Quantum computational advantage via 60-qubit 24-cycle random circuit sampling

• Published in: Science bulletin (Beijing) Vol. 67; no. 3; pp. 240 - 245
• Main Authors: Zhu, Qingling, Cao, Sirui, Chen, Fusheng, Chen, Ming-Cheng, Chen, Xiawei, Chung, Tung-Hsun, Deng, Hui, Du, Yajie, Fan, Daojin, Gong, Ming, Guo, Cheng, Guo, Chu, Guo, Shaojun, Han, Lianchen, Hong, Linyin, Huang, He-Liang, Huo, Yong-Heng, Li, Liping, Li, Na, Li, Shaowei, Li, Yuan, Liang, Futian, Lin, Chun, Lin, Jin, Qian, Haoran, Qiao, Dan, Rong, Hao, Su, Hong, Sun, Lihua, Wang, Liangyuan, Wang, Shiyu, Wu, Dachao, Wu, Yulin, Xu, Yu, Yan, Kai, Yang, Weifeng, Yang, Yang, Ye, Yangsen, Yin, Jianghan, Ying, Chong, Yu, Jiale, Zha, Chen, Zhang, Cha, Zhang, Haibin, Zhang, Kaili, Zhang, Yiming, Zhao, Han, Zhao, Youwei, Zhou, Liang, Lu, Chao-Yang, Peng, Cheng-Zhi, Zhu, Xiaobo, Pan, Jian-Wei
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15-02-2022
• Subjects: Quantum computation; Quantum information; Quantum physics; Superconducting quantum computing; Superconducting qubit; Superconducting qubit; Quantum computation; Quantum information; Superconducting quantum computing; Quantum physics
• ISSN: 2095-9273
• DOI: 10.1016/j.scib.2021.10.017

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To ensure a long-term quantum computational advantage, the quantum hardware should be upgraded to withstand the competition of continuously improved classical algorithms and hardwares. Here, we demonstrate a superconducting quantum computing systems Zuchongzhi 2.1, which has 66 qubits in a two-dimensional array in a tunable coupler architecture. The readout fidelity of Zuchongzhi 2.1 is considerably improved to an average of 97.74%. The more powerful quantum processor enables us to achieve larger-scale random quantum circuit sampling, with a system scale of up to 60 qubits and 24 cycles, and fidelity of FXEB=(3.66±0.345)×10-4. The achieved sampling task is about 6 orders of magnitude more difficult than that of Sycamore [Nature 574, 505 (2019)] in the classic simulation, and 3 orders of magnitude more difficult than the sampling task on Zuchongzhi 2.0 [arXiv:2106.14734 (2021)]. The time consumption of classically simulating random circuit sampling experiment using state-of-the-art classical algorithm and supercomputer is extended to tens of thousands of years (about 4.8×104 years), while Zuchongzhi 2.1 only takes about 4.2 h, thereby significantly enhancing the quantum computational advantage.