Resource-aware distributed quantum circuits partitioning strategy and transmission cost optimization

doi:10.1088/1674-1056/ae13ec

中国物理B ›› 2026, Vol. 35 ›› Issue (7): 70302-070302.doi: 10.1088/1674-1056/ae13ec

Resource-aware distributed quantum circuits partitioning strategy and transmission cost optimization

Pengcheng Zhu(朱鹏程)^1,2,†, Zongyuan Dai(戴宗原)¹, Lihua Wei(卫丽华)¹, Jin Qian(钱进)¹, and Shi-Guang Feng(冯世光)^3,‡

1 College of Information Engineering, Taizhou University, Taizhou 225300, China;
2 College of Information Engineering, Suqian University, Suqian 223800, China;
3 School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China

收稿日期:2025-06-24 修回日期:2025-10-14 接受日期:2025-10-16 发布日期:2026-07-15
通讯作者: Pengcheng Zhu, Shi-Guang Feng E-mail:zhupcnt@163.com;fengshg3@mail.sysu.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 62072259), in part by the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20221411), and in part by the Quantum Science Strategic Initiative Project of Guangdong Province, China (Grant No. GDZX2303007).

Resource-aware distributed quantum circuits partitioning strategy and transmission cost optimization

Pengcheng Zhu(朱鹏程)^1,2,†, Zongyuan Dai(戴宗原)¹, Lihua Wei(卫丽华)¹, Jin Qian(钱进)¹, and Shi-Guang Feng(冯世光)^3,‡

1 College of Information Engineering, Taizhou University, Taizhou 225300, China;
2 College of Information Engineering, Suqian University, Suqian 223800, China;
3 School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China

Received:2025-06-24 Revised:2025-10-14 Accepted:2025-10-16 Published:2026-07-15
Contact: Pengcheng Zhu, Shi-Guang Feng E-mail:zhupcnt@163.com;fengshg3@mail.sysu.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 62072259), in part by the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20221411), and in part by the Quantum Science Strategic Initiative Project of Guangdong Province, China (Grant No. GDZX2303007).

摘要/Abstract

摘要： To overcome the physical limitations of current quantum hardware in terms of available qubits and connectivity, distributed quantum computing (DQC) has emerged as a promising and scalable paradigm. However, in distributed settings, cross-node qubit interactions incur high communication overhead due to the use of costly quantum communication protocols. Efficient circuit partitioning and transmission cost optimization have thus become key challenges. This work addresses the often-overlooked issues of hardware heterogeneity and redundant transmission by proposing a resource-aware partitioning and transmission cost optimization method for distributed quantum circuits. First, we develop a partitioning framework constrained by qubit resources, which accommodates node capacity differences to enable flexible qubit allocation. Second, we model gate dependencies using a directed acyclic graph (DAG) representation and introduce formal criteria to detect ``initial-state" and ``final-state" redundancies. A measurement-reset strategy is then employed to replace part of the quantum communication, reducing inter-node data transmission. Experimental results on a variety of benchmark circuits and heterogeneous architectures demonstrate that our method significantly reduces transmission cost and improves overall resource utilization. These findings offer both theoretical insight and practical guidance for efficient distributed quantum computing.

关键词: distributed quantum computing, quantum circuits, circuits partitioning, resource-aware

Abstract: To overcome the physical limitations of current quantum hardware in terms of available qubits and connectivity, distributed quantum computing (DQC) has emerged as a promising and scalable paradigm. However, in distributed settings, cross-node qubit interactions incur high communication overhead due to the use of costly quantum communication protocols. Efficient circuit partitioning and transmission cost optimization have thus become key challenges. This work addresses the often-overlooked issues of hardware heterogeneity and redundant transmission by proposing a resource-aware partitioning and transmission cost optimization method for distributed quantum circuits. First, we develop a partitioning framework constrained by qubit resources, which accommodates node capacity differences to enable flexible qubit allocation. Second, we model gate dependencies using a directed acyclic graph (DAG) representation and introduce formal criteria to detect ``initial-state" and ``final-state" redundancies. A measurement-reset strategy is then employed to replace part of the quantum communication, reducing inter-node data transmission. Experimental results on a variety of benchmark circuits and heterogeneous architectures demonstrate that our method significantly reduces transmission cost and improves overall resource utilization. These findings offer both theoretical insight and practical guidance for efficient distributed quantum computing.

Key words: distributed quantum computing, quantum circuits, circuits partitioning, resource-aware

中图分类号: (Quantum information)

03.67.-a

03.67.Lx (Quantum computation architectures and implementations) 03.67.Ac (Quantum algorithms, protocols, and simulations)

Pengcheng Zhu(朱鹏程), Zongyuan Dai(戴宗原), Lihua Wei(卫丽华), Jin Qian(钱进), and Shi-Guang Feng(冯世光). Resource-aware distributed quantum circuits partitioning strategy and transmission cost optimization[J]. 中国物理B, 2026, 35(7): 70302-070302.

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Resource-aware distributed quantum circuits partitioning strategy and transmission cost optimization

Resource-aware distributed quantum circuits partitioning strategy and transmission cost optimization

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