Search Results for author: Alexander Debus

Found 6 papers, 2 papers with code

Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows

no code implementations27 Feb 2023 Anna Willmann, Jurjen Couperus Cabadağ, Yen-Yu Chang, Richard Pausch, Amin Ghaith, Alexander Debus, Arie Irman, Michael Bussmann, Ulrich Schramm, Nico Hoffmann

Understanding and control of Laser-driven Free Electron Lasers remain to be difficult problems that require highly intensive experimental and theoretical research.

Normalising Flows

Continual learning autoencoder training for a particle-in-cell simulation via streaming

no code implementations9 Nov 2022 Patrick Stiller, Varun Makdani, Franz Pöschel, Richard Pausch, Alexander Debus, Michael Bussmann, Nico Hoffmann

These simulations will have a high spatiotemporal resolution, which will impact the training of machine learning models since storing a high amount of simulation data on disk is nearly impossible.

Continual Learning

Data-Driven Shadowgraph Simulation of a 3D Object

no code implementations1 Jun 2021 Anna Willmann, Patrick Stiller, Alexander Debus, Arie Irman, Richard Pausch, Yen-Yu Chang, Michael Bussmann, Nico Hoffmann

In this work we propose a deep neural network based surrogate model for a plasma shadowgraph - a technique for visualization of perturbations in a transparent medium.

Object

Large-scale Neural Solvers for Partial Differential Equations

1 code implementation8 Sep 2020 Patrick Stiller, Friedrich Bethke, Maximilian Böhme, Richard Pausch, Sunna Torge, Alexander Debus, Jan Vorberger, Michael Bussmann, Nico Hoffmann

However, recent numerical solvers require manual discretization of the underlying equation as well as sophisticated, tailored code for distributed computing.

Distributed Computing

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