7 papers
Scaling Quantum Machine Learning without Tricks: Full-Resolution and Diverse Image Generation
Jonas Jäger, Florian J. Kiwit, Carlos A. RiofrÃo
Quantum generative modeling is a rapidly evolving discipline at the intersection of quantum computing and machine learning. Contemporary quantum machine learning is generally limit…
Quantum State Preparation via Neural Network Encoding in Quantum Machine Learning
Kevin W. Aoun, Florian J. Kiwit, Carlos A. RiofrÃo +4
A central challenge in quantum machine learning is the state preparation bottleneck that describes the prohibitive computational cost of loading high-dimensional classical data int…
Hybrid Quantum-HPC Middleware Systems for Adaptive Resource, Workload and Task Management
Pradeep Mantha, Florian J. Kiwit, Nishant Saurabh +2
Hybrid quantum-classical applications pose significant resource management challenges due to heterogeneity and dynamism in both infrastructure and workloads. Quantum-HPC environmen…
Typical Machine Learning Datasets as Low-Depth Quantum Circuits
Florian J. Kiwit, Bernhard Jobst, Andre Luckow +2
Quantum machine learning (QML) is an emerging field that investigates the capabilities of quantum computers for learning tasks. While QML models can theoretically offer advantages…
Pilot-Quantum: A Quantum-HPC Middleware for Resource, Workload and Task Management
Pradeep Mantha, Florian J. Kiwit, Nishant Saurabh +2
As quantum hardware advances, integrating quantum processing units (QPUs) into HPC environments and managing diverse infrastructure and software stacks becomes increasingly essenti…
BenchQC -- Scalable and modular benchmarking of industrial quantum computing applications
Florian Geissler, Eric Stopfer, Christian Ufrecht +19
We present BenchQC, a research project funded by the state of Bavaria, which promotes an application-centric perspective for benchmarking real-world quantum applications. Diverse u…