Search result: Catalogue data in Spring Semester 2018
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 | |
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401-0232-10L | Analysis II | O | 8 credits | 4V + 2U | T. H. Willwacher | |
Abstract | Introduction to differential calculus and integration in several variables. | |||||
Objective | ||||||
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 | Konrad Koenigsberger, Analysis II. Christian Blatter: Ingenieur-Analysis (Kapitel 4-6). | |||||
401-0302-10L | Complex Analysis | O | 4 credits | 3V + 1U | P. S. Jossen | |
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 | |||||
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 | 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. Brown, R. Churchill: "Complex Analysis and Applications", McGraw-Hill 1995 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 Ch. Blatter: "Komplexe Analysis, Fourier- und Laplace-Transformation", Autographie 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 | |||||
402-0040-00L | Physics I | O | 5 credits | 4V + 2U | Y. M. Acremann, D. Pescia | |
Abstract | Part A: Introduction to mechanics, wave phenomena, Kelpler problem, rotational motion. Part B: electrostatics of metals and isolators, magnetostatics, Maxwell equations. | |||||
Objective | Fundamentals of mechanics, oscillations, waves, electrostatics and magnetostatics. | |||||
Content | Part A: Introduction to mechanics, wave phenomena, Kelpler problem, rotational motion. Part B: electrostatics of metals and isolators, magnetostatics, Maxwell equations. | |||||
Lecture notes | A copy of the blackboard is made available online. | |||||
Literature | (Fakultativ): Teil A: W. Nolting, "Klassische Mechanik", Springer Verlag, Berlin, 2011. Teil B: W. Nolting, "Elektrodynamik", Springer Verlag, Berlin, 2011 | |||||
529-4000-00L | Chemistry | O | 4 credits | 3G | E. C. Meister | |
Abstract | Introduction 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) | |||||
Content | Chemical bonding (LCAO-MO) and molecular structure (VSEPR), reactions, equilibria, electrochemistry, 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. | |||||
252-0002-00L | Data Structures and Algorithms | O | 7 credits | 4V + 2U | F. Friedrich Wicker | |
Abstract | This course is about fundamental algorithm design paradigms (such as induction, divide-and-conquer, backtracking, dynamic programming), classic algorithmic problems (such as sorting and searching), and data structures (such as lists, hashing, search trees). Moreover, an introduction to parallel programming is provided. The programming model of C++ will be discussed in some depth. | |||||
Objective | An understanding of the design and analysis of fundamental algorithms and data structures. Knowledge regarding chances, problems and limits of parallel and concurrent programming. Deeper insight into a modern programming model by means of the programming language C++. | |||||
Content | Fundamental algorithms and data structures are presented and analyzed. Firstly, this comprises design paradigms for the development of algorithms such as induction, divide-and-conquer, backtracking and dynamic programming and classical algorithmic problems such as searching and sorting. Secondly, data structures for different purposes are presented, such as linked lists, hash tables, balanced search trees, heaps and union-find structures. The relationship and tight coupling between algorithms and data structures is illustrated with geometric problems and graph algorithms. In the part about parallel programming, parallel architectures are discussed conceptually (multicore, vectorization, pipelining). Parallel programming concepts are presented (Amdahl's and Gustavson's laws, task/data parallelism, scheduling). Problems of concurrency are analyzed (Data races, bad interleavings, memory reordering). Process synchronisation and communication in a shared memory system is explained (mutual exclusion, semaphores, monitors, condition variables). Progress conditions are analysed (freedom from deadlock, starvation, lock- and wait-freedom). The concepts are underpinned with examples of concurrent and parallel programs and with parallel algorithms. The programming model of C++ is discussed in some depth. The RAII (Resource Allocation is Initialization) principle will be explained. Exception handling, functors and lambda expression and generic prorgamming with templates are further examples of this part. The implementation of parallel and concurrent algorithm with C++ is also part of the exercises (e.g. threads, tasks, mutexes, condition variables, promises and futures). | |||||
Literature | Cormen, 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 / Notice | Prerequisites: Lecture Series 252-0835-00L Informatik I or equivalent knowledge in programming with C++. | |||||
Basic Courses | ||||||
Block G1 All course units within Block G1 are offered in the autumn semester. | ||||||
Block G2 All course units within Block G2 are offered in the autumn semester. | ||||||
Block G3 227-0014-10L Operating Systems and Networks replaces 227-0014-00L Computer Engineering II, with exercises on Friday afternoon. | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
401-0674-00L | Numerical Methods for Partial Differential Equations Not meant for BSc/MSc students of mathematics. | O | 8 credits | 4V + 2U + 1A | R. Hiptmair | |
Abstract | Derivation, properties, and implementation of fundamental numerical methods for a few key partial differential equations: convection-diffusion, heat equation, wave equation, conservation laws. Implementation in C++ based on a finite element library. | |||||
Objective | Main skills to be acquired in this course: * Ability to implement advanced numerical methods for the solution of partial differential equations efficiently. * Ability to modify and adapt numerical algorithms guided by awareness of their mathematical foundations. * Ability to select and assess numerical methods in light of the predictions of theory * Ability to identify features of a PDE (= partial differential equation) based model that are relevant for the selection and performance of a numerical algorithm. * Ability to understand research publications on theoretical and practical aspects of numerical methods for partial differential equations. * Skills in the efficient implementation of finite element methods on unstructured meshes. This course is neither a course on the mathematical foundations and numerical analysis of methods nor an course that merely teaches recipes and how to apply software packages. | |||||
Content | 1 Case Study: A Two-point Boundary Value Problem 1.1 Introduction 1.2 A model problem 1.3 Variational approach 1.4 Simplified model 1.5 Discretization 1.5.1 Galerkin discretization 1.5.2 Collocation [optional] 1.5.3 Finite differences 1.6 Convergence 2 Second-order Scalar Elliptic Boundary Value Problems 2.1 Equilibrium models 2.1.1 Taut membrane 2.1.2 Electrostatic fields 2.1.3 Quadratic minimization problems 2.2 Sobolev spaces 2.3 Variational formulations 2.4 Equilibrium models: Boundary value problems 3 Finite Element Methods (FEM) 3.1 Galerkin discretization 3.2 Case study: Triangular linear FEM in two dimensions 3.3 Building blocks of general FEM 3.4 Lagrangian FEM 3.4.1 Simplicial Lagrangian FEM 3.4.2 Tensor-product Lagrangian FEM 3.5 Implementation of FEM in C++ 3.5.1 Mesh file format (Gmsh) 3.5.2 Mesh data structures (DUNE) 3.5.3 Assembly 3.5.4 Local computations and quadrature 3.5.5 Incorporation of essential boundary conditions 3.6 Parametric finite elements 3.6.1 Affine equivalence 3.6.2 Example: Quadrilaterial Lagrangian finite elements 3.6.3 Transformation techniques 3.6.4 Boundary approximation 3.7 Linearization [optional] 4 Finite Differences (FD) and Finite Volume Methods (FV) [optional] 4.1 Finite differences 4.2 Finite volume methods (FVM) 5 Convergence and Accuracy 5.1 Galerkin error estimates 5.2 Empirical Convergence of FEM 5.3 Finite element error estimates 5.4 Elliptic regularity theory 5.5 Variational crimes 5.6 Duality techniques [optional] 5.7 Discrete maximum principle [optional] 6 2nd-Order Linear Evolution Problems 6.1 Parabolic initial-boundary value problems 6.1.1 Heat equation 6.1.2 Spatial variational formulation 6.1.3 Method of lines 6.1.4 Timestepping 6.1.5 Convergence 6.2 Wave equations [optional] 6.2.1 Vibrating membrane 6.2.2 Wave propagation 6.2.3 Method of lines 6.2.4 Timestepping 6.2.5 CFL-condition 7 Convection-Diffusion Problems 7.1 Heat conduction in a fluid 7.1.1 Modelling fluid flow 7.1.2 Heat convection and diffusion 7.1.3 Incompressible fluids 7.1.4 Transient heat conduction 7.2 Stationary convection-diffusion problems 7.2.1 Singular perturbation 7.2.2 Upwinding 7.3 Transient convection-diffusion BVP 7.3.1 Method of lines 7.3.2 Transport equation 7.3.3 Lagrangian split-step method 7.3.4 Semi-Lagrangian method 8 Numerical Methods for Conservation Laws 8.1 Conservation laws: Examples 8.2 Scalar conservation laws in 1D 8.3 Conservative finite volume discretization 8.3.1 Semi-discrete conservation form 8.3.2 Discrete conservation property 8.3.3 Numerical flux functions 8.3.4 Montone schemes 8.4 Timestepping 8.4.1 Linear stability 8.4.2 CFL-condition 8.4.3 Convergence 8.5 Higher order conservative schemes [optional] 8.5.1 Slope limiting 8.5.2 MUSCL scheme 8.6. FV-schemes for systems of conservation laws [optional] | |||||
Lecture notes | Lecture documents and classroom notes will be made available to the audience as PDF. | |||||
Literature | Chapters of the following books provide supplementary reading (detailed references in course material): * D. Braess: Finite Elemente, Theorie, schnelle Löser und Anwendungen in der Elastizitätstheorie, Springer 2007 (available online). * S. Brenner and R. Scott. Mathematical theory of finite element methods, Springer 2008 (available online). * A. Ern and J.-L. Guermond. Theory and Practice of Finite Elements, volume 159 of Applied Mathematical Sciences. Springer, New York, 2004. * Ch. Großmann and H.-G. Roos: Numerical Treatment of Partial Differential Equations, Springer 2007. * W. Hackbusch. Elliptic Differential Equations. Theory and Numerical Treatment, volume 18 of Springer Series in Computational Mathematics. Springer, Berlin, 1992. * P. Knabner and L. Angermann. Numerical Methods for Elliptic and Parabolic Partial Differential Equations, volume 44 of Texts in Applied Mathematics. Springer, Heidelberg, 2003. * S. Larsson and V. Thomée. Partial Differential Equations with Numerical Methods, volume 45 of Texts in Applied Mathematics. Springer, Heidelberg, 2003. * R. LeVeque. Finite Volume Methods for Hyperbolic Problems. Cambridge Texts in Applied Mathematics. Cambridge University Press, Cambridge, UK, 2002. However, study of supplementary literature is not important for for following the course. | |||||
Prerequisites / Notice | Mastery of basic calculus and linear algebra is taken for granted. Familiarity with fundamental numerical methods (solution methods for linear systems of equations, interpolation, approximation, numerical quadrature, numerical integration of ODEs) is essential. Important: Coding skills and experience in C++ are essential. Homework assignments involve substantial coding, partly based on a C++ finite element library. The written examination will be computer based and will comprise coding tasks. | |||||
529-0431-00L | Physical Chemistry III: Molecular Quantum Mechanics | O | 4 credits | 4G | B. H. Meier, M. Ernst | |
Abstract | Postulates of quantum mechanics, operator algebra, Schrödinger's equation, state functions and expectation values, matrix representation of operators, particle in a box, tunneling, harmonic oscillator, molecular vibrations, angular momentum and spin, generalised Pauli principle, perturbation theory, electronic structure of atoms and molecules, Born-Oppenheimer approximation. | |||||
Objective | This is an introductory course in quantum mechanics. The course starts with an overview of the fundamental concepts of quantum mechanics and introduces the mathematical formalism. The postulates and theorems of quantum mechanics are discussed in the context of experimental and numerical determination of physical quantities. The course develops the tools necessary for the understanding and calculation of elementary quantum phenomena in atoms and molecules. | |||||
Content | Postulates and theorems of quantum mechanics: operator algebra, Schrödinger's equation, state functions and expectation values. Linear motions: free particles, particle in a box, quantum mechanical tunneling, the harmonic oscillator and molecular vibrations. Angular momentum: electronic spin and orbital motion, molecular rotations. Electronic structure of atoms and molecules: the Pauli principle, angular momentum coupling, the Born-Oppenheimer approximation. Variational principle and perturbation theory. Discussion of bigger systems (solids, nano-structures). | |||||
Lecture notes | A script written in German will be distributed. The script is, however, no replacement for personal notes during the lecture and does not cover all aspects discussed. | |||||
227-0014-10L | Operating Systems & Networks Only for Computational Science and Engineering BSc. | O | 4 credits | 2V + 2U | R. Wattenhofer | |
Abstract | We learn the important functions of operating systems. Networking: IP, routing, transport, flows, applications, sockets, link and physical layer, Markov chains, PageRank, security. Storage: memory hierarchy, file systems, caching, hashing, data bases. Computation: virtualization, processes, threads, concurrency, scheduling, locking, synchronization, mutual exclusion, deadlocks, consistency. | |||||
Objective | see above | |||||
Content | Computers come in all shapes and sizes: servers, laptops, tablets, smartphones, smartwatches, all the way down to that tiny microcontroller in a washing machine. People buy a computer because (i) it gives them access to the Internet, (ii) it provides storage, and probably also because (iii) it computes. While having network access seems to be vital, advanced storage and computing capabilities more and more move to designated servers ("the cloud"). In this lecture, we learn how computers provide networking, storage, and computation by means of an operating system. We start out with networking, and discuss the internet protocol, addressing, routing, transport layer protocols, flows, some representative application layer protocols, and how to implement these with sockets. We also discuss the link and physical layer, Markov chains and PageRank, and selected topics in security. Regarding storage, we talk about the memory hierarchy, file systems, caching, efficient data structures such as hashing, and data base principles. Concerning computation, we discuss the virtualization of the processing units with processes and threads. We focus on concurrency and examine scheduling, locking, synchronization, mutual exclusion, deadlocks, and consistency. The lecture will use various teaching paradigms. The majority of the lecture will be based on blackboard discussions, supported by a script. Where appropriate we will also use slides or demonstrations. A few lectures will be flipped classroom style. The lecture will feature weekly paper exercises. However, some of the course material is best learned in front of an actual computer. In addition to the lecture we offer exciting hands-on exercises in a lab environment. | |||||
Lecture notes | Available | |||||
Block G4 Students that enrol for the second year in the CSE Bachelor Programme and whose first year examination did not involve the subject "Physics I" will instead of "Physics II" (402-0034-10L) take the "Physics I and II" (402-0043-00L and 402-0044-00L) courses with performance assessment as a yearly course. As of FS 2018 the course unit 151-0122-00L Fluid Dynamics for CSE gets replaced in Block G4 by 151-0102-00L Fluid Dynamics I. | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
402-0034-10L | Physics II | W | 4 credits | 2V + 2U | C. Degen | |
Abstract | This is a two-semester course introducing students into the foundations of Modern Physics. Topics include electricity and magnetism, light, waves, quantum physics, solid state physics, and semiconductors. Selected topics with important applications in industry will also be considered. | |||||
Objective | The lecture is intended to promote critical, scientific thinking. Key concepts of Physics will be acquired, with a focus on technically relevant applications. At the end of the two semesters, students will have a good overview over the topics of classical and modern Physics. | |||||
Content | Introduction into Quantum Physics, Absorption and Emission of Electromagnetic Radiation, Basics of Solid State Physics, Semiconductors | |||||
Lecture notes | Lecture notes will be available in German. | |||||
Literature | Paul A. Tipler, Gene Mosca, Michael Basler und Renate Dohmen Physik: für Wissenschaftler und Ingenieure Spektrum Akademischer Verlag, 2009, 1636 Seiten, ca. 80 Euro. Paul A. Tipler, Ralph A. Llewellyn Moderne Physik Oldenbourg Wissenschaftsverlag, 2009, 982 Seiten, ca. 75 Euro. | |||||
Prerequisites / Notice | No testat requirements for this lecture. | |||||
402-0044-00L | Physics II | W | 4 credits | 3V | T. Esslinger | |
Abstract | Introduction to the concepts and tools in physics with the help of demonstration experiments: electromagnetism, optics, introduction to modern physics. | |||||
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 | |||||
151-0102-00L | Fluid Dynamics I | O | 6 credits | 4V + 2U | T. Rösgen | |
Abstract | An introduction to the physical and mathematical foundations of fluid dynamics is given. Topics include dimensional analysis, integral and differential conservation laws, inviscid and viscous flows, Navier-Stokes equations, boundary layers, turbulent pipe flow. Elementary solutions and examples are presented. | |||||
Objective | An introduction to the physical and mathematical principles of fluid dynamics. Fundamental terminology/principles and their application to simple problems. | |||||
Content | Phenomena, applications, foundations dimensional analysis and similitude; kinematic description; conservation laws (mass, momentum, energy), integral and differential formulation; inviscid flows: Euler equations, stream filament theory, Bernoulli equation; viscous flows: Navier-Stokes equations; boundary layers; turbulence | |||||
Lecture notes | Lecture notes (extended formulary) for the course are made available electronically. | |||||
Literature | Recommended book: Fluid Mechanics, Kundu & Cohen & Dowling, 6th ed., Academic Press / Elsevier (2015). | |||||
Prerequisites / Notice | Leistungskontrolle: Sessionsprüfung (schriftlich), Dauer 2 Stunden Erlaubte Hilfsmittel: Lehrbuch (freie Auswahl), IFD Skript, 8 Seiten (=4 Blätter) eigene Notizen, Taschenrechner (nicht internetfähig, nicht vernetzt, leerer Speicher). Aufgabensammlungen (gedruckt oder handschriftlich) sind nicht erlaubt. Voraussetzungen: Physik, Analysis | |||||
529-0483-00L | Statistical Physics and Computer Simulation | O | 4 credits | 2V + 1U | M. Reiher | |
Abstract | Principles and applications of statistical mechanics and equilibrium molecular dynamics, Monte Carlo simulation, Stochastic dynamics. Exercises using a MD simulation program to generate ensembles and subsequently calculate ensemble averages. | |||||
Objective | Introduction to statistical mechanics with the aid of computer simulation, development of skills to carry out statistical mechanical calculations using computers and interpret the results. | |||||
Content | Principles and applications of statistical mechanics and equilibrium molecular dynamics, Monte Carlo simulation, Stochastic dynamics. Exercises using a MD simulation program to generate ensembles and subsequently calculate ensemble averages. | |||||
Literature | will be announced in the lecture | |||||
Prerequisites / Notice | Since the exercises on the computer do convey and test essentially different skills as those being conveyed during the lectures and tested at the oral exam, the results of a small programming project will be presented in a 10-minutes talk by Pairs of students who had been working on the project. Additional information will be provided in the first lecture. | |||||
Core Courses | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
151-0116-00L | High Performance Computing for Science and Engineering (HPCSE) for CSE | O | 7 credits | 4G + 2P | P. Koumoutsakos, P. Chatzidoukas | |
Abstract | This course focuses on programming methods and tools for parallel computing on multi and many-core architectures. Emphasis will be placed on practical and computational aspects of Bayesian Uncertainty Quantification and Machine Learning including the implementation of these algorithms on HPC architectures. | |||||
Objective | The course will teach - programming models and tools for multi and many-core architectures - fundamental concepts of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences. - fundamentals of Deep Learning | |||||
Content | High Performance Computing: - Advanced topics in shared-memory programming - Advanced topics in MPI - GPU architectures and CUDA programming Uncertainty Quantification: - Uncertainty quantification under parametric and non-parametric modeling uncertainty - Bayesian inference with model class assessment - Markov Chain Monte Carlo simulation Machine Learning - Deep Neural Networks and Stochastic Gradient Descent - Deep Neural Networks for Data Compression (Autoencoders) - Recurrent Neural Networks | |||||
Lecture notes | Link Class notes, handouts | |||||
Literature | - Class notes - Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein - CUDA by example, J. Sanders and E. Kandrot - Data Analysis: A Bayesian Tutorial, Devinderjit Sivia - Machine Learning: A Bayesian and Optimization Perspective, S. Theodorides | |||||
Prerequisites / Notice | Attendance of HPCSE I | |||||
252-0232-00L | Software Design | O | 6 credits | 2V + 1U | D. Gruntz | |
Abstract | The course Software Design presents and discusses design patterns regularly used to solve problems in object oriented design and object oriented programming. The presented patterns are illustrated with examples from the Java libraries and are applied in a project. | |||||
Objective | The students - know the principles of object oriented programming and can apply these. - know the most important object oriented design patterns. - can apply design patterns to solve design problems. - discover in a given design the use of design patterns. | |||||
Content | This course makes an introduction to object oriented programming. As programming language Java is used. The focus of this course however is object oriented design, in particular design patterns. Design patterns are solutions to recurring design problems. The discussed patterns are illustrated with examples from the Java libraries and are applied in the context of a project. | |||||
Lecture notes | no script | |||||
Literature | - Gamma, Helm, Johnson, Vlissides; Design Patterns: Elements of Reusable Object-Oriented Software; Prentice Hall;ISBN 978-0201633610 - Freeman, Freeman, Sierra; Head First Design Patterns, Head First Design Patterns; O'Reilly; ISBN 978-0596007126 | |||||
Prerequisites / Notice | The course Software Design is designed for students in the computational sciences program, but is open to students of all programs. The precondition is, that participants have knowledge in structured programming (e.g. with C, C++, C# or Java). | |||||
Fields of Specialization | ||||||
Astrophysics | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
402-0394-00L | Theoretical Astrophysics and Cosmology UZH students are not allowed to register this course unit at ETH. They must book the corresponding module directly at UZH. | W | 10 credits | 4V + 2U | L. M. Mayer, J. Yoo | |
Abstract | This is the second of a two course series which starts with "General Relativity" and continues in the spring with "Theoretical Astrophysics and Cosmology", where the focus will be on applying general relativity to cosmology as well as developing the modern theory of structure formation in a cold dark matter Universe. | |||||
Objective | ||||||
Content | The course will cover the following topics: - Homogeneous cosmology - Thermal history of the universe, recombination, baryogenesis and nucleosynthesis - Dark matter and Dark Energy - Inflation - Perturbation theory: Relativistic and Newtonian - Model of structure formation and initial conditions from Inflation - Cosmic microwave background anisotropies - Spherical collapse and galaxy formation - Large scale structure and cosmological probes | |||||
Literature | Suggested textbooks: H.Mo, F. Van den Bosch, S. White: Galaxy Formation and Evolution S. Carroll: Space-Time and Geometry: An Introduction to General Relativity S. Dodelson: Modern Cosmology Secondary textbooks: S. Weinberg: Gravitation and Cosmology V. Mukhanov: Physical Foundations of Cosmology E. W. Kolb and M. S. Turner: The Early Universe N. Straumann: General relativity with applications to astrophysics A. Liddle and D. Lyth: Cosmological Inflation and Large Scale Structure | |||||
Prerequisites / Notice | Knowledge of General Relativity is recommended. | |||||
Physics of the Atmosphere | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
701-1216-00L | Numerical Modelling of Weather and Climate | W | 4 credits | 3G | C. Schär, U. Lohmann | |
Abstract | The guiding principle of this lecture is that students can understand how weather and climate models are formulated from the governing physical principles and how they are used for climate and weather prediction purposes. | |||||
Objective | The guiding principle of this lecture is that students can understand how weather and climate models are formulated from the governing physical principles and how they are used for climate and weather prediction purposes. | |||||
Content | The course provides an introduction into the following themes: numerical methods (finite differences and spectral methods); adiabatic formulation of atmospheric models (vertical coordinates, hydrostatic approximation); parameterization of physical processes (e.g. clouds, convection, boundary layer, radiation); atmospheric data assimilation and weather prediction; predictability (chaos-theory, ensemble methods); climate models (coupled atmospheric, oceanic and biogeochemical models); climate prediction. Hands-on experience with simple models will be acquired in the tutorials. | |||||
Lecture notes | Slides and lecture notes will be made available at Link | |||||
Literature | List of literature will be provided. | |||||
Prerequisites / Notice | Prerequisites: to follow this course, you need some basic background in atmospheric science, numerical methods (e.g., "Numerische Methoden in der Umweltphysik", 701-0461-00L) as well as experience in programming | |||||
Chemistry | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
529-0474-00L | Quantum Chemistry | W | 6 credits | 3G | M. Reiher, T. Weymuth | |
Abstract | Introduction into the basic concepts of electronic structure theory and into numerical methods of quantum chemistry. Exercise classes are designed to deepen the theory; practical case studies using quantum chemical software to provide a 'hands-on' expertise in applying these methods. | |||||
Objective | Nowadays, chemical research can be carried out in silico, an intellectual achievement for which Pople and Kohn have been awarded the Nobel prize of the year 1998. This lecture shows how that has been accomplished. It works out the many-particle theory of many-electron systems (atoms and molecules) and discusses its implementation into computer programs. A complete picture of quantum chemistry shall be provided that will allow students to carry out such calculations on molecules (for accompanying experimental work in the wet lab or as a basis for further study of the theory). | |||||
Content | Basic concepts of many-particle quantum mechanics. Derivation of the many-electron theory for atoms and molecules; starting with the harmonic approximation for the nuclear problem and with Hartree-Fock theory for the electronic problem to Moeller-Plesset perturbation theory and configuration interaction and to coupled cluster and multi-configurational approaches. Density functional theory. Case studies using quantum mechanical software. | |||||
Lecture notes | Hand outs will be provided for each lecture (they are supplemented by (computer) examples that continuously illustrate how the theory works). | |||||
Literature | Textbooks on Quantum Chemistry: F.L. Pilar, Elementary Quantum Chemistry, Dover Publications I.N. Levine, Quantum Chemistry, Prentice Hall Hartree-Fock in basis set representation: A. Szabo and N. Ostlund, Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory, McGraw-Hill Textbooks on Computational Chemistry: F. Jensen, Introduction to Computational Chemistry, John Wiley & Sons C.J. Cramer, Essentials of Computational Chemistry, John Wiley & Sons | |||||
Prerequisites / Notice | Basic knowledge in quantum mechanics (e.g. through course physical chemistry III - quantum mechanics) required | |||||
Fluid Dynamics | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
151-0208-00L | Computational Methods for Flow, Heat and Mass Transfer Problems | W | 4 credits | 2V + 2U | D. W. Meyer-Massetti | |
Abstract | Numerical methods for the solution of flow, heat and mass transfer problems are presented and practised by analytical and computer solutions for simple examples. Subjects: solution process, physical and mathematical models, basic equations, discretization methods, numerical solution of advection, diffusion and Poisson equations, turbulent flows. | |||||
Objective | Knowledge of and practical experience with important discretisation and solution methods for computational fluid dynamics and heat and mass transfer problems | |||||
Content | Aufbauend auf den Lehrveranstaltungen über Fluiddynamik, Thermodynamik, Computational Methods for Engineering Application I (empfehlenswertes Wahlfach, 4. Semester) und Informatik (Programmieren) werden numerische Methoden für Berechnungsaufgaben der Fluiddynamik, Energie- und Verfahrenstechnik dargestellt und an einfachen Beispielen geübt. 1. Einleitung Übersicht, Anwendungen Problemlösungsprozess, Fehler 2. Rekapitulation der Grundgleichungen Formulierung, Anfangs- und Randbedingungen 3. Numerische Diskretisierungsverfahren Finite-Differenzen- und Finite-Volumen-Verfahren Grundbegriffe: Konsistenz, Stabilität, Konvergenz 4. Lösung der grundlegenden Gleichungstypen Wärmeleitungs/Diffusionsgleichung (parabolisch) Poisson-Gleichung (elliptisch) Advektionsgleichung/Wellengleichung (hyperbolisch) und Advektions-Diffusions-Gleichung 5. Berechnung inkompressibler Strömungen 6. Berechnung turbulenter Strömungen | |||||
Lecture notes | Lecture notes are available (in German) | |||||
Literature | a list of references is supplied | |||||
Prerequisites / Notice | It is crucial to actively solve the analytical and practical (programming) exercises. | |||||
Systems and Control | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
227-0216-00L | Control Systems II | W | 6 credits | 4G | R. Smith | |
Abstract | Introduction to basic and advanced concepts of modern feedback control. | |||||
Objective | Introduction to basic and advanced concepts of modern feedback control. | |||||
Content | This course is designed as a direct continuation of the course "Regelsysteme" (Control Systems). The primary goal is to further familiarize students with various dynamic phenomena and their implications for the analysis and design of feedback controllers. Simplifying assumptions on the underlying plant that were made in the course "Regelsysteme" are relaxed, and advanced concepts and techniques that allow the treatment of typical industrial control problems are presented. Topics include control of systems with multiple inputs and outputs, control of uncertain systems (robustness issues), limits of achievable performance, and controller implementation issues. | |||||
Lecture notes | The slides of the lecture are available to download. | |||||
Literature | Skogestad, Postlethwaite: Multivariable Feedback Control - Analysis and Design. Second Edition. John Wiley, 2005. | |||||
Prerequisites / Notice | Prerequisites: Control Systems or equivalent | |||||
227-0046-10L | Signals and Systems II | W | 4 credits | 2V + 2U | J. Lygeros | |
Abstract | Continuous and discrete time linear system theory, state space methods, frequency domain methods, controllability, observability, stability. | |||||
Objective | Introduction to basic concepts of system theory. | |||||
Content | Modeling and classification of dynamical systems. Modeling of linear, time invariant systems by state equations. Solution of state equations by time domain and Laplace methods. Stability, controllability and observability analysis. Frequency domain description, Bode and Nyquist plots. Sampled data and discrete time systems. Advanced topics: Nonlinear systems, chaos, discrete event systems, hybrid systems. | |||||
Lecture notes | Copy of transparencies | |||||
Literature | Recommended: K.J. Astrom and R. Murray, "Feedback Systems: An Introduction for Scientists and Engineers", Princeton University Press 2009 Link | |||||
Prerequisites / Notice | THE LECTURE WILL BE GIVEN IN ENGLISH. |
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