The authors present Pilot-Quantum, a middleware for adaptive resource management in hybrid quantum-HPC systems, along with execution motifs and a performance modeling toolkit called Q-Dreamer.
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A calibration-aware graph reinforcement-learning router improves exact simulated fidelity by ~0.25-0.29 over SABRE baselines on 5-8 qubit MQT Bench circuits, while 10-qubit circuits still favor SABRE.
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Hybrid Quantum-HPC Middleware Systems for Adaptive Resource, Workload and Task Management
The authors present Pilot-Quantum, a middleware for adaptive resource management in hybrid quantum-HPC systems, along with execution motifs and a performance modeling toolkit called Q-Dreamer.
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Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing
A calibration-aware graph reinforcement-learning router improves exact simulated fidelity by ~0.25-0.29 over SABRE baselines on 5-8 qubit MQT Bench circuits, while 10-qubit circuits still favor SABRE.