17 citations · 74 across the 13 of their papers we have counts for
13 papers
Offset Finding of Beamline Parameters on the METRIXS Beamline at BESSY II Using Machine Learning
David Meier, Thomas Zeschke, Peter Feuer-Forson +3
Beamline alignment is challenging as the beamline components must be set up ideally so that the rays follow the desired optical path. Automated methods using a digital twin allow f…
Reconstructing Time-of-Flight Detector Values of Angular Streaking Using Machine Learning
David Meier, Wolfram Helml, Thorsten Otto +3
Angular streaking experiments enable for experimentation in the attosecond regions. However, the deployed Time-of-flight detectors are susceptible to noise and failure. These short…
Attosecond soft X-ray pulses generated by chirp-dispersed manipulation in an XFEL reveal nonlinear core-electron dynamics in neon
Lars Funke, Markus Ilchen, Svitozar Serkez +59
Free-electron lasers have demonstrated their capability of generating intense attosecond X-ray pulses, which are the key to studying electron dynamics at their natural time scale a…
Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation
Diego Botache, Jens Decke, Winfried Ripken +4
This paper presents a methodological framework for training, self-optimising, and self-organising surrogate models to approximate and speed up multiobjective optimisation of techni…
Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis
Diego Botache, Kristina Dingel, Rico Huhnstock +2
Splitting of sequential data, such as videos and time series, is an essential step in various data analysis tasks, including object tracking and anomaly detection. However, splitti…
DADO -- Low-Cost Query Strategies for Deep Active Design Optimization
Jens Decke, Christian Gruhl, Lukas Rauch +1
In this experience report, we apply deep active learning to the field of design optimization to reduce the number of computationally expensive numerical simulations. We are interes…
Dataset of a parameterized U-bend flow for Deep Learning Applications
Jens Decke, Olaf Wünsch, Bernhard Sick
This dataset contains 10,000 fluid flow and heat transfer simulations in U-bend shapes. Each of them is described by 28 design parameters, which are processed with the help of Comp…
Three-dimensional close-to-substrate trajectories of magnetic microparticles in dynamically changing magnetic field landscapes
Rico Huhnstock, Meike Reginka, Claudius Sonntag +5
The transport of magnetic nano- or microparticles in microfluidic devices using artificially designed magnetic field landscapes (MFL) is promising for the implementation of key fun…
Optimizing a Superconducting Radiofrequency Gun Using Deep Reinforcement Learning
David Meier, Luis Vera Ramirez, Jens Völker +3
Superconducting photoelectron injectors are a promising technique for generating high brilliant pulsed electron beams with high repetition rates and low emittances. Experiments suc…
Translatory and rotatory motion of Exchange-Bias capped Janus particles controlled by dynamic magnetic field landscapes
Rico Huhnstock, Meike Reginka, Andreea Tomita +6
Magnetic Janus particles (MJPs), fabricated by covering a non-magnetic spherical particle with a hemispherical magnetic in-plane exchange-bias layer system cap, display an onion ma…
Artificial intelligence for online characterization of ultrashort X-ray free-electron laser pulses
Kristina Dingel, Thorsten Otto, Lutz Marder +11
X-ray free-electron lasers (XFELs) as the world's brightest light sources provide ultrashort X-ray pulses with a duration typically in the order of femtoseconds. Recently, they hav…
Transport efficiency of biofunctionalized magnetic particles tailored by surfactant concentration
Meike Reginka, Hai Hoang, Özge Efendi +8
Controlled transport of surface functionalized magnetic beads in a liquid medium is a central requirement for the handling of captured biomolecular targets in microfluidic lab-on-c…
AdaPT: Adaptable Particle Tracking for Spherical Microparticles in Lab on Chip Systems
Kristina Dingel, Rico Huhnstock, André Knie +2
Due to its rising importance in science and technology in recent years, particle tracking in videos presents itself as a tool for successfully acquiring new knowledge in the field…