aiqbench analysis
DPRQ introduces a dynamic programming approach to optimize qubit routing in distributed quantum computing, addressing the critical bottleneck of inefficient inter-node entanglement distribution. By focusing on global circuit-level optimization rather than greedy block-level strategies, this algorithm significantly reduces communication overhead and resource requirements for executing quantum circuits across multiple nodes. This advancement is essential for scaling quantum systems beyond single-processor limitations without compromising execution speed or accuracy.
DPRQ: A Dynamic Programming-based Qubit Routing Algorithm for Collective Communication in Distributed Quantum Computing
arXiv:2609.04524v1 Announce Type: new Abstract: Distributed quantum computing (DQC) offers a promising approach to scale quantum computing by overcoming the resource limitations of a single quantum processor. However, inter-node communication remains a major bottleneck of DQC due to inefficient and error-prone entanglement distribution. Optimizing inter-node communication can not only reduce the amount of entanglement resource needed to execute a quantum circuit but also improve execution speed and accuracy of the results. This paper proposes DPRQ, a qubit routing algorithm for minimizing inter-node communication in distributed quantum circuits divided into collective communication blocks. Unlike current approaches that utilize greedy block-level qubit routing strategies, DPRQ employs a dynamic programming-based technique focused on global circuit-level optimization, while capturing inter-block dependencies. We evaluated DPRQ on four sets of quantum circuits and a variety of DQC configurations. The results demonstrate that DPRQ's innovative routing strategy achieves an average of 24.40% reduction with a maximum of 85.06% reduction in inter-node communication, when compared to the state-of-the-art collective communication-based DQC compiler QuComm.
Abstract:Distributed quantum computing (DQC) offers a promising approach to scale quantum computing by overcoming the resource limitations of a single quantum processor. However, inter-node communication remains a major bottleneck of DQC due to inefficient and error-prone entanglement distribution. Optimizing inter-node communication can not only reduce the amount of entanglement resource needed to execute a quantum circuit but also improve execution speed and accuracy of the results. This paper proposes DPRQ, a qubit routing algorithm for minimizing inter-node communication in distributed quantum circuits divided into collective communication blocks. Unlike current approaches that utilize greedy block-level qubit routing strategies, DPRQ employs a dynamic programming-based technique focused on global circuit-level optimization, while capturing inter-block dependencies. We evaluated DPRQ on four sets of quantum circuits and a variety of DQC configurations. The results demonstrate that DPRQ's innovative routing strategy achieves an average of 24.40% reduction with a maximum of 85.06% reduction in inter-node communication, when compared to the state-of-the-art collective communication-based DQC compiler QuComm.
Quantum Physics (quant-ph); Distributed, Parallel, and Cluster Computing (cs.DC)
arXiv:2609.04524 [quant-ph]
(or arXiv:2609.04524v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2609.04524 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
Proc. 3rd ACM SIGCOMM Workshop on Quantum Networks and Distributed Quantum Computing (QuNet' 26), 2026, pp. 68-73
https://doi.org/10.1145/3833409.3833449 Focus to learn more DOI(s) linking to related resources
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