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arXiv · 2309.05147

Fully scalable randomized benchmarking without motion reversal

Jordan Hines·Daniel Hothem·Robin Blume-Kohout·Birgitta Whaley·Timothy Proctor
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Abstract

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.

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Jordan Hines, Daniel Hothem, Robin Blume-Kohout, Birgitta Whaley, Timothy Proctor. 2023-09-10. Fully scalable randomized benchmarking without motion reversal. https://doi.org/10.1103/prxquantum.5.030334

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