量子-经典融合计算发展现状与趋势研究

doi:10.12267/j.issn.2096-5931.2024.07.002

信息通信技术与政策 ›› 2024, Vol. 50 ›› Issue (7): 9-17.doi: 10.12267/j.issn.2096-5931.2024.07.002

量子-经典融合计算发展现状与趋势研究

Research on current situation and trend of quantum-classical fused computing development

张萌¹, 王敬¹, 黄智国², 钱岭²

1.中国信息通信研究院技术与标准研究所,北京 100191
2.中移(苏州)软件技术有限公司,苏州 215000

收稿日期:2024-05-23 出版日期:2024-07-25 发布日期:2024-07-30
作者简介:
张萌,中国信息通信研究院技术与标准研究所光网络技术与应用研究部高级工程师,量子信息网络产业联盟应用产业组副组长,主要从事量子信息领域的政策、产业、标准和前沿技术研究,以及分组传送、时频同步领域的技术研究、测试认证等相关工作
王敬,中国信息通信研究院技术与标准研究所光网络技术与应用研究部工程师,主要从事量子信息领域技术研究、标准制定以及测试验证等相关工作
黄智国,中移(苏州)软件技术有限公司云能力中心高级技术研究员,主要从事量子计算技术研究、量子云平台架构设计和工程研发工作
钱岭,中移(苏州)软件技术有限公司首席专家、云能力中心首席科学家,主要从事量子计算、云计算和大数据领域技术方向演进和总体架构设计工作

ZHANG Meng¹, WANG Jing¹, HUANG Zhiguo², QIAN Ling²

1. Technology and Standards Research Institute, China Academy of Information and Communications Technology, Beijing 100191, China
2. China Mobile (Suzhou) Software Technology Co., Ltd., Suzhou 215000, China

Received:2024-05-23 Online:2024-07-25 Published:2024-07-30

摘要/Abstract

摘要：

量子计算当前正处于一个关键的发展阶段,其中理论研究、工程研发、应用探索与产业培育都在并行推进。然而,目前量子计算处理器的硬件性能尚不能满足大规模应用问题求解的需求。在这个背景下,量子-经典融合计算应运而生,融合了量子计算与经典计算的优势,为复杂问题的解决提供了崭新的思路和方法,从而迅速成为业界瞩目的焦点。首先,对量子-经典融合计算的概念、关键技术以及发展现状进行了研究;其次,对其发展趋势进行了展望;最后,提出了推动量子-经典融合计算发展的相应建议。

关键词: 量子-经典融合计算, 量子计算, 发展现状, 建议

Abstract:

Quantum computing is at a critical stage of parallel development in theoretical research, engineering development, application exploration, and industrialization cultivation. The hardware performance of quantum computing processors still cannot meet the requirements of solving large-scale application problems. Quantum-classical fused computing combines the advantages of quantum computing and classical computing, providing new ideas and methods for solving certain complex problems, and gradually becoming a research highlight. Firstly, this paper analyzes the concept, key technologies, and current development situation of quantum-classical fused computing. Then, it looks forward to the development trend of quantum-classical fused computing. Finally, it puts forward corresponding suggestions to promote the high-quality development of quantum-classical fused computing.

Key words: quantum-classical fused computing, quantum computing, development situation, suggestion

中图分类号:

TN918
O413

张萌, 王敬, 黄智国, 钱岭. 量子-经典融合计算发展现状与趋势研究[J]. 信息通信技术与政策, 2024, 50(7): 9-17.

ZHANG Meng, WANG Jing, HUANG Zhiguo, QIAN Ling. Research on current situation and trend of quantum-classical fused computing development[J]. Information and Communications Technology and Policy, 2024, 50(7): 9-17.

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链接本文:

http://ictp.caict.ac.cn/CN/10.12267/j.issn.2096-5931.2024.07.002

http://ictp.caict.ac.cn/CN/Y2024/V50/I7/9

图/表 2

参考文献 26

[1]	中国信息通信研究院. 量子信息技术发展与应用研究报告(2023年)[R], 2023.
[2]	FU X, YU J T, SU X, et al. Quingo: a programming framework for heterogeneous quantum-classical computing with NISQ features[J]. ACM Transactions on Quantum Computing, 2021, 2(4):1-37.
[3]	KNILL E. Conventions for quantum pseudocode[R]. arXiv Preprint, arXiv:2211.02559, 1996.
[4]	PERUZZO A, MCCLEAN J, SHADBOLT P, et al. A variational eigenvalue solver on a photonic quantum processor[J]. Nature Communications, 2014, 5(1):4213.
[5]	MCCLEAN J R, ROMERO J, BABBUSH R, et al. The theory of variational hybrid quantum-classical algorithms[J]. New Journal of Physics, 2016, 18(2):023023.
[6]	TILLY J, CHEN H X, CAO S X, et al. The variational quantum eigensolver: a review of methods and best practices[J]. Physics Reports, 2022,986:1-128.
[7]	FARHI E, GOLDSTONE J, GUTMANN S. A quantum approximate optimization algorithm[J]. arXiv Preprint, arXiv:1411.4028, 2014.
[8]	PELOFSKE E, BÄRTSCHI A, EIDENBENZ S. Quantum annealing vs. QAOA: 127 qubit higher-order ising problems on NISQ computers[C]// International Conference on High Performance Computing. Springer Nature Switzerland, 2023:240-258.
[9]	ZEGUENDRY A, JARIR Z, QUAFAFOU M. Quantum machine learning: a review and case studies[J]. Entropy, 2023, 25(2):287.
[10]	WAN K H, DAHLSTEN O, KRISTJÁNSSON H, et al. Quantum generalisation of feedforward neural networks[J]. npj Quantum Information, 2017, 3(1):36.
[11]	BEER K, BONDARENKO D, FARRELLY T, et al. Training deep quantum neural networks[J]. Nature Communications, 2020,11:808.
[12]	CONG I, CHOI S, LUKIN M D. Quantum convolutional neural networks[J]. Nature Physics, 2019,15: 1273-1278.
[13]	CEREZO M, ARRASMITH A, BABBUSH R, et al. Variational quantum algorithms[J]. Nature Reviews Physics, 2021,3:625-644.
[14]	FU X, RIESEBOS L, ROL M A, et al. eQASM: an executable quantum instruction set architecture[C]// 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA). IEEE, 2019:224-237.
[15]	IBM. IBM quantum summit 2023[EB/OL]. (2023-12-04)[2024-03-19]. https://www.ibm.com/quantum/summit-2023.
[16]	科大国盾量子技术股份有限公司. 不算太难?500比特量子计算芯片面世[EB/OL]. (2024-04-25)[2024-05-07]. https://baijiahao.baidu.com/s?id=1797359672674040367&wfr=spider&for=pc.
[17]	中国科学院. 2024中关村论坛年会发布中国科学院多项重大成果[EB/OL]. (2024-04-25)[2024-05-07]. https://www.cas.cn/spx/202404/t20240425_5012649.shtml.
[18]	Quantinuum. Quantinuum extends its significant lead in quantum computing, achieving historic milestones for hardware fidelity and quantum volume[EB/OL]. (2024-04-16)[2024-05-08]. https://www.quantinuum.com/news/quantinuum-extends-its-significant-lead-in-quantum-computing-achieving-historic-milestones-for-hardware-fidelity-and-quantum-volume.
[19]	BLUVSTEIN D, EVERED S J, GEIM A A, et al. Logical quantum processor based on reconfigurable atom arrays[J]. Nature, 2024,626:58-65.
[20]	PAUSE L, STURM L, MITTENBÜHLER M, et al. Supercharged two-dimensional tweezer array with more than 1 000 atomic qubits[J]. Optica, 2021, 11(2):222-226.
[21]	Atom Computing. Quantum startup Atom Computing first to exceed 1 000 qubits[EB/OL]. (2023-10-24)[2024-03-20]. https://atom-computing.com/quantum-startup-atom-computing-first-to-exceed-1000-qubits/.
[22]	MADSEN L S, LAUDENBACH F, ASKARANI M F, et al. Quantum computational advantage with a programmable photonic processor[J]. Nature, 2022,606:75-81.
[23]	DENG Y H, GU Y C, LIU H L, et al. Gaussian boson sampling with pseudo-photon-number-resolving detectors and quantum computational advantage[J]. Physical Review Letters, 2023,131:150601.
[24]	GIL-FUSTER E, EISERT J, BRAVO-PRIETO C. Understanding quantum machine learning also requires rethinking generalization[J]. Nature Communications, 2024,15:2277.
[25]	SUPRANO A, ZIA D, INNOCENTI L, et al. Experimental property reconstruction in a photonic quantum extreme learning machine[J]. Physical Review Letters, 2024, 132(16):160802.
[26]	IBM. Development & Innovation Roadmap.[EB/OL]. 2024[2024-05-07]. https://www.ibm.com/quantum/assets/IBM_Quantum_Development_&_Innovation_Roadmap.pdf.

量子-经典融合计算发展现状与趋势研究

Research on current situation and trend of quantum-classical fused computing development

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