3 papers
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
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…
quant-ph2024
Qunicorn: A Middleware for the Unified Execution Across Heterogeneous Quantum Cloud Offerings
Benjamin Weder, Johanna Barzen, Martin Beisel +4
Quantum computers are available via a variety of different quantum cloud offerings. These offerings are heterogeneous and differ in features, such as pricing models or types of acc…