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Abstract

Machine learning is widely applied in various areas due to its advantages in pattern recognition, but it is severely restricted by the computing power of classic computers. In recent years, with the rapid development of quantum technology, quantum machine learning has been verified experimentally verified in many quantum systems, and exhibited great advantages over classical algorithms for certain specific problems. In the present review, we mainly introduce two typical spin systems, nuclear magnetic resonance and nitrogen-vacancy centers in diamond, and review some representative experiments in the field of quantum machine learning, which were carried out in recent years.

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Authors and contacts

Corresponding author:Lu Da-Wei,ludw@sustc.edu.cn

Funds:Project supported by the National Key Research and Development Program of China (Grant No. 2019YFA0308100), the National Natural Science Foundation of China (Grant Nos. 12075110, 11975117, 11905099, 11875159, U1801661), the Guangdong Basic and Applied Basic Research Foundation, China (Grant No. 2019A1515011383), the Guangdong International Collaboration Program, China (Grant No. 2020A0505100001), the Science, Technology, and Innovation Commission of Shenzhen Municipality, China (Grant Nos. ZDSYS20170303165926217, KQTD20190929173815000, JCYJ20200109140803865, JCYJ20170412152620376, JCYJ20180302174036418), the Pengcheng Scholars, the Guangdong Innovative and Entrepreneurial Research Team Program, China (Grant No. 2019ZT08C044), and the Guangdong Provincial Key Laboratory, China (Grant No. 2019B121203002)

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Vol. 70, Issue 14 - 2021-07-20

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