calculus and integration in several variables.  
Learning objective  Einführung in die Grundlagen der Analysis  
Content  Differentiation in several variables, maxima and minima, the implicit function theorem, integration in several variables, integration over submanifolds, the theorems of Gauss and Stokes.  
Lecture notes  Christian Blatter: IngenieurAnalysis (Kapitel 46). Konrad Koenigsberger, Analysis II.  
401030210L  Complex Analysis  O  4 credits  3V + 1U  F. Da Lio  
Abstract  Basics 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  
Learning objective  Erwerb von einigen grundlegenden Werkzeuge der komplexen Analysis.  
Content  Examples of analytic functions, Cauchy‘s theorem, Taylor and Laurent series, singularities of analytic functions, residues. Fourier series and Fourier integral, Laplace transform.  
Literature  J. Brown, R. Churchill: "Complex Analysis and Applications", McGrawHill 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 / Notice  Prerequisites: Analysis I and II  
402004400L  Physics II  O  4 credits  3V + 1U  S. P. Quanz  
Abstract  Introduction to the concepts and tools in physics with the help of demonstration experiments: electromagnetism, optics, introduction to modern physics.  
Learning objective  The 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.  
Content  Electromagnetism (electric current, magnetic fields, electromagnetic induction, magnetic materials, Maxwell's equations) Optics (light, geometrical optics, interference and diffraction) Short introduction to quantum physics  
Lecture notes  The lecture follows the book "Physik" by Paul A. Tipler.  
Literature  Paul A. Tipler and Gene Mosca Physik Springer Spektrum Verlag  
529400000L  Chemistry  O  4 credits  3G  E. C. Meister  
Abstract  Introduction to chemistry with aspects of inorganic, organic and physical chemistry.  
Learning objective   Understanding of simple models of chemical bonding and the threedimensional 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)  
Content  Periodic system of the elements, chemical bonding (LCAOMO), molecular structure (VSEPR), reactions, equilibria, chemical kinetics.  
Lecture notes  Handouts of lecture presentations and additional supporting information will be offered.  
Literature  C.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.  
252000200L  Data Structures and Algorithms  O  8 credits  4V + 2U  M. Fischer, F. Friedrich Wicker  
Abstract  The course provides the foundations for the design and analysis of algorithms. Classic 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.  
Learning objective  An 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.  
Content  Data 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, divideandconquer, sweepline method, 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, unionfind), further tools for runtime analysis (e.g. amortized analysis). The relationship and tight coupling between algorithms and data structures is illustrated with geometric problems (convex hull, line intersections, closest point pairs) graph algorithms (traversals, topological sort, transitive closure, shortest paths, minimum spanning trees, max flow). Programming model of C++: correct and efficient memory handling, generic programming with templates, functional approaches with functors and lambda expressions. Parallel programming: 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). The concepts provided in the course are motivated and illustrated with practically relevant algorithms and applications. Exercises are carried out in CodeExpert, an online IDE and exercise management system. All required mathematical tools above high school level are covered, including a basic introduction to graph theory.  
Literature  (available from the course website)  
Prerequisites / Notice  Prerequisites: Lecture Series 252083500L Informatik I or equivalent knowledge in programming with C++.  
Competencies 

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