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Date Time Venue Talk
05/23/22 03:00 pm Zoom On observability estimates for semigroups in Banach spaces
Dennis Gallaun

In this talk, I would like to present the main results of my PhD thesis.
We study a general method to obtain observability estimates for control systems in infinite dimensional spaces by combining an uncertainty principle and a dissipation estimate. Contrary to previous results obtained in the context of Hilbert spaces, we obtain conditions for observability in Banach spaces, allow for more general asymptotic behavior in the assumptions, and retain explicit estimates on the observability constant.
Our approach has applications, e.g., to control systems on non-reflexive spaces and anomalous diffusion operators.
Further, we derive duality results that connect observability estimates to controllability and stabilizability properties. As an application, we study controllability properties of systems given by fractional powers of elliptic differential operators with constant coefficients in $L_p(\mathbb{R}^d)$ for $p\in [1,\infty)$ and thick control sets.

05/09/22 03:00 pm Zoom Resilience in Spectral Deferred Corrections
Thomas Baumann, FZ Jülich

Advancement in computational speed is nowadays gained by using more processing units rather than faster ones.
Faults in the processing units caused by numerous sources including radiation and aging have been neglected in the past.
However, the increasing size of HPC machines makes them more susceptible and it is important to develop a resilience strategy to avoid losing millions of CPU hours.
Parallel-in-time methods target the very largest of computers and are hence required to come with algorithm-based fault tolerance.
We look here at spectral deferred corrections (SDC), which is a time marching scheme that is at the heart of parallel-in-time methods such as PFASST.
Due to its iterative nature, there is ample opportunity to plug in computationally inexpensive fault tolerance schemes, many of which are also easy to implement.
We experimentally examine the capability of various strategies to recover from single bit flips in time serial SDC, which will later be applied to parallel-in-time methods.

05/02/22 03:00 pm Zoom Robot manipulation in real-time, in the real-world, and under uncertainty.*
Wisdom Agboh, University of Leeds

Robots have the potential to disrupt many aspects of our lives, from healthcare to manufacturing. To realize this potential, a key challenge is real-time robot manipulation. Given a task, how can a robot quickly generate a motion plan to successfully complete it? How can the robot react in real-time to potential uncertainties in the real-world as it executes its plan? In this talk, we will overview recent developments at the University of Leeds, to realize real-time robot manipulation. These will include parallel-in-time integration methods that leverage parallel computing to significantly speed-up physics predictions for various robot manipulation tasks. It will also include learning-based and optimal control-based methods for robots to handle real-world uncertainties in object pose estimation and model parameters. We hope these recent advances will help accelerate the next generation of intelligent robots.


Meeting ID: 853 5362 6407
Passcode: 045209
04/25/22 03:00 pm Zoom Component sizes of scale-free inhomogeneous random graphs
Matthias Lienau

The Norros-Reittu model is an inhomogeneous random multigraph that exhibits the so-called scale-free or power-law behaviour, which is observed in real-world complex networks. We study the component sizes of the Norros-Reittu model in the subcritical regime, i.e. in the abscence of a giant component, and show convergence of the point process of the component sizes to a Poisson process. It is planned to derive similar results for other models such as the random connection model.
04/11/22 03:00 pm Am Schwarzenberg-Campus 3 (E), Room 3.074 & Zoom Introductory Talk: Boundary layer enriched Hybrid Discontinuous Galerkin Methods for Convection dominated flow
Abdul Qadir Ibrahim

The thesis deals with boundary layer enrichment of convection dominated flow problems using the Hybrid Discontinuous Galerkin Method. It aims to introduce an appropriate and computationally efficient Hybrid Discontinuous Galerkin formulation for the most important model problems of incompressible fluid flow, namely the convection-diffusion equation.The main contribution is the derivation, discussion and analysis of the Enriched Finite elementSpace using non-polynomial spaces (specifically boundary layer functions) for both the Discontinuous Galerkin Methods and the Hybrid Discontinuous Galerkin Method. We evaluate the robustness (i.e linear stability as well as reasonable linear systems) and accuracy of this method using various analytical and realistic problems and compare the results to those obtained using the standard (H)DG method. Numerical results are provided to contrast the Enriched (H)DG methods with standard (H)DG approaches.
03/31/22 04:30 pm Am Schwarzenberg-Campus 3 (E), Room 3.074 Understanding Double Descent in Neural Networks [Bachelorarbeit]
Marvin Steinmeister
03/29/22 10:00 am Zoom Random Walks and Tridiagonal Matrices [Masterarbeit]
Luis Weber, TM
02/23/22 10:30 am Zoom Untersuchung statistischer Vorhersagealgorithmen für Offshore Wetter-Zeitreihen [Bachelorarbeit]
Sebastian Eberle
02/22/22 03:00 pm Online Forecasting the shipped volume using a neural network model based on a booking data driven pick-up approach [Masterarbeit]
Gordon Lisch
02/15/22 01:00 pm online Machine Learning of Gradient-based Optimization Methods [Bachelorarbeit]
Leonard Schröter

* Talk within the Colloquium on Applied Mathematics