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# Events for 12/07/2018 from all calendars

## Working Seminar in Groups, Dynamics, and Operator Algebras

## Algebra and Combinatorics Seminar

## Geometry Seminar

## Colloquium - Agnieszka Miedlar

**Time:** 2:00PM - 2:00PM

**Location:** BLOC 506A

**Speaker:** Jintao Deng, Texas A&M University

**Title:** *Topological full groups of one-sided shifts of finite type VII*

**Time:** 3:00PM - 4:00PM

**Location:** BLOC 628

**Speaker:** Yang Qi, University of Chicago

**Title:** *On the rank preserving property of a linear section and its applications in tensors*

**Abstract:** This talk is motivated by several conjectures on tensor ranks arising from signal processing and complexity theory. In the talk, we will first translate these conjectures into the geometric language, and reduce the problems to the study of a particular property of a linear section of an irreducible nondegenerate projective variety, namely the rank preserving property. Then we will introduce several useful tools and show some results obtained via these tools. This talk is based on a joint work with Lek-Heng Lim.

**Time:** 4:00PM - 5:00PM

**Location:** BLOC 628

**Speaker:** Y. Qi, U. Chicago

**Title:** *TBA*

**Time:** 4:00PM - 5:00PM

**Location:** BLOC 220

**Speaker:** Agnieszka Miedlar, University of Kansas

**Description:** **Title:** Challenges for Eigenvalue Computations in Breakthrough Applications

**Abstract:** Many real life problems lead to challenging PDE eigenvalue problems, e.g., vibrations of structures or calculation of energy levels in quantum mechanics. A lot of research is devoted to the so-called Adaptive Finite Element Method (AFEM) which allows discretization of the governing PDE, solving the finite dimensional algebraic eigenvalue problem and iteratively improving obtained numerical approximations. However, advanced approaches dedicated to solve these challenging eigenvalue problems require a unified framework bringing together: spectral and perturbation theory to derive a priori error estimators, a posteriori error analysis which enables deriving efficient and reliable error estimators which take into account various errors of different origins, iterative solvers and model reduction techniques to efficiently solve finite dimensional algebraic linear and nonlinear eigenvalue problems etc. This talk will discuss several attempts to achieve the above goal. In particular, we will explain how the Cauchy integral-based approaches offer an attractive algorithmic framework when solving interior large-scale linear and nonlinear eigenvalue problems. Finally, we will illustrate presented methods with several numerical examples.

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