Hierarchical QAOA Circuit Design Framework for Distributed Quantum Computing

Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a promising approach for solving combinatorial optimization problems on real quantum devices. As QAOA scales to tackle larger problem instances, the limited qubit capacity of single-chip systems becomes a critical bottleneck. To overcome this limitation, distributed quantum computing (DQC) provides a scalable solution. However, when QAOA circuits are executed in such systems, their performance is significantly hindered by the high cost of remote communication. Motivated by this challenge, we propose HiQ-DF , a QAOA circuit design framework tailored for DQC systems. By employing a hierarchical optimization strategy, HiQ-DF enables comprehensive multi-objective optimization during circuit construction. Experimental results on QAOA circuits solving MaxCut instances show that our framework significantly outperforms baseline methods, achieving an average reduction of 26.12% in EPR pair usage (up to 36.85%), 26.44% in circuit latency (up to 35.27%), and 39.63% in circuit depth (up to 49.3%).