A Resource-Virtualized and Hardware-Aware Quantum Compilation Framework for Real Quantum Computing Processors

As quantum computing systems continue to scale up and become more clustered, efficiently compiling user quantum programs into high-fidelity executable sequences on real hardware remains a key challenge for current quantum compilation systems. In this study, we introduce a system-software framework that integrates resource virtualization and hardware-aware compilation for real quantum computing processors, termed QSteed. QSteed virtualizes quantum processors through a 4-layer abstraction hierarchy comprising the real quantum processing unit (QPU), standard QPU (StdQPU), substructure of the QPU (SubQPU), and virtual QPU (VQPU). These abstractions, together with calibration data, device topology, and noise descriptors, are maintained in a dedicated database to enable unified and fine-grained management across superconducting quantum platforms. At run time, the modular compiler queries the database to match each incoming circuit with the most suitable VQPU, after which it confines layout, routing, gate resynthesis, and noise-adaptive optimizations to that virtual subregion. The complete stack has been deployed on the Quafu superconducting cluster, where experimental runs confirm the correctness of the virtualization model and the efficacy of the compiler without requiring modifications to user code. By integrating resource virtualization with a select-then-compile workflow, QSteed demonstrates a robust architecture for compiling programs on noisy superconducting processors. This architectural approach offers a promising path toward efficient compilation needs across various superconducting quantum computing platforms in the noisy intermediate-scale quantum era.

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Publication Details

Journal
Research
Published
2025-01-01
DOI
https://doi.org/10.34133/research.0947
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

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article

A Resource-Virtualized and Hardware-Aware Quantum Compilation Framework for Real Quantum Computing Processors

Wei-Feng Zhuang, Dong E. Liu, Mengjun Hu, Yirong Jin et al.
Research
Quantum Computing Algorithms and Architecture
article

A Resource-Virtualized and Hardware-Aware Quantum Compilation Framework for Real Quantum Computing Processors

Wei-Feng Zhuang, Dong E. Liu, Mengjun Hu, Yirong Jin, Yulong Feng, Xudan Chai, Hong-Ze Xu, Haifeng Yu, Xinpeng Zhang, Zheng‐An Wang, Jingbo Wang, Heng Fan, Yu Chen, Yu‐Xin Jin
article en

Abstract

As quantum computing systems continue to scale up and become more clustered, efficiently compiling user quantum programs into high-fidelity executable sequences on real hardware remains a key challenge for current quantum compilation systems. In this study, we introduce a system-software framework that integrates resource virtualization and hardware-aware compilation for real quantum computing processors, termed QSteed. QSteed virtualizes quantum processors through a 4-layer abstraction hierarchy comprising the real quantum processing unit (QPU), standard QPU (StdQPU), substructure of the QPU (SubQPU), and virtual QPU (VQPU). These abstractions, together with calibration data, device topology, and noise descriptors, are maintained in a dedicated database to enable unified and fine-grained management across superconducting quantum platforms. At run time, the modular compiler queries the database to match each incoming circuit with the most suitable VQPU, after which it confines layout, routing, gate resynthesis, and noise-adaptive optimizations to that virtual subregion. The complete stack has been deployed on the Quafu superconducting cluster, where experimental runs confirm the correctness of the virtualization model and the efficacy of the compiler without requiring modifications to user code. By integrating resource virtualization with a select-then-compile workflow, QSteed demonstrates a robust architecture for compiling programs on noisy superconducting processors. This architectural approach offers a promising path toward efficient compilation needs across various superconducting quantum computing platforms in the noisy intermediate-scale quantum era.

ResearchVol. 8
Beijing Institute of Technology (CN), Chinese Academy of Sciences (CN), Hefei University (CN), Chinese Academy of Engineering (CN), Institute of Computing Technology (CN), Centre for Quantum Computation and Communication Technology (AU), Institute of Mechanics (BG), Beijing Academy of Quantum Information Sciences (CN), Institute of Physics (CN), University of Chinese Academy of Sciences (CN), Tsinghua University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 86%
Quantum Computing Algorithms and Architecture
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