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Kolloquium der Arbeitsgruppe Modellierung • Numerik • Differentialgleichungen

Wintersemester 2018/2019
Verantwortliche Dozenten:
Alle Professoren der
Arbeitsgruppe Modellierung • Numerik • Differentialgleichungen
Koordination:
Mones Raslan
Termine:
Di 16-18 Uhr in MA 313 und nach Vereinbarung
Inhalt:
Vorträge von Gästen und Mitarbeitern zu aktuellen Forschungsthemen
Kontakt:

Beschreibung

Das Kolloquium der Arbeitsgruppe "Modellierung, Numerik, Differentialgleichungen" im Institut der Mathematik ist ein Kolloquium klassischer Art. Es wird also von einem breiten Kreis der Professoren und Mitarbeiter aus allen zugehörigen Lehrstühlen, insbesondere Angewandte Funktionalanalysis, Numerische Lineare Algebra, und Partielle Differentialgleichungen, besucht. Auch Studierende nach dem Bachelorabschluss zählen schon zu den Teilnehmern unseres Kolloquiums.

Aus diesen Gründen freuen wir uns insbesondere über Vorträge, die auf einen nicht spezialisierten Hörerkreis zugeschnitten sind und auch von Studierenden nach dem Bachelorabschuss bereits mit Profit gehört werden können.

Terminplanung / schedule (Abstracts s. unten / Abstracts see below)
Datum
date
Zeit
time
Raum
room
Vortragende(r)
speaker
Titel
title
Einladender
invited by
23.10.2018
16:15
MA 313
Ronald W. Hoppe (Universität Augsburg / University of Houston)

Rolf D. Grigorieff
Numerical Solution of Second and Fourth Order Total Variation Flow Problems 
Kolloquium zum 80. Geburtstag von Rolf D. Grigorieff
06.11.2018
16:15
MA 313
Robert Calderbank
(Duke University)


Golay, Heisenberg and Weyl
G. Kutyniok
13.11.2018
16:15
MA 313
David Šiška
(University of  Edinburgh)
Exponential Convergence of Policy Improvement Algorithm for Controlled Diffusions
E. Emmrich
04.12.2018
16:15
MA 313
María Soledad Aronna (Escola de Matemática Aplicada Rio de Janeiro) 
On second order optimality conditions for control-affine problems 
F. Tröltzsch
18.12.2018
16:15
MA 313
08.01.2019
16:15
MA 313
Herbert Egger (TU Darmstadt)
On the systematic approximation of evolution problems
with dissipation, Hamiltonian, or gradient structure
V. Mehrmann
15.01.2019
16:15
MA 313
22.01.2019
16:15
MA 313
29.01.2019
16:15
MA 313
Paul Kotyczka
(TU München)
Volker Mehrmann
05.02.2019
16:15
MA 313
12.02.2019
16:15
MA 313
19.02.2019
16:15
MA 313

Abstracts zu den Vorträgen

Ronald W. Hoppe (Universität Augsburg / University of Houston)

Numerical Solution of Second and Fourth Order Total Variation Flow Problems

 

María Soledad Aronna (Escola de Matemática Aplicada Rio de Janeiro): 

On second order optimality conditions for control-affine problems 

In this talk I will present the main features of first and second order optimality conditions for optimal control problems of ordinary differential equations that are affine with respect to the control and nonlinear with respect to the state. Assuming the presence of control constraints, I will present a second order sufficient condition for optimality and a numerical scheme in the form of a shooting method.

 

Robert Calderbank (Duke University): 

Golay, Heisenberg and Weyl

Sixty years ago, efforts by Marcel Golay to improve the sensitivity of far infrared spectrometry led to the discovery of pairs of complementary sequences. We will describe how these sequences are finding new application in active sensing, where the challenge is how to see faster, to see more finely where necessary, and to see with greater sensitivity, by being more discriminating about how we look.

Biography: Robert Calderbank is Director of the Information Initiative at Duke University, where he is Professor of Mathematics and of Electrical and Computer Engineering. Prior to joining Duke in 2010, he directed the Program in Applied and Computational Mathematics at Princeton University. Prior to joining Princeton in 2004 he was Vice President for Research at AT&T, in charge of what may have been the first industrial research lab where the primary focus was Big Data.

Dr. Calderbank is well known for contributions to voiceband modem technology, to quantum information theory, and for co-invention of space-time codes for wireless communication. His research papers have been cited almost 50,000 times and his inventions are found in billions of consumer devices. Professor Calderbank was elected to the National Academy of Engineering in 2005 and has received a number of awards, including the 2013 IEEE Hamming Medal for his contributions to information transmission, and the 2015 Claude E. Shannon Award.

 

David Siska (University of Edinburgh)

Exponential Convergence of Policy Improvement Algorithm for Controlled Diffusions

In this talk I will present the main features of first and second order optimality conditions for optimal control problems of ordinary differential equations that are affine with respect to the control and nonlinear with respect to the state. Assuming the presence of control constraints, I will present a second order sufficient condition for optimality and a numerical scheme in the form of a shooting method.

 

Herbert Egger (TU Darmstadt)

On the systematic approximation of evolution problems
with dissipation, Hamiltonian, or gradient structure.

A general framework for the numerical approximation of evolution
problems is presented that allows
to preserve an underlying dissipative, Hamiltonian, or gradient
structure. The approach is based on rewriting
the evolution problem in a particular form that complies with the
underlying structure and its variational
formulation. The underlying structure is then preserved automatically
under Galerkin projection in space,
which allows to deduce important structural properties for appropriate
discretization schemes including
projection based model reduction methods.

For the time-discretization, we consider two different approaches
depending on the underlying geometric
structure, i.e., discontinuous Galerkin and Petrov-Galerkin
approximations. Again, the basic structure of
the problem is inherited automatically by the proposed discretization
schemes.

The presented framework is rather general and allows the numerical
approximation of a wide range of applications,
including nonlinear partial differential equations and port-Hamiltonian
systems. Several examples will be discussed
for illustration and some connections to other discretization approaches
will be revealed.

Zusatzinformationen / Extras