Quantum Brain
← Back to papers

Verifying Quantum Advantage Experiments with Multiple Amplitude Tensor Network Contraction.

Yong Liu, Yaojian Chen, Chu Guo, Jiawei Song, X. Shi, Lin Gan, Wenzhao Wu, Wei Wu, H. Fu, Xin Liu, Dexun Chen, Zhifeng Zhao, Guangwen Yang, Jiangang Gao·December 9, 2022·DOI: 10.1103/PhysRevLett.132.030601
PhysicsComputer ScienceMedicine

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

The quantum supremacy experiment, such as Google Sycamore [F. Arute et al., Nature (London) 574, 505 (2019).NATUAS0028-083610.1038/s41586-019-1666-5], poses a great challenge for classical verification due to the exponentially increasing compute cost. Using a new-generation Sunway supercomputer within 8.5 d, we provide a direct verification by computing 3×10^{6} exact amplitudes for the experimentally generated bitstrings, obtaining a cross-entropy benchmarking fidelity of 0.191% (the estimated value is 0.224%). The leap of simulation capability is built on a multiple-amplitude tensor network contraction algorithm which systematically exploits the "classical advantage" (the inherent "store-and-compute" operation mode of von Neumann machines) of current supercomputers, and a fused tensor network contraction algorithm which drastically increases the compute efficiency on heterogeneous architectures. Our method has a far-reaching impact in solving quantum many-body problems, statistical problems, as well as combinatorial optimization problems.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.