  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 new method to
classically solve this problem by contracting the corresponding tensor network
just once, and is massively more efficient than existing methods in obtaining 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
one million uncorrelated bitstrings $\{\mathbf s\}$ which are sampled from a
distribution $\hat P(\mathbf s)=|\hat \psi(\mathbf s)|^2$, where the
approximate state $\hat \psi$ has fidelity $F\approx 0.0037$. The whole
computation has cost about $15$ hours on a computational cluster with $512$
GPUs. The obtained one million samples, the contraction code and contraction
order is 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.
