Výsledky vyhledávání - "Xue, Shichuan"

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Experimental quantum natural gradient optimization in photonics

Autor: Wang, Yizhi, Xue, Shichuan, Wang, Yaxuan, Ding, Jiangfang, Shi, Weixu, Wang, Dongyang, Liu, Yong, Liu, Yingwen, Fu, Xiang, Huang, Guangyao, Huang, Anqi, Deng, Mingtang, Wu, Junjie

Publikováno v: Optics Letters Vol. 48, Issue 14, pp. 3745-3748 (2023)

Variational quantum algorithms (VQAs) combining the advantages of parameterized quantum circuits and classical optimizers, promise practical quantum applications in the Noisy Intermediate-Scale Quantum era. The performance of VQAs heavily depends on

Externí odkaz: http://arxiv.org/abs/2310.07371

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Quantum generative adversarial learning in photonics

Autor: Wang, Yizhi, Xue, Shichuan, Wang, Yaxuan, Liu, Yong, Ding, Jiangfang, Shi, Weixu, Wang, Dongyang, Liu, Yingwen, Fu, Xiang, Huang, Guangyao, Huang, Anqi, Deng, Mingtang, Wu, Junjie

Publikováno v: Optics Letters Vol. 48, Issue 20, pp. 5197-5200 (2023)

Quantum Generative Adversarial Networks (QGANs), an intersection of quantum computing and machine learning, have attracted widespread attention due to their potential advantages over classical analogs. However, in the current era of Noisy Intermediat

Externí odkaz: http://arxiv.org/abs/2310.00585

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Large-scale full-programmable quantum walk and its applications

With photonics, the quantum computational advantage has been demonstrated on the task of boson sampling. Next, developing quantum-enhanced approaches for practical problems becomes one of the top priorities for photonic systems. Quantum walks are pow

Externí odkaz: http://arxiv.org/abs/2208.13186

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Variational quantum process tomography

Autor: Xue, Shichuan, Liu, Yong, Wang, Yang, Zhu, Pingyu, Guo, Chu, Wu, Junjie

Publikováno v: Phys. Rev. A 105, 032427 (2022)

Quantum process tomography is an experimental technique to fully characterize an unknown quantum process. Standard quantum process tomography suffers from exponentially scaling of the number of measurements with the increasing system size. In this wo

Externí odkaz: http://arxiv.org/abs/2108.02351

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Variational Quantum Circuits for Quantum State Tomography

Autor: Liu, Yong, Wang, Dongyang, Xue, Shichuan, Huang, Anqi, Fu, Xiang, Qiang, Xiaogang, Xu, Ping, Huang, He-Liang, Deng, Mingtang, Guo, Chu, Yang, Xuejun, Wu, Junjie

Publikováno v: Phys. Rev. A 101, 052316 (2020)

Quantum state tomography is a key process in most quantum experiments. In this work, we employ quantum machine learning for state tomography. Given an unknown quantum state, it can be learned by maximizing the fidelity between the output of a variati

Externí odkaz: http://arxiv.org/abs/1912.07286

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General-purpose quantum circuit simulator with Projected Entangled-Pair States and the quantum supremacy frontier

Autor: Guo, Chu, Liu, Yong, Xiong, Min, Xue, Shichuan, Fu, Xiang, Huang, Anqi, Qiang, Xiaogang, Xu, Ping, Liu, Junhua, Zheng, Shenggen, Huang, He-Liang, Deng, Mingtang, Poletti, Dario, Bao, Wan-Su, Wu, Junjie

Publikováno v: Phys. Rev. Lett. 123, 190501 (2019)

Recent advances on quantum computing hardware have pushed quantum computing to the verge of quantum supremacy. Random quantum circuits are outstanding candidates to demonstrate quantum supremacy, which could be implemented on a quantum device that su

Externí odkaz: http://arxiv.org/abs/1905.08394

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