Automorphic Forms Seminar, Dr. Arnab Mitra, Technion-Israel Institute of Technology, Haifa, MATH 215
Thursday, Jul 20 1:30 pm - 2:30 pm
On local symplectic periods on general and unitary groupsAbstract: Let E/F be a quadratic separable extension of non-archimedean local fields. The group Sp(2n,F) sits inside both GL(2n,F) and U(2n,F) (the quasi-split unitary group with respect to the extension E/F) as a closed subgroup. This talk is about Sp(2n,F)-distinguished representations of the aforementioned groups. I will begin by motivating the question of classifying distinguished representations for general symmetric spaces after which we will look into some specific classification results for Sp(2n,F)-distinguished representations of these two groups.
Department Colloquium, Prof. A. Raghuram, Indian Institute of Science Education and Research, MATH 175
Tuesday, Aug 22 3:30 pm - 4:30 pm
From Calculus to Number Theory (via Cohomology)
Monday, Aug 28 4:30 pm - 5:30 pm
Tuesday, Aug 29 3:30 pm - 4:30 pm
Monday, Sep 11 4:30 pm - 5:30 pm
Automorphic Forms and Representation Theory Seminar, Prof. Allen Moy, Hong Kong University of Science and Technology, BRNG 1260
Thursday, Sep 14 1:30 pm - 2:30 pm
An Euler-Poincare formula for a depth zero Bernstein projectorWork of Bezrukavnikov-Kazhdan-Varshavsky uses an equivariant system of trivial idempotents of Moy-Prasad groups to obtain an Euler-Poincare formula for the r-depth Bernstein projector. We establish an Euler-Poincare formula for the projector to an individual depth zero Bernstein component in terms of an equivariant system of Peter-Weyl idempotents of parahoric subgroups P associated to a block of the reductive quotient P. This work is joint with Dan Barbasch and Dan Ciubortau.
Graduate Student Invited Colloquium Speaker, Prof. Ilse Ipsen, North Carolina State University, MATH 175
Tuesday, Sep 19 3:30 pm - 4:30 pm
Randomized Algorithms for Matrix ComputationsThe emergence of massive data sets, over the past fifteen or so years, has lead to the development of Randomized Numerical Linear Algebra. Fast and accurate randomized matrix algorithms are being designed for applications like machine learning, population genomics, astronomy, nuclear engineering, and optimal experimental design. We give a flavour of randomized algorithms for the solution of least squares/regression problems and, if time permits, for the computation of logdeterminants. Along the way we illustrate important concepts from numerical analysis (conditioning and pre-conditioning) and statistics (sampling and leverage scores).
Jean Rubin Memorial Lecture (Colloquium), Prof. Jacqueline M. Hughes-Oliver, North Carolina State University, MATH 175
Tuesday, Sep 26 3:30 pm - 4:30 pm
Tuesday, Oct 17 3:30 pm - 4:30 pm
Monday, Oct 23 4:30 pm - 5:30 pm
Tuesday, Oct 24 3:30 pm - 4:30 pm