Experimental quantum end-to-end learning on a superconducting processor

Experimental quantum end-to-end learning on a superconducting processor

Abstract Machine learning can be enhanced by a quantum computer via its inherent quantum parallelism. In the pursuit of quantum advantages for machine learning with noisy intermediate-scale quantum devices, it was proposed that the learning model can be designed in an end-to-end fashion, i.e., the q...

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Bibliographic Details
Main Authors: Xiaoxuan Pan, Xi Cao, Weiting Wang, Ziyue Hua, Weizhou Cai, Xuegang Li, Haiyan Wang, Jiaqi Hu, Yipu Song, Dong-Ling Deng, Chang-Ling Zou, Re-Bing Wu, Luyan Sun
Format: Article
Language:English
Published: Nature Portfolio 2023-03-01
Series:npj Quantum Information
Online Access:https://doi.org/10.1038/s41534-023-00685-w

Internet

https://doi.org/10.1038/s41534-023-00685-w

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