A Quantum Circuit Optimization Framework for Distributed Quantum Computing

Fengsheng Liu

doi:10.1109/tcad.2026.3656760

A Quantum Circuit Optimization Framework for Distributed Quantum Computing

2026-01-21

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DOI：10.1109/tcad.2026.3656760

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Distributed quantum computing (DQC) is essential for achieving scalability by overcoming the resource constraints of current noisy intermediate-scale quantum devices through multiprocessor architectures. Traditional quantum circuit compilation has focused on monolithic optimization metrics such as gate count and depth. However, distributed architectures introduce the concept of global gates, which refer to cross-partition operations that dominate communication overhead. Existing methods employ a circuit optimization followed by circuit partitioning, which often leads to partitioning results with more communications. This work proposes a circuit optimization framework that explicitly targets DQC, aiming to optimize global gates overhead while maintaining the total gate counts. A beam search algorithm is employed to explore an equivalent circuit under a set of transformation rules, minimizing a mixed cost function that balances total and global gate overhead. This approach achieves an average reduction rate of 16.89% in total gates and 31.24% in global gates on 26 benchmark circuits when the number of partitions is 2, and 15.42% and 25.09%, respectively, when the number of partitions is 3.

Keywords:

Distributed quantum circuit partitioning

distributed quantum computing (DQC)

quantum circuit optimization

A Quantum Circuit Optimization Framework for Distributed Quantum Computing

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