Strong Quantum Computational Advantage Using a Superconducting Quantum Processor.

By Yulin Wu, Wansu Bao, S. Cao, Fusheng Chen, Ming-Cheng Chen, Xiawei Chen, T. Chung, H. Deng, Yajie Du, Daojin Fan and 44 more. Physical Review Letters, 2021

971 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/f8964f44103f6a504e1582e94be22290ecd5a1e8

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Citations in the corpus

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The randomized measurement toolbox (2022, background): “Variations of this idea are known as cross-entropy benchmarking 83–85 and random circuit sampling 86,87 .”
A Race-Track Trapped-Ion Quantum Processor (2023, background): “Also, it has been run on a variety of quantum computers in the context of quantum advantage demonstrations [55, 61, 62], making it useful from the standpoint of crossplatform comparisons.”
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