Large-Scale Quantum Device Benchmarking via LXEB with Particle-Number-Conserving Random Quantum Circuits

TL;DR

This paper introduces a particle-number conservation constraint in random quantum circuits to enable classical simulation and benchmarking of large-scale quantum devices exceeding 100 qubits, overcoming previous computational limitations.

Contribution

It proposes a novel particle-number-conserving quantum circuit model and a modified LXEB method, MLXEB, for efficient classical simulation and fidelity estimation of large quantum systems.

Findings

Particle-number conservation reduces Hilbert space size, enabling classical simulation of >100 qubits.

MLXEB provides accurate fidelity estimates under particle-number-conserving dynamics.

Numerical simulations validate the effectiveness of the proposed benchmarking approach.

Abstract

Linear cross-entropy benchmarking (LXEB) with random quantum circuits is a standard method for evaluating quantum computers. However, LXEB requires classically simulating the ideal output distribution of a given quantum circuit with high numerical precision, which becomes infeasible beyond approximately 50 qubits, even on state-of-the-art supercomputers. As a result, LXEB cannot be directly applied to evaluate large-scale quantum devices, which now exceed 100 qubits and continue to grow rapidly in size. To address this limitation, we introduce a constraint known as particle-number conservation into the random quantum circuits used for benchmarking. This restriction significantly reduces the size of the Hilbert space for a fixed particle number, enabling classical simulations of circuits with over 100 qubits when the particle number is $O(1)$. Furthermore, we propose a modified version of LXEB, called MLXEB, which enables fidelity estimation under particle-number-conserving dynamics. Through numerical simulations, we investigate the conditions under which MLXEB provides accurate fidelity estimates.