5 papers · 1 filter
QML Essentials -- A framework for working with Quantum Fourier Models
Melvin Strobl, Maja Franz, Eileen Kuehn +2
In this work, we propose a framework in the form of a Python package, specifically designed for the analysis of Quantum Machine Learning models. This framework is based on the Penn…
Make Some Noise! Measuring Noise Model Quality in Real-World Quantum Software
Stefan Raimund Maschek, Jürgen Schwitalla, Maja Franz +1
Noise and imperfections are among the prevalent challenges in quantum software engineering for current NISQ systems. They will remain important in the post-NISQ area, as logical, e…
From Hope to Heuristic: Realistic Runtime Estimates for Quantum Optimisation in NHEP
Maja Franz, Manuel Schönberger, Melvin Strobl +5
Noisy Intermediate-Scale Quantum (NISQ) computers, despite their limitations, present opportunities for near-term quantum advantages in Nuclear and High-Energy Physics (NHEP) when…
QCE'24 Tutorial: Quantum Annealing -- Emerging Exploration for Database Optimization
Nitin Nayak, Manuel Schönberger, Valter Uotila +4
Quantum annealing is a meta-heuristic approach tailored to solve combinatorial optimization problems with quantum annealers. In this tutorial, we provide a fundamental and comprehe…
Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation
Maja Franz, Tobias Winker, Sven Groppe +1
Identifying optimal join orders (JOs) stands out as a key challenge in database research and engineering. Owing to the large search space, established classical methods rely on app…