Strong Quantum Computational Advantage Using a Superconducting Quantum Processor

Yulin Wu; Wan-Su Bao; Sirui Cao; Fusheng Chen; Ming-Cheng Chen; Xiawei Chen; Tung-Hsun Chung; Hui Deng; Yajie Du; Daojin Fan; Ming Gong; Cheng Guo; Chu Guo; Shaojun Guo; Lianchen Han; Linyin Hong; He-Liang Huang; Yong-Heng Huo; Liping Li; Na Li; Shaowei Li; Yuan Li; Futian Liang; Chun Lin; Jin Lin; Haoran Qian; Dan Qiao; Hao Rong; Hong Su; Lihua Sun; Liangyuan Wang; Shiyu Wang; Dachao Wu; Yu Xu; Kai Yan; Weifeng Yang; Yang Yang; Yangsen Ye; Jianghan Yin; Chong Ying; Jiale Yu; Chen Zha; Cha Zhang; Haibin Zhang; Kaili Zhang; Yiming Zhang; Han Zhao; Youwei Zhao; Liang Zhou; Qingling Zhu; Chao-Yang Lu; Cheng-Zhi Peng; Xiaobo Zhu; Jian-Wei Pan

doi:10.1103/PhysRevLett.127.180501

Strong Quantum Computational Advantage Using a Superconducting Quantum Processor

Phys Rev Lett. 2021 Oct 29;127(18):180501. doi: 10.1103/PhysRevLett.127.180501.

Authors

Yulin Wu^{1

2

3}, Wan-Su Bao⁴, Sirui Cao^{1

2

3}, Fusheng Chen^{1

2

3}, Ming-Cheng Chen^{1

2

3}, Xiawei Chen², Tung-Hsun Chung^{1

2

3}, Hui Deng^{1

2

3}, Yajie Du², Daojin Fan^{1

2

3}, Ming Gong^{1

2

3}, Cheng Guo^{1

2

3}, Chu Guo^{1

2

3}, Shaojun Guo^{1

2

3}, Lianchen Han^{1

2

3}, Linyin Hong⁵, He-Liang Huang^{1

2

3

4}, Yong-Heng Huo^{1

2

3}, Liping Li², Na Li^{1

2

3}, Shaowei Li^{1

2

3}, Yuan Li^{1

2

3}, Futian Liang^{1

2

3}, Chun Lin⁶, Jin Lin^{1

2

3}, Haoran Qian^{1

2

3}, Dan Qiao², Hao Rong^{1

2

3}, Hong Su^{1

2

3}, Lihua Sun^{1

2

3}, Liangyuan Wang², Shiyu Wang^{1

2

3}, Dachao Wu^{1

2

3}, Yu Xu^{1

2

3}, Kai Yan², Weifeng Yang⁵, Yang Yang², Yangsen Ye^{1

2

3}, Jianghan Yin², Chong Ying^{1

2

3}, Jiale Yu^{1

2

3}, Chen Zha^{1

2

3}, Cha Zhang^{1

2

3}, Haibin Zhang², Kaili Zhang^{1

2

3}, Yiming Zhang^{1

2

3}, Han Zhao², Youwei Zhao^{1

2

3}, Liang Zhou⁵, Qingling Zhu^{1

2

3}, Chao-Yang Lu^{1

2

3}, Cheng-Zhi Peng^{1

2

3}, Xiaobo Zhu^{1

2

3}, Jian-Wei Pan^{1

2

3}

Affiliations

¹ Hefei National Laboratory for Physical Sciences at the Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China.
² Shanghai Branch, CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Shanghai 201315, China.
³ Shanghai Research Center for Quantum Sciences, Shanghai 201315, China.
⁴ Henan Key Laboratory of Quantum Information and Cryptography, Zhengzhou 450000, China.
⁵ QuantumCTek Co., Ltd., Hefei 230026, China.
⁶ Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.

PMID: 34767433
DOI: 10.1103/PhysRevLett.127.180501

Abstract

Scaling up to a large number of qubits with high-precision control is essential in the demonstrations of quantum computational advantage to exponentially outpace the classical hardware and algorithmic improvements. Here, we develop a two-dimensional programmable superconducting quantum processor, Zuchongzhi, which is composed of 66 functional qubits in a tunable coupling architecture. To characterize the performance of the whole system, we perform random quantum circuits sampling for benchmarking, up to a system size of 56 qubits and 20 cycles. The computational cost of the classical simulation of this task is estimated to be 2-3 orders of magnitude higher than the previous work on 53-qubit Sycamore processor [Nature 574, 505 (2019)NATUAS0028-083610.1038/s41586-019-1666-5. We estimate that the sampling task finished by Zuchongzhi in about 1.2 h will take the most powerful supercomputer at least 8 yr. Our work establishes an unambiguous quantum computational advantage that is infeasible for classical computation in a reasonable amount of time. The high-precision and programmable quantum computing platform opens a new door to explore novel many-body phenomena and implement complex quantum algorithms.