Zobrazeno 1 - 10
of 591
pro vyhledávání: '"Huang, Anqi"'
The decoy-state method is a prominent approach to enhance the performance of quantum key distribution (QKD) systems that operate with weak coherent laser sources. Due to the limited transmissivity of single photons in optical fiber, current experimen
Externí odkaz:
http://arxiv.org/abs/2411.00709
Autor:
Peng, Qingquan, Chen, Jiu-Peng, Xing, Tianyi, Wang, Dongyang, Wang, Yizhi, Liu, Yang, Huang, Anqi
The twin-field class quantum key distribution (TF-class QKD) has experimentally demonstrated the ability to surpass the fundamental rate-distance limit without requiring a quantum repeater, as a revolutional milestone. In TF-class QKD implementation,
Externí odkaz:
http://arxiv.org/abs/2408.09318
Autor:
Xing, Tianyi, Liu, Junxuan, Zhang, Likang, Wang, Min-Yan, Li, Yu-Huai, Liu, Ruiyin, Peng, Qingquan, Wang, Dongyang, Wang, Yaxuan, Liu, Hongwei, Li, Wei, Cao, Yuan, Huang, Anqi
One of the most significant vulnerabilities in the source unit of quantum key distribution (QKD) is the correlation between quantum states after modulation, which shall be characterized and evaluated for its practical security performance. In this wo
Externí odkaz:
http://arxiv.org/abs/2408.07960
The intensity correlations due to imperfect modulation during the quantum-state preparation in a measurement-device-independent quantum key distribution (MDI QKD) system compromise its security performance. Therefore, it is crucial to assess the impa
Externí odkaz:
http://arxiv.org/abs/2408.08011
Autor:
Zhang, Xinfang, Wu, Zhihao, White, Gregory A. L., Xiang, Zhongcheng, Hu, Shun, Peng, Zhihui, Liu, Yong, Zheng, Dongning, Fu, Xiang, Huang, Anqi, Poletti, Dario, Modi, Kavan, Wu, Junjie, Deng, Mingtang, Guo, Chu
The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning
Externí odkaz:
http://arxiv.org/abs/2312.06062
Autor:
Makarov, Vadim, Abrikosov, Alexey, Chaiwongkhot, Poompong, Fedorov, Aleksey K., Huang, Anqi, Kiktenko, Evgeny, Petrov, Mikhail, Ponosova, Anastasiya, Ruzhitskaya, Daria, Tayduganov, Andrey, Trefilov, Daniil, Zaitsev, Konstantin
A commercial quantum key distribution (QKD) system needs to be formally certified to enable its wide deployment. The certification should include the system's robustness against known implementation loopholes and attacks that exploit them. Here we re
Externí odkaz:
http://arxiv.org/abs/2310.20107
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
Autor:
Chen, Xiong-Hui, Ye, Junyin, Zhao, Hang, Li, Yi-Chen, Shi, Haoran, Xu, Yu-Yan, Ye, Zhihao, Yang, Si-Hang, Huang, Anqi, Xu, Kai, Zhang, Zongzhang, Yu, Yang
Imitation learning (IL) enables agents to mimic expert behaviors. Most previous IL techniques focus on precisely imitating one policy through mass demonstrations. However, in many applications, what humans require is the ability to perform various ta
Externí odkaz:
http://arxiv.org/abs/2310.05712
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
We propose a high-rate scheme for discretely-modulated continuous-variable quantum key distribution (DM CVQKD) using quantum machine learning technologies, which divides the whole CVQKD system into three parts, i.e., the initialization part that is u
Externí odkaz:
http://arxiv.org/abs/2308.03283