most citedQuantum Computing and Tensor Networks for Laminate Design: A Novel Approach to Stacking Sequence Retrieval

14 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2026

Illuminating early ZrC oxidation using ensemble small-cell DFT with dynamic gas management

Philip Wurzner, Boyang Chen, Matthias Möller +3

During zirconium carbide oxidation, liberated carbon can remain beneath the oxide or escape as gas, complicating the interpretation of mass measurements. We adapt the small-cell en…

quant-ph2026

MOSAIQC: Mixed-topology-aware Optimization for Scalable Approximate noise-Informed Quantum circuit Cutting

Koen Mesman, Yinglu Tang, Matthias Moller +2

Current quantum computers do not yet have the required qubit resources to meet the demands of most practical quantum algorithms. To circumvent this constraint, the practice of divi…

quant-ph2024

Quantum-assisted Stacking Sequence Retrieval and Laminated Composite Design

Arne Wulff, Swapan Madabhushi Venkata, Boyang Chen +3

We, the QAIMS lab lab at the Aerospace Faculty of TU Delft, participated as finalists in the Airbus/BMW Quantum Computing Challenge 2024. Stacking sequence retrieval, a complex com…

quant-ph2024★ 1 cited

NN-AE-VQE: Neural network parameter prediction on autoencoded variational quantum eigensolvers

Koen Mesman, Yinglu Tang, Matthias Moller +2

A longstanding computational challenge is the accurate simulation of many-body particle systems. Especially for deriving key characteristics of high-impact but complex systems such…

quant-ph2024★ 14 cited

Quantum Computing and Tensor Networks for Laminate Design: A Novel Approach to Stacking Sequence Retrieval

Arne Wulff, Boyang Chen, Matthew Steinberg +3

As with many tasks in engineering, structural design frequently involves navigating complex and computationally expensive problems. A prime example is the weight optimization of la…