We study the problem of generating independent samples from the output distribution of Google’s Sycamore quantum circuits with a target fidelity, which is believed to be beyond the reach of classical supercomputers and has been used to demonstrate quantum supremacy. We propose a method to classically solve this problem by contracting the corresponding tensor network just once, and is massively more efficient than existing methods in generating a large number of uncorrelated samples with a target fidelity. For the Sycamore quantum supremacy circuit with 53 qubits and 20 cycles, we have generated $1\times {10}^6$ uncorrelated bitstrings $\mathbf{s}$ which are sampled from a distribution $\widehat{P}(\mathbf{s})=|\widehat{\psi }(\mathbf{s}){|}^2$, where the approximate state $\widehat{\psi }$ has fidelity $F\approx 0.0037$. The whole computation has cost about 15 h on a computational cluster with 512 GPUs. The obtained $1\times {10}^6$ samples, the contraction code and contraction order are made public. If our algorithm could be implemented with high efficiency on a modern supercomputer with ExaFLOPS performance, we estimate that ideally, the simulation would cost a few dozens of seconds, which is faster than Google’s quantum hardware.

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• Quantum computation
• Tensor network methods