How to Design a Classically Difficult Random Quantum Circuit for Quantum Computational Advantage Experiments

TL;DR

This paper introduces an automated protocol design method to optimize random quantum circuits, significantly increasing the classical simulation difficulty of quantum advantage experiments, thereby advancing the validation of quantum computational supremacy.

Contribution

The paper presents a novel automated approach for designing random quantum circuits that enhances their classical simulation complexity, applicable to realistic quantum hardware architectures.

Findings

Increased classical simulation cost for Zuchongzhi's 56-qubit experiment.

Estimated at least tenfold increase in simulation difficulty for Google's 70-qubit experiment.

Method is adaptable to various planar quantum processor architectures.

Abstract

Quantum computational advantage is a critical milestone for near-term quantum technologies and an essential step towards building practical quantum computers. Recent successful demonstrations of quantum computational advantage owe much to specifically designed random quantum circuit (RQC) protocols that enable hardware-friendly implementation and, more importantly, pose great challenges for classical simulation. Here, we report the automated protocol design approach used for finding the optimal RQC in the \textit{Zuchongzhi} quantum computational advantage experiment [Phys. Rev. Lett. 127 (18), 180501 (2021)]. Without a carefully designed protocol, the classical simulation cost of the \textit{Zuchongzhi}'s 56-qubit 20-cycle RQC experiment would not be considerably higher than Google's 53-qubit 20-cycle experiment, even though more qubits are involved. For Google's latest RQC experiment using $70$ qubits and $24$ cycles [arXiv:2304.11119 (2023)], we estimate that its classical simulation cost can be increased by at least one order of magnitude using our approach. The proposed method can be applied to generic planar quantum processor architectures and addresses realistic imperfections such as processor defects, underpinning quantum computational advantage experiments in future generations of quantum processors.