南方科技大学知识苑(SUSTech KC): Experimental Quantum-Enhanced Machine Learning in Spin-Based Systems

题名	Experimental Quantum-Enhanced Machine Learning in Spin-Based Systems
作者	Wang，Xiangyu; Lin，Zidong; Che，Liangyu; Chen，Hanyu; Lu，Dawei
通讯作者	Lu，Dawei
发表日期	2022
DOI	10.1002/qute.202200005
发表期刊	Advanced Quantum Technologies 影响因子和分区
EISSN	2511-9044
卷号	5
摘要	With the advancement of computing power and algorithms, machine learning has been a powerful tool in numerous applications nowadays. However, the hardware limitation of classical computers and the increasing size of datasets urge the community to explore new techniques for machine learning. Quantum-enhanced machine learning is such a rapidly growing field. It refers to quantum algorithms that are implemented in quantum computers, which can improve the computational speed of classical machine learning tasks and often promises an exponential speedup. In the past few years, the development of experimental quantum technologies leads to many experimental demonstrations of quantum-enhanced machine learning in diverse physical systems. Here, the recent experimental progress in this field in two typical spin-based quantum systems—nuclear magnetic resonance and nitrogen-vacancy centers in diamond—is reviewed, and the ongoing challenges are discussed.
关键词	nitrogen-vacancy centers nuclear magnetic resonance quantum machine learning spin qubits
相关链接	[Scopus记录]
收录类别	SCI ; EI
语种	英语
学校署名	第一 ; 通讯
资助项目	National Key Research and Development Program of China[2019YFA0308100] ; National Natural Science Foundation of China[12075110,11975117,11905099,11875159,11905111,"U1801661"] ; Guangdong Basic and Applied Basic Research Foundation[2019A1515011383] ; Guangdong International Collaboration Program[2020A0505100001] ; Science, Technology and Innovation Commission of Shenzhen Municipality["ZDSYS20190902092905285","KQTD20190929173815000","JCYJ20200109140803865","JCYJ20180302174036418"] ; Pengcheng Scholars, Guangdong Innovative and Entrepreneurial Research Team Program[2019ZT08C044] ; Guangdong Provincial Key Laboratory[2019B121203002]
WOS研究方向	Physics ; Optics
WOS类目	Quantum Science & Technology ; Optics
WOS记录号	WOS:000809379900001
出版者	WILEY
EI入藏号	20222412216736
EI主题词	Machine learning ; Nitrogen ; Nuclear magnetic resonance ; Quantum optics ; Qubits
EI分类号	Machine Learning:723.4.2 ; Light, Optics and Optical Devices:741 ; Light/Optics:741.1 ; Nanotechnology:761 ; Chemical Products Generally:804 ; Quantum Theory; Quantum Mechanics:931.4
Scopus记录号	2-s2.0-85131533423
来源库	Scopus
引用统计	被引频次[WOS]：3
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/336294
专题	理学院_物理系量子科学与工程研究院
作者单位	Shenzhen Institute for Quantum Science and Engineering and Department of Physics,Southern University of Science and Technology,Shenzhen,518055,China
第一作者单位	物理系; 量子科学与工程研究院
通讯作者单位	物理系; 量子科学与工程研究院
第一作者的第一单位	物理系; 量子科学与工程研究院
推荐引用方式 GB/T 7714	Wang，Xiangyu,Lin，Zidong,Che，Liangyu,et al. Experimental Quantum-Enhanced Machine Learning in Spin-Based Systems[J]. Advanced Quantum Technologies,2022,5.
APA	Wang，Xiangyu,Lin，Zidong,Che，Liangyu,Chen，Hanyu,&Lu，Dawei.(2022).Experimental Quantum-Enhanced Machine Learning in Spin-Based Systems.Advanced Quantum Technologies,5.
MLA	Wang，Xiangyu,et al."Experimental Quantum-Enhanced Machine Learning in Spin-Based Systems".Advanced Quantum Technologies 5(2022).