Establishing a New Benchmark in Quantum Computational Advantage with 105-qubit Zuchongzhi 3.0 Processor.
Dongxin Gao, D. Fan, C. Zha, Jiahao Bei, Guoqing Cai, J. Cai, S. Cao, Fusheng Chen, Jiang Chen, Kefu Chen, Xiawei Chen, Xiqing Chen, Zhe Chen, Zhiyuan Chen, Zihua Chen, Wenhao Chu, Hui Deng, Zhibin Deng, Pei Ding, Xun Ding, Zhuzhengqi Ding, Shuai Dong, Yupeng Dong, Bo Fan, Yu Fu, Song-Ming Gao, Lei Ge, M. Gong, J. Gui, Cheng Guo, Shaojun Guo, Xiaoyan Guo, Lianchen Han, Tan He, Linyin Hong, Yisen Hu, He-Liang Huang, Yongting Huo, Tao Jiang, Zuokai Jiang, Hong-Yan Jin, Yunxiang Leng, Dayu Li, Dongdong Li, Fang-Ke Li, Jiaqi Li, Jinjin Li, Junyan Li, Junyun Li, Na Li, Shaowei Li, Wei Li, Yuhuai Li, Yuan Li, Futian Liang, Xue-yan Liang, Na Liao, Jin Lin, Weiping Lin, Dailin Liu, Hongxiu Liu, Maliang Liu, Xinyu Liu, Xuemeng Liu, Yanchen Liu, Hao Lou, Yuwei Ma, Lingxin Meng, Hao Mou, Kailiang Nan, Binghan Nie, M. Nie, Jie Ning, Le Niu, Wenyi Peng, H. Qian, H. Rong, Tao Rong, Hui Shen, Qiong Shen, Hong-ying Su, Feifan Su, Chenyin Sun, Lian-Xu Sun, Tianzuo Sun, Yingxiu Sun, Yimeng Tan, Jun Tan, Longyue Tang, Wenbing Tu, Cai-Yu Wan, Jiafei Wang, Biao Wang, Chang Wang, Chen Wang, Chu Wang, Jian Wang, Lian-Qiang Wang, Rui Wang, Sheng-li Wang, Xiaomin Wang, Xinzhe Wang, Xunxun Wang, Yeru Wang, Zuolin Wei, Jia-Ning Wei, Dachao Wu, Gang Wu, Jin Yu Wu, Sheng-Cai Wu, Yulin Wu, Shiyong Xie, Lianjie Xin, Yu Xu, Chun Xue, Kai Yan, Weifeng Yang, Xinpeng Yang, Yang Yang, Yang-zhi Ye, Z. Ye, C. Ying, Jiale Yu, Qi-Ming Yu, Wenhu Yu, Xiangdong Zeng, Shaoyu Zhan, Feifei Zhang, Haibin Zhang, Kaili Zhang, Pan Zhang, Wen Zhang, Yiming Zhang, Yongzhuo Zhang, Lixiang Zhang, Guming Zhao, Peng Zhao, Xianhe Zhao, Xintao Zhao, You-Wei Zhao, Zhong Zhao, Luyuan Zheng, Fei Zhou, Liang Zhou, Naibin Zhou, Naibin Zhou, Shifeng Zhou, Shuang Zhou, Zhengxiao Zhou, Chen-Xi Zhu, Qi-Kun Zhu, Gui-Zhou Zou, Haonan Zou, Qiang Zhang, Chaochun Lu, Chengwangli Peng, Xiaobo Zhu, Jian-Wei Pan·December 16, 2024·DOI: 10.1103/physrevlett.134.090601
MedicinePhysics
AI Breakdown
Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.
Abstract
In the relentless pursuit of quantum computational advantage, we present a significant advancement with the development of Zuchongzhi 3.0. This superconducting quantum computer prototype, comprising 105 qubits, achieves high operational fidelities, with single-qubit gates, two-qubit gates, and readout fidelity at 99.90%, 99.62%, and 99.13%, respectively. Our experiments with an 83-qubit, 32-cycle random circuit sampling on the Zuchongzhi 3.0 highlight its superior performance, achieving 1×10^{6} samples in just a few hundred seconds. This task is estimated to be infeasible on the most powerful classical supercomputers, Frontier, which would require approximately 5.9×10^{9} yr to replicate the task. This leap in processing power places the classical simulation cost 6 orders of magnitude beyond Google's SYC-67 and SYC-70 experiments [Morvan et al., Nature 634, 328 (2024)10.1038/s41586-024-07998-6], firmly establishing a new benchmark in quantum computational advantage. Our work not only advances the frontiers of quantum computing but also lays the groundwork for a new era where quantum processors play an essential role in tackling sophisticated real-world challenges.