Here you can find past and upcoming events organized by our group.
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Thu24Oct2024Thu27Mar2025
Prof. Dr. Nicolas Gauger, Chair for Scientific Computing (SciComp), TU Kaiserslautern
SciComp Seminar Series
Please contact Prof. Gauger, if you want to register for an online talk in our SciComp Seminar Series or just to register for the seminar.
A list of the already scheduled talks can be found –> here:
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Thu07Nov2024
11:45Hybrid (Room 32-349 and via Zoom)
Dr. Marcella Bonazzoli, Inria Saclay Centre at Institut Polytechnique de Paris (Palaiseau, France)
Title: One-shot and domain decomposition methods for inverse problems
Abstract:
When an inverse problem is solved by a gradient-based optimization algorithm, the corresponding forward and adjoint problems, which are introduced to compute the gradient, can be also solved iteratively, for instance by domain decomposition methods. In this framework, one-shot inversion methods iterate at the same time on the inverse problem unknown and on the forward and adjoint problem solutions. We are especially interested in the case where the inner iterations for the direct and adjoint problems are incomplete, that is, stopped before achieving a high accuracy on their solutions.
We analyze the convergence of one-shot methods for general linear inverse problems and fixed-point iterations for the associated forward/adjoint problems. In particular, we establish sufficient conditions on the descent step for convergence, which are explicit in the number of inner iterations. We provide numerical experiments, for linear and non linear inverse problems, to illustrate the convergence of these methods in comparison with the classical gradient descent method, where the forward and adjoint problems are solved exactly by a direct solver instead.
This is joint work with Tuan Anh Vu and Houssem Haddar.How to join online
You can join online via Zoom, using the following link:
https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09 -
Tue19Nov2024
11:00Room 32-349
Lea Fischer, University of Göttingen
Title: Proximal Block Implicit-Explicit Algorithm for Near-field Ptychography
Abstract:
The talk explores the application of the Proximal Heterogeneous Block Input-Output Method (PHeBIE) algorithm to the blind near-field ptychography problem. The structure of the near-field ptychography problem uses lateral and longitudinal shifts of the object. The talk begins with an introduction to fundamental concepts of numerical analysis, focusing on the Fourier transform and the Fresnel near-field propagator. We present an approach to near-field ptychography using lateral and longitudinal shifts, as well as the PHeBIE algorithm. The core of this work lies in the application of the PHeBIE algorithm to near-field ptychography. The resulting new algorithm is implemented in Python and numerical results are presented.
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Thu12Dec2024
11:45Room 32-349
Gururaj Bhat, RPTU
Title: Electricity market nodeling
Abstract:
Electricity is a unique and indispensable commodity that underpins nearly every aspect of
modern life. Electricity prices are affected by numerous factors like fuel sources for power
generation, infrastructure of the electricity grids, and weather, to name a few. Modelling
electricity prices is a complex process due to its non-storable property and the different
characteristics it exhibits, which are discussed in this work. Nonetheless, it is important
to have reliable price simulations to manage risks, keep the system operating smoothly,
and encourage investment in infrastructure and technology for the future. Acknowledging
the past work on anomaly detection in electricity price data, this thesis evaluates existing
methods on recent German market prices and addresses the challenges faced by them.
This work proposes a segmented anomaly detection approach for data processing before
the data is used for calibrating the spot price model. A two-factor electricity spot price
model with a diffusion factor and a jump factor is implemented. Analysis and inferences
drawn from studying the impact of the existing and new methods on the data quality are
presented first. The yield of the respective methods is then evaluated by the calibration
and simulation performance of the chosen two-factor model. The results support the
application of segmented approaches presented in this work as they identify jumps with
higher accuracy, and are able to capture more realised spot price observations in the
different quantile ranges of the simulated price paths. -
Fri13Dec2024
The goal of the workshop is to give an overview of recent research activities at SciComp. In addition, collaborators from Fraunhofer ITWM, DFKI, MTU Aero Engines and TU Eindhoven will give invited presentations for scientific exchange. Finally, we will brainstorm about future collaboration.
Program
13:00-15:00 Scientific Short Presentations – SciComp (5+5 minutes each)
(Dr. E. Özkaya, Dr. M. Sagebaum, T. Kortus, A. Schilling, O. Burghardt, R. Pochampalli, J. Blühdorn, G. Suarez, Dr. L. Chen, M. Aehle, J. Rottmayer)15:00-15:30 Coffee break
Keynote Talk
15:30-16:45 Prof L. Kusch (TU Eindhoven)16:45-17:30 Scientific Short Presentations – Guests (10+5 minutes each)
(S. Hauck (ITWM), M. Klostermeier (DFKI), C. Battistoni (MTU))17:30-18:00 Brainstorming/Thoughts on Future Collaboration (Prof. N. Gauger)
18:00 Workshop Dinner
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Fri13Dec2024
15:30Hybrid (Room 32-349 and via Zoom)
Prof. Lisa Kusch, TU Eindhoven, The Netherlands
Title:
Design of optical systems: Extending inverse design strategies for imaging and using neural networks for the design of optical surfaces.Abstract:
Optical systems are designed for various purposes: In non-imaging systems (e.g. lighting) optical surfaces shall guide the light to achieve a certain illuminance. For imaging systems (e.g. cameras, telescopes) light coming from a single point of the object shall also be focused on a single point of the image.
Inverse methods for optical design have been established in the past for designing illumination systems. The overall goal is to find freeform optical surfaces that convert a source distribution into a desired target distribution. With the help of laws for optics, it is possible to find the inverse solution of this problem. This involves solving the Monge-Ampere equation with a transport boundary condition. In this talk we extend the methodology to the design of imaging systems and propose an alternative process for finding the inverse solution.
Designing for imaging optics (cameras, scopes) aims at minimizing aberrations that are deviations from the perfect image on a given target surface. In the first part of this talk we derive an additional condition for inverse design to allow for the design of imaging systems. We apply this methodology for the design of a two-dimensional reflector system and compare the results to a classical design of a telescope system.
In the second part of this talk we will take a closer look at an alternative approach for solving the Monge-Ampere equation with transport boundary condition using a neural network. We impose properties of the underlying physical problem by formulating an appropriate loss function for training the network. The performance is compared to the classical solution strategy based on finite differences and the methodology is further analysed by performing a hyperparameter study.
Finally, we will see some future challenges for the design of imaging systems.
How to join online
You can join online via Zoom, using the following link:
https://uni-kl-de.zoom.us/j/63123116305?pwd=Yko3WU9ZblpGR3lGUkVTV1kzMCtUUT09