We introduce binary randomized benchmarking (BiRB), a protocol that streamlines traditional RB by using circuits consisting almost entirely of i.i.d. layers of gates. BiRB reliably and efficiently extracts the average error rate of a Clifford gate set by sending tensor product eigenstates of random Pauli operators through random circuits with i.i.d. layers. Unlike existing RB methods, BiRB does not use motion reversal circuits -- i.e., circuits that implement the identity (or a Pauli) operator -- which simplifies both the method and the theory proving its reliability. Furthermore, this simplicity enables scaling BiRB to many more qubits than the most widely-used RB methods.
@article{arxiv.2309.05147,
title = {Fully scalable randomized benchmarking without motion reversal},
author = {Jordan Hines and Daniel Hothem and Robin Blume-Kohout and Birgitta Whaley and Timothy Proctor},
journal= {arXiv preprint arXiv:2309.05147},
year = {2024}
}
Comments
9 pages + appendices, 5 figures, v2: Close to published version, fixed typos in theory section