Zobrazeno 1 - 10
of 433
pro vyhledávání: '"Wu, Yu‐Chun"'
Optimizing the frequency configuration of qubits and quantum gates in superconducting quantum chips presents a complex NP-complete optimization challenge. This process is critical for enabling practical control while minimizing decoherence and suppre
Externí odkaz:
http://arxiv.org/abs/2412.01183
Autor:
Xue, Cheng, Xu, Xiao-Fan, Zhuang, Xi-Ning, Sun, Tai-Ping, Wang, Yun-Jie, Tan, Ming-Yang, Ye, Chuang-Chao, Liu, Huan-Yu, Wu, Yu-Chun, Chen, Zhao-Yun, Guo, Guo-Ping
Nonlinear partial differential equations (PDEs) are crucial for modeling complex fluid dynamics and are foundational to many computational fluid dynamics (CFD) applications. However, solving these nonlinear PDEs is challenging due to the vast computa
Externí odkaz:
http://arxiv.org/abs/2411.06759
Autor:
Liu, Huan-Yu, Zhuang, Xi-Ning, Wang, Chao, Dou, Meng-Han, Chen, Zhao-Yun, Xue, Cheng, Wu, Yu-Chun, Guo, Guo-Ping
In recent years, quantum computation has been rapidly advancing, driving a technological revolution with significant potential across various sectors, particularly in finance. Despite this, the insurance industry, an essential tool for mitigating unf
Externí odkaz:
http://arxiv.org/abs/2410.20841
Autor:
Zhang, Jiaxuan, Chen, Zhao-Yun, Li, Jia-Ning, Wei, Tian-Hao, Liu, Huan-Yu, Zhuang, Xi-Ning, Li, Qing-Song, Wu, Yu-Chun, Guo, Guo-Ping
Large-scale quantum computation requires to be performed in the fault-tolerant manner. One crucial issue of fault-tolerant quantum computing (FTQC) is reducing the overhead of implementing logical gates. Recently proposed correlated decoding and ``al
Externí odkaz:
http://arxiv.org/abs/2410.16963
HiMA: Hierarchical Quantum Microarchitecture for Qubit-Scaling and Quantum Process-Level Parallelism
Autor:
Zhou, Qi, Mei, Zi-Hao, Shi, Han-Qing, Guo, Liang-Liang, Yang, Xiao-Yan, Wang, Yun-Jie, Xu, Xiao-Fan, Xue, Cheng, Kong, Wei-Cheng, Wang, Jun-Chao, Wu, Yu-Chun, Chen, Zhao-Yun, Guo, Guo-Ping
Quantum computing holds immense potential for addressing a myriad of intricate challenges, which is significantly amplified when scaled to thousands of qubits. However, a major challenge lies in developing an efficient and scalable quantum control sy
Externí odkaz:
http://arxiv.org/abs/2408.11311
Autor:
Zhang, Sheng, Duan, Peng, Wang, Yun-Jie, Wang, Tian-Le, Wang, Peng, Zhao, Ren-Ze, Yang, Xiao-Yan, Zhao, Ze-An, Guo, Liang-Liang, Chen, Yong, Zhang, Hai-Feng, Du, Lei, Tao, Hao-Ran, Li, Zhi-Fei, Wu, Yuan, Jia, Zhi-Long, Kong, Wei-Cheng, Chen, Zhao-Yun, Wu, Yu-Chun, Guo, Guo-Ping
In the NISQ era, achieving large-scale quantum computing demands compact circuits to mitigate decoherence and gate error accumulation. Quantum operations with diverse degrees of freedom hold promise for circuit compression, but conventional approache
Externí odkaz:
http://arxiv.org/abs/2407.06687
Autor:
Wang, Shengbin, Li, Guihui, Chen, Zhaoyun, Wang, Peng, Dou, Menghan, Zheng, Haiyong, Wang, Zhimin, Gu, Yongjian, Wu, Yu-Chun, Guo, Guo-Ping
Solving combinatorial optimization problems using variational quantum algorithms (VQAs) represents one of the most promising applications in the NISQ era. However, the limited trainability of VQAs could hinder their scalability to large problem sizes
Externí odkaz:
http://arxiv.org/abs/2407.05589
Autor:
Chen, Zhao-Yun, Ma, Teng-Yang, Ye, Chuang-Chao, Xu, Liang, Tan, Ming-Yang, Zhuang, Xi-Ning, Xu, Xiao-Fan, Wang, Yun-Jie, Sun, Tai-Ping, Chen, Yong, Du, Lei, Guo, Liang-Liang, Zhang, Hai-Feng, Tao, Hao-Ran, Wang, Tian-Le, Yang, Xiao-Yan, Zhao, Ze-An, Wang, Peng, Zhang, Sheng, Zhang, Chi, Zhao, Ren-Ze, Jia, Zhi-Long, Kong, Wei-Cheng, Dou, Meng-Han, Wang, Jun-Chao, Liu, Huan-Yu, Xue, Cheng, Zhang, Peng-Jun-Yi, Huang, Sheng-Hong, Duan, Peng, Wu, Yu-Chun, Guo, Guo-Ping
Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including an iterati
Externí odkaz:
http://arxiv.org/abs/2406.06063
Autor:
Zhuang, Xi-Ning, Chen, Zhao-Yun, Xue, Cheng, Xu, Xiao-Fan, Wang, Chao, Liu, Huan-Yu, Sun, Tai-Ping, Wang, Yun-Jie, Wu, Yu-Chun, Guo, Guo-Ping
Quantum machine learning has demonstrated significant potential in solving practical problems, particularly in statistics-focused areas such as data science and finance. However, challenges remain in preparing and learning statistical models on a qua
Externí odkaz:
http://arxiv.org/abs/2406.01335
Autor:
Liu, Huan-Yu, Lin, Xiaoshui, Chen, Zhao-Yun, Xue, Cheng, Sun, Tai-Ping, Li, Qing-Song, Zhuang, Xi-Ning, Wang, Yun-Jie, Wu, Yu-Chun, Gong, Ming, Guo, Guo-Ping
The rapid development of quantum computers has enabled demonstrations of quantum advantages on various tasks. However, real quantum systems are always dissipative due to their inevitable interaction with the environment, and the resulting non-unitary
Externí odkaz:
http://arxiv.org/abs/2405.20712