Benchmarking Quantum Processor Performance at Scale
David C. McKay, Ian Hincks, Emily J. Pritchett, Malcolm, Carroll, Luke C. G. Govia, Seth T. Merkel

TL;DR
This paper introduces a scalable, layer-based benchmarking method for large quantum processors that measures two-qubit gate fidelity, providing a continuous and quantitative assessment of device performance at scale.
Contribution
The authors develop a new benchmarking protocol using simultaneous direct randomized benchmarking to evaluate layer fidelity, sensitive to crosstalk, applicable to large-scale quantum devices.
Findings
Measured layer fidelity of 0.26 and 0.19 on 80 and 100 qubits respectively
Achieved layer fidelity of 0.61 and 0.26 on 133 qubits for two different processors
Defined error per layered gate (EPLG) as a scalable, device-independent metric
Abstract
As quantum processors grow, new performance benchmarks are required to capture the full quality of the devices at scale. While quantum volume is an excellent benchmark, it focuses on the highest quality subset of the device and so is unable to indicate the average performance over a large number of connected qubits. Furthermore, it is a discrete pass/fail and so is not reflective of continuous improvements in hardware nor does it provide quantitative direction to large-scale algorithms. For example, there may be value in error mitigated Hamiltonian simulation at scale with devices unable to pass strict quantum volume tests. Here we discuss a scalable benchmark which measures the fidelity of a connecting set of two-qubit gates over qubits by measuring gate errors using simultaneous direct randomized benchmarking in disjoint layers. Our layer fidelity can be easily related to…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Advancements in Semiconductor Devices and Circuit Design · Low-power high-performance VLSI design
