29 citations · 44 across the 12 of their papers we have counts for
14 papers
JAQSI: Just Another Quantum Simulator
Melvin Strobl, Maja Franz, Lukas Scheller +3
Classical simulation supports the development and validation of quantum algorithms through full-state inspection, controlled noise models and backpropagation, albeit for small quan…
Towards Tensor-Network SAT-Solvers for Quantum-Classical Workflows
Benjamin Zec, Lukas Schmidbauer, Maja Franz +1
Integrated HPC/QC systems aim to combine classical high-performance computing with quantum processors, but cannot be reduced to mechanisms for dispatching quantum kernels. An integ…
Works on My QPU: Reproducibility in Quantum Computing Research
Dominik Köster, Maja Franz, Benjamin Zec +3
Quantum computing research increasingly depends on complex software stacks, yet the reproducibility of published results does not receive the priority and longevity mandated by rec…
Software Between Quantum and Machine Learning -- And Down to Pulses
Maja Franz, Melvin Strobl, Jonathan Hunz +5
Contemporary quantum computing platforms remain, in essence, programmable physical systems whose control is typically mediated through unitary gate abstractions. While such abstrac…
Beyond Gates: Pulse Level Quantum Fourier Models
Melvin Strobl, Maja Franz, Lukas Scheller +3
In the domain of variational quantum algorithms, quantum Fourier models (QFMs) provide a mathematically well defined structure for quantum machine learning (QML). There has been a…
Towards Quantum Software for Quantum Simulation
Maja Franz, Lukas Schmidbauer, Joshua Ammermann +2
Quantum simulation is a leading candidate for demonstrating practical quantum advantage over classical computation, as it is believed to provide exponentially more compute power th…
Going off Pattern? QAOA Parameter Heuristics and Potentials of Parsimony
Vincent Eichenseher, Maja Franz, Christian Wolff +1
Structured variational quantum algorithms such as the Quantum Approximate Optimisation Algorithm (QAOA) have emerged as leading candidates for exploiting advantages of near-term qu…
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…
Out of Tune: Demystifying Noise-Effects on Quantum Fourier Models
Maja Franz, Melvin Strobl, Leonid Chaichenets +3
Variational quantum algorithms have received substantial theoretical and empirical attention. As the underlying variational quantum circuit (VQC) can be represented by Fourier seri…
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…
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…
Peel Pile? Cross-Framework Portability of Quantum Software
Manuel Schönberger, Maja Franz, Stefanie Scherzinger +1
In recent years, various vendors have made quantum software frameworks available. Yet with vendor-specific frameworks, code portability seems at risk, especially in a field where h…
Uncovering Instabilities in Variational-Quantum Deep Q-Networks
Maja Franz, Lucas Wolf, Maniraman Periyasamy +5
Deep Reinforcement Learning (RL) has considerably advanced over the past decade. At the same time, state-of-the-art RL algorithms require a large computational budget in terms of t…