Branch-Aware Quantum Constant Propagation for Dynamic Quantum Circuits
2026-06-01 • Emerging Technologies
Emerging Technologies
AI summaryⓘ
The authors developed a new way to optimize quantum circuits that can change while running, called dynamic circuits. Their method, Branch-Aware Quantum Constant Propagation (BQCP), improves on earlier techniques by carefully tracking how measurements affect both classical and quantum parts of the circuit in different scenarios. This allows more precise simplifications of the circuit that keep the results correct. They also make sure the method doesn't become too slow by limiting the complexity of what it tracks. Tests show that their approach reduces circuit size better than previous methods for dynamic circuits.
Quantum circuitsCompile-time optimizationDynamic circuitsMid-circuit measurementClassical feedforwardQuantum constant propagationPath-sensitive analysisCircuit simplificationSoundnessQuantum state representation
Authors
Innocenzo Fulginiti, Yanbin Chen
Abstract
Compile-time optimization is important for improving the efficiency and reliability of quantum circuits on current noisy hardware. While many existing methods simplify circuits using structural patterns or quantum-state information, most of them target only unitary circuits and do not support dynamic circuits with mid-circuit measurements and classical feedforward. In this work, we present Branch-Aware Quantum Constant Propagation (BQCP), a compile-time analysis for dynamic circuits. BQCP extends Quantum Constant Propagation (QCP) by tracking the classical information produced by mid-circuit measurements together with the corresponding post-measurement quantum states across different execution branches. This enables path-sensitive reasoning inside conditional blocks and more precise information propagation than QCP. To keep the analysis scalable, we bound both the size of the quantum-state representation and the number of tracked branches. Using the information inferred by the analysis, we apply semantics-preserving simplifications to circuit operations. We prove the soundness of both the analysis and the simplifications. Experimental results on both application-driven and synthetic benchmarks show that, on dynamic circuits, our method consistently achieves larger reductions than other existing passes including QCP.