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AdaptDQC: Adaptive Distributed Quantum Computing With Quantitative Performance Analysis

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OA
AI
D
Debin Xiang
L
Liqiang Lu
S
Siwei Tan
X
Xinghui Jia
Z
Zhe Zhou
G
Guangyu Sun
M
Mingshuai Chen
J
Jianwei Yin
DOI:10.1109/TC.2025.3586027delete
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Abstract

Abstract

En 中文
We present AdaptDQC, an adaptive compiler framework for optimizing distributed quantum computing (DQC) under diverse performance metrics and inter-chip communication (ICC) architectures. AdaptDQC leverages a novel spatial-temporal graph model to describe quantum circuits, model ICC architectures, and quantify critical performance metrics in DQC systems, yielding a systematic and adaptive approach to constructing circuit-partitioning and chip-mapping strategies that admit hybrid ICC architectures and are optimized against various objectives. Experimental results on a collection of benchmarks show that AdaptDQC outperforms state-of-the-art compiler frameworks: It reduces, on average, the communication cost by up to 35.4% and the latency by up to 38.4%.
Keywords:
Distributed quantum computing
heterogeneous quantum communication
distributed systems

Journal

IEEE Transactions on Computers cover
IEEE Transactions on Computers
IF:
3.8
Papers:
5.3K
Citations:
9.8K

Organization

P
peking university
Scholars:
11.8W
Papers: 8.7W
Citations: 146
Z
zhejiang university
Scholars:
17.5W
Papers: 12.0W
Citations: 152