Post-cut metadata from quantum circuit fragments enables high-accuracy inference of algorithm family, cut mechanism, and Hamiltonian structure via machine learning on fragment width, depth, and gate counts.
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DQR enables efficient scheduling and failover for cut quantum circuit fragments across local QPUs and remote simulators on real HPC hardware with low coordination overhead.
QuMod is a multi-programmable scheduler for modular QPUs that jointly optimizes qubit mapping, parallel circuit execution, measurement synchronization, and inter-QPU teleportation via dynamic circuits.
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.
citing papers explorer
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Post-Cut Metadata Inference Attacks on Quantum Circuit Cutting Pipelines
Post-cut metadata from quantum circuit fragments enables high-accuracy inference of algorithm family, cut mechanism, and Hamiltonian structure via machine learning on fragment width, depth, and gate counts.
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Wave-Based Dispatch for Circuit Cutting in Hybrid HPC--Quantum Systems
DQR enables efficient scheduling and failover for cut quantum circuit fragments across local QPUs and remote simulators on real HPC hardware with low coordination overhead.
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QuMod: Parallel Quantum Job Scheduling on Modular QPUs using Circuit Cutting
QuMod is a multi-programmable scheduler for modular QPUs that jointly optimizes qubit mapping, parallel circuit execution, measurement synchronization, and inter-QPU teleportation via dynamic circuits.
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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.