How to Design a Classically Difficult Random Quantum Circuit for Quantum Computational Advantage Experiments

Author:

Huang He-Liang123,Zhao Youwei23,Guo Chu4

Affiliation:

1. Henan Key Laboratory of Quantum Information and Cryptography, Zhengzhou, China.

2. Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences, University of Science and Technology of China, Hefei, China.

3. Shanghai Research Center for Quantum Science and CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Shanghai, China.

4. Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education, Department of Physics and Synergetic Innovation Center for Quantum Effects and Applications, Hunan Normal University, Changsha, China.

Abstract

Quantum computational advantage is a critical milestone for near-term quantum technologies and a crucial step toward building practical quantum computers. Recent successful demonstrations of quantum computational advantage owe much to specially designed random quantum circuit (RQC) protocols that enable hardware-friendly implementation and, more importantly, pose great challenges for classical simulation. Here, we report an automated protocol-design approach for determining the optimal RQC in the Zuchongzhi quantum computational advantage experiment. Without a carefully designed protocol, the classical simulation cost of the Zuchongzhi 56-qubit 20-cycle RQC experiment would not be considerably higher than Google’s 53-qubit 20-cycle experiment, even though more qubits are involved. For Google’s latest RQC experiment using 70 qubits and 24 cycles, we estimate that the classical simulation cost can be increased by at least one order of magnitude using the proposed approach. The proposed method can be applied to generic planar quantum processor architectures and addresses realistic imperfections such as processor defects, underpinning quantum computational advantage experiments in future generations of quantum processors.

Funder

Youth Talent Lifting Project

National Natural Science Foundation of China

Open Research Fund from State Key Laboratory of High Performance Computing of China

Publisher

American Association for the Advancement of Science (AAAS)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3