Large-scale quantum device benchmarking via LXEB with particle-number-conserving random quantum circuits
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.
Type
Publication
Physical Review Research

Authors
Associate Professor
Hiroshi Ueda is an Associate Professor at the Center for Quantum Information and Quantum Biology (QIQB), The University of Osaka.
His research focuses on tensor network methods, quantum many-body physics, quantum algorithms, and quantum-classical hybrid computation. He develops theoretical and numerical approaches for understanding quantum many-body systems and for designing quantum algorithms inspired by tensor network structures.