Search result: Catalogue data in Autumn Semester 2021

Mathematics Master Information
For the Master's degree in Applied Mathematics the following additional condition (not manifest in myStudies) must be obeyed: At least 15 of the required 28 credits from core courses and electives must be acquired in areas of applied mathematics and further application-oriented fields.
Electives: Pure Mathematics
Selection: Analysis
401-4421-71LHarmonic AnalysisW4 credits2VA. Figalli
AbstractThe goal of this class is to give an introduction to harmonic analysis, covering a series of classical important results such as:
1) interpolation theorems
2) convergence properties of Fourier series
3) Calderón-Zygmund operators
4) Littlewood-Paley decomposition
5) Hardy and BMO spaces
Lecture notesI plan to write some notes of the class.
LiteratureThere is no official textbook.
401-4475-71LMicrolocal AnalysisW6 credits3GP. Hintz
AbstractMicrolocal analysis is the analysis of partial differential equations in phase space. The first half of the course introduces basic notions such as pseudodifferential operators, wave front sets of distributions, and elliptic parametrices. The second half develops modern tools for the study of nonelliptic equations, with applications to wave equations arising in general relativity.
ObjectiveStudents will be able to analyze linear partial differential operators (with smooth coefficients) and their solutions in phase space, i.e. in the cotangent bundle. For various classes of operators including, but not limited to, elliptic and hyperbolic operators, they will be able to prove existence and uniqueness (possibly up to finite-dimensional obstructions) of solutions, and study the precise regularity properties of solutions.

The first goal is to construct and apply parametrices (approximate inverses) or approximate solutions of PDEs using suitable calculi of pseudodifferential operators (ps.d.o.s). This requires defining ps.d.o.s and the associated symbol calculus on Euclidean space, proving the coordinate invariance of ps.d.o.s, and defining a ps.d.o. calculus on manifolds (including mapping properties on Sobolev spaces).

The second goal is to analyze distributions and operations on them (such as: products, restrictions to submanifolds) using information about their wave front sets or other microlocal regularity information. Students will in particular be able to compute the wave front set of distributions.

The third goal is to infer microlocal properties (in the sense of wave front sets) of solutions of general linear PDEs, with a focus on elliptic, hyperbolic and certain degenerate hyperbolic PDE. For hyperbolic operators, this includes proving the Duistermaat-Hörmander theorem on the propagation of singularities. For certain degenerate hyperbolic operators, students will apply positive commutator methods to prove results on the propagation of microlocal regularity at critical or invariant sets for the Hamiltonian vector field of the principal symbol of the partial differential operator under study.
ContentTempered distributions, Sobolev spaces, Schwartz kernel theorem.

Symbols, asymptotic summation.

Pseudodifferential operators on Euclidean space: composition, principal symbols and the symbol calculus, elliptic parametrix construction, boundedness on Sobolev spaces.

Pseudodifferential operators on manifolds, elliptic operators on compact manifolds and Fredholm theory, basic symplectic geometry.

Microlocalization: wave front set, characteristic set; pairings, products, restrictions of distributions.

Hyperbolic evolution equations: existence and uniqueness of solutions, Egorov's theorem.

Propagation of singularities: the Duistermaat-Hörmander theorem, microlocal estimates at radial sets.

Applications to general relativity: asymptotic behavior of waves on de Sitter space.
Lecture notesLecture notes will be made available on the course website.
LiteratureLars Hörmander, "The Analysis of Linear Partial Differential Operators", Volumes I and III.

Alain Grigis and Johannes Sjöstrand, "Microlocal Analysis for differential operators: an introduction".
Prerequisites / NoticeStudents are expected to have a good understanding of functional analysis. Familiarity with distribution theory, the Fourier transform, and analysis on manifolds is useful but not strictly necessary; the relevant notions will be recalled in the course.
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesfostered
Method-specific CompetenciesAnalytical Competenciesassessed
Media and Digital Technologiesfostered
Project Managementfostered
Social CompetenciesCommunicationassessed
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
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