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.
Cutting circuits with multiple two-qubit unitaries
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
quant-ph 2years
2026 2representative citing papers
InterQ presents a communication-aware scheduler for modular QPUs that jointly optimizes placement, parallel execution, adaptive circuit cutting, and link-specific coordination for superconducting, trapped-ion, and neutral-atom systems.
citing papers explorer
-
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.
-
InterQ: Communication-Aware Scheduling Across Modular QPUs with Classical and Quantum Links
InterQ presents a communication-aware scheduler for modular QPUs that jointly optimizes placement, parallel execution, adaptive circuit cutting, and link-specific coordination for superconducting, trapped-ion, and neutral-atom systems.