Quantum Computational Advantage via 60-Qubit 24-Cycle Random Circuit Sampling

To ensure a long-term quantum computational advantage, the quantum hardware should be upgraded to withstand the competition of continuously improved classical algorithms and hardwares. Here, we demonstrate a superconducting quantum computing systems $\mathit{\text{Zuchongzhi}}$ 2.1, which has 66 qubits in a two-dimensional array in a tunable coupler architecture. The readout fidelity of $\mathit{\text{Zuchongzhi}}$ 2.1 is considerably improved to an average of 97.74%. The more powerful quantum processor enables us to achieve larger-scale random quantum circuit sampling, with a system scale of up to 60 qubits and 24 cycles. The achieved sampling task is about 6 orders of magnitude more difficult than that of Sycamore [Nature $\mathbf{\text{574}}$, 505 (2019)] in the classic simulation, and 3 orders of magnitude more difficult than the sampling task on $\mathit{\text{Zuchongzhi}}$ 2.0 [arXiv:2106.14734 (2021)]. The time consumption of classically simulating random circuit sampling experiment using state-of-the-art classical algorithm and supercomputer is extended to tens of thousands of years (about $4.8\times {10}^4$ years), while $\mathit{\text{Zuchongzhi}}$ 2.1 only takes about 4.2 hours, thereby significantly enhancing the quantum computational advantage.