341 citations
- Volkswagen Group (United States)US10 papers
- Technical University of MunichDE7 papers
- Eötvös Loránd UniversityHU5 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE5 papers
- RWTH Aachen UniversityDE5 papers
- Michigan State UniversityUS4 papers
- Technische Universität BraunschweigDE4 papers
- Ludwig-Maximilians-Universität MünchenDE3 papers
- Technische Universität DarmstadtDE3 papers
- Xanadu Quantum Technologies (Canada)CA3 papers
- BMW (Germany)DE2 papers
- École Polytechnique Fédérale de LausanneCH2 papers
50 papers
Decoder Dependence in Surface-Code Threshold Estimation under Digitized Hybrid Continuous-Variable and Discrete Noise
Dennis Delali Kwesi Wayo, Chinonso Onah, Leonardo Goliatt +1
Surface-code threshold estimates depend on the inference pipeline, including decoder and estimator choices. We compare decoders within a single LiDMaS+ workflow under Pauli-referen…
Evaluating Sample-Based Krylov Quantum Diagonalization for Heisenberg Models with Applications to Materials Science
Roman Firt, Neel Misciasci, Jonathan E. Mueller +4
We evaluate the Sample-based Krylov Quantum Diagonalization (SKQD) algorithm on one- and two-dimensional Heisenberg models, including strongly correlated regimes in which the groun…
Benchmarking Convolutional Neural Network and Graph Neural Network based Surrogate Models on a Real-World Car External Aerodynamics Dataset
Sam Jacob Jacob, Markus Mrosek, Carsten Othmer +1
Aerodynamic optimization is crucial for developing eco-friendly, aerodynamic, and stylish cars, which requires close collaboration between aerodynamicists and stylists, a collabora…
Real-time and On-site Aerodynamics using Stereoscopic PIV and Deep Optical Flow Learning
Mohamed Elrefaie, Steffen Hüttig, Mariia Gladkova +3
We introduce Recurrent All-Pairs Field Transforms for Stereoscopic Particle Image Velocimetry (RAFT-StereoPIV). Our approach leverages deep optical flow learning to analyze time-re…
On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer
Elie Aljalbout, Felix Frank, Maximilian Karl +1
We study the choice of action space in robot manipulation learning and sim-to-real transfer. We define metrics that assess the performance, and examine the emerging properties in t…
Scalable stellar evolution forecasting: Deep learning emulation vs. hierarchical nearest neighbor interpolation
K. Maltsev, F. R. N. Schneider, F. K. Roepke +5
Many astrophysical applications require efficient yet reliable forecasts of stellar evolution tracks. One example is population synthesis, which generates forward predictions of mo…