1st Semester<\/strong><\/em><\/p>\n (R. Pakzad<\/a>)<\/em> - Local and global curve theory of curves, Hopf theorem, classical surface theory, the inner geometry of surfaces, theorema egregium, geometry and topology, Gauss-Bonnet theorem.<\/p>\n <\/div>\r\n \r\n (M. Rouleux<\/a>) <\/em>- Hilbert spaces, orthogonal projections onto closed convex sets and consequences, Hilbertian basis, weak convergence in a Hilbert space and its properties (weak Bolzano-Weierstrass), Riesz representation theorem; Linear continuous (bounded) operators on Hilbert space, connection with weak convergence, self-adjoint operators, compact operators, norm limit of finite rank operators; Elements of spectral theory, spectral localization and Lax-Milgram theorem, diagonalization of compact self-adjoint operators; Banach spaces, Hahn-Banach theorem, linear continuous functionals on Banach space, weak convergence, Banach-Steinhaus theorem and its consequences, open mapping theorem, closed graph theorem.<\/p>\n <\/div>\r\n \r\n (S. Vaienti<\/a>)<\/em> - Recalls on probability spaces and random variables: general definitions, monotone continuity properties of probability measures (Beppo Levi), Borel-Cantelli lemma, monotone classes theorem and Dynkin's classes (statements only) and applications, discrete probability (characterization); Random variables (r.v.): general definitions, discrete, continuous and absolutely continuous r.v., distribution functions, Chebychev nequality, Skorokhod representation theorem on the existence of r.v.'s from a given law, calculations of probability distributions; Generating and characteristic functions of a r.v.; Gaussian vectors; Conditional probabilities and conditional expections; Sequences and sums of random variables: different kinds of convergence: almost sure, in probability, in distribution and relationship with the convergence of characteristics functions, Paul Levy's theorem, Skorokhod representation theorem; Limit theorems: laws of large numbers and central theorem limit, large deviations for Bernoulli r.v., some notions on random walks and Markov chains, construction of Brownian motion.<\/p>\n <\/div>\r\n \r\n (J. Asch<\/a> et Y. Aubry<\/a>)<\/em> - Matrix Lie groups: definitions, classical groups, compactness, connectedness, homomorphisms; Lie algebras and the exponential mapping: matrix\u00a0 exponential, Lie algebras, abstract Lie algebras, complexification; Lie algebras vs. Lie groups: Baker-Campbell-Hausdorff formula, Lie group and Lie algebra homomorphisms; Basic representation theory: defintions, examples, Schur's lemma, direct sum of representations; Irreducible representations of SU(2): construction of some representations of SU(2), irreducible representations of su(2), representations of Lie groups vs. representations of Lie algebras.<\/p>\n <\/div>\r\n \r\n English - 2 ECTS -- 18h<\/strong><\/p>\n (F. Armao<\/a>)<\/em> - This class will focus on oral and written comprehension\/production of English with a strong emphasis on oral interaction. Students will be asked to do an oral presentation connected with their field of study; this presentation will lead to a debate in English between students. Further details will be given during the first class (which should not be missed). Additionally, we will work on other scientific themes, mainly through the prism of video and written documents. Students are required to attend class and to actively participate.<\/p>\n TICE - 1 ECTS -- 10h<\/strong><\/p>\n (T. Champion<\/a>)<\/em> Learning LaTeX: a software package particularly well-suited to prepare documents containing mathematical formulas.<\/p>\n <\/div>\r\n <\/div>\r\n\r\n\r\n\r\n <\/div>\n 2nd Semester<\/strong><\/em><\/p>\n (P. Briet<\/a>) - Spaces of test functions: locally convex and separated topological vector spaces, convergence and continuity, most important test function spaces; Distributions: definitions, convergence of of distributions; Basic operations on distributions: derivatives, multiplication by a function, support and singular support; Convolution: convolution of functions, regularisation, convolution of distributions; Fundamental solutions: definition, fundamental solutions of important differential operators; Tempered distributions: Fourier transform, tempered distributions, Fourier transform of tempered distributions, applications.<\/p>\n <\/div>\r\n \r\n (R. Pakzad<\/a>, C. Galusinski<\/a>)<\/em> - Approximation of elliptic PDEs: finite difference, finite element, and finite volume method; Evolution problems and stability: parabolic and hyperbolic problems; Applications to image restoration.<\/p>\n <\/div>\r\n \r\n Applied analysis - 3 ECTS -- 30h<\/strong><\/p>\n
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