DC-MBQC: A Distributed Compilation Framework for Measurement-Based Quantum Computing
Yecheng Xue, Rui Yang, Zhiding Liang, Tongyang Li

TL;DR
This paper introduces DC-MBQC, a novel distributed quantum compilation framework for measurement-based quantum computing, addressing key challenges in task allocation and inter-QPU communication, with significant improvements in execution time and photon lifetime.
Contribution
It presents the first tailored distributed compilation framework for MBQC, including algorithms for task partitioning and layer scheduling, optimizing performance on photonic quantum systems.
Findings
7.46× reduction in photon lifetime requirements
6.82× speedup with 8 QPUs
Demonstrates advantages of distributed MBQC in photonic systems
Abstract
Distributed quantum computing (DQC) is a promising technique for scaling up quantum systems. While significant progress has been made in DQC for quantum circuit models, there exists much less research on DQC for measurement-based quantum computing (MBQC), which is a universal quantum computing model that is essentially different from the circuit model and particularly well-suited to photonic quantum platforms. In this paper, we propose DC-MBQC, the first distributed quantum compilation framework tailored for MBQC. We identify and address two key challenges in enabling DQC for MBQC. First, for task allocation among quantum processing units (QPUs), we develop an adaptive graph partitioning algorithm that preserves the structure of the graph state while balancing the workload across QPUs. Second, for inter-QPU communication, we introduce the layer scheduling problem and propose an…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum Mechanics and Applications
