Research Seminar "Representations and Probability 2"
- Knowledge of key notions and results in asymptotic representations theory
- Knowledge of key notions and results in theory of random point fields, including determinantal processes.
- Knowledge of key results in theory of determinantal processes. Ability to use them to study properties of simple DPs.
- Knowledge of key results and methods in asymptotic representations theory, including asymptotic theory of characters.
- Knowledge of main results in theory of othogonal polynomials (Christoffel-Darboux kernels, etc.) Familiarity with asymtotic results for orthogonal polynomial ensembles.
- Orthogonal polynomials and random point processesElements of theory of orthogonal polynomial ensembles. Their relations to random point processes. Asymptotic problems for point processes and the corresponding functional-analytic properties of the assocuated orthogonal polynomial ensembles.
- Determinantal processesDefinition. Correlation functions. Kernel of a process and the associated operator in L2. Macchi-Soshnikov theorem. Properties of DP: rigidity, behaviour of conditional measures.
- Asymptotic representations theoryKey problems in ART. Invariant measures on spaces of matrices. Spectres distributions and their asymptotics.
- Interim assessment (4 module)The students are given a list of problems to solve at home for 7-14 days before the exam. Number of points for each problem, as well as the formula to transform the sum of points into the usual 0..10 grade is given along with the problems. On the exam student presents their solutions orally and answer some questions on the adjacent theory. Points can be deduced for poor knowledge of theoretical basis of the solutions.
- Fulton, W. (1997). Young Tableaux : With Applications to Representation Theory and Geometry. Cambridge [England]: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=570403
- Fuad Aleskerov, & Andrey Subochev. (2013). Modeling optimal social choice: matrix-vector representation of various solution concepts based on majority rule. Journal of Global Optimization, (2), 737. https://doi.org/10.1007/s10898-012-9907-2