activity
20242026
collaborators

6 papers

cs.SE2026

A Methodology for Investigating AI Patterns Prevalence in Software Repositories

Srinath Perera, Hasinthaka Piyumal, Frank Leymann +1

As Artificial Intelligence(AI)-based applications take off, a clear understanding of AI patterns can uplift the quality of AI applications. Many AI patterns have been proposed in t…

quant-ph2025

Loss Behavior in Supervised Learning with Entangled States

Alexander Mandl, Johanna Barzen, Marvin Bechtold +2

Quantum Machine Learning (QML) aims to leverage the principles of quantum mechanics to speed up the process of solving machine learning problems or improve the quality of solutions…

quant-ph2025

On the Differential Topology of Expressivity of Parameterized Quantum Circuits

Johanna Barzen, Frank Leymann

Parameterized quantum circuits play a key role in quantum computing. Measuring the suitability of such a circuit for solving a class of problems is needed. One such promising measu…

quant-ph2025

Simulating Quantum State Transfer between Distributed Devices using Noisy Interconnects

Marvin Bechtold, Johanna Barzen, Frank Leymann +1

Scaling beyond individual quantum devices via distributed quantum computing relies critically on high-fidelity quantum state transfers between devices, yet the quantum interconnect…

quant-ph2025

Harnessing Patterns to Support the Development of Hybrid Quantum Applications

Daniel Vietz, Martin Beisel, Johanna Barzen +3

Quantum computing provides computational advantages in various domains. To benefit from these advantages complex hybrid quantum applications must be built, which comprise both quan…

cs.SE2024

Quantum Software Engineering: Roadmap and Challenges Ahead

Juan M. Murillo, Jose Garcia-Alonso, Enrique Moguel +13

As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective -k…