Benchmarking universal quantum gates via channel spectrum

Yanwu Gu (), Wei-Feng Zhuang, Xudan Chai and Dong E. Liu ()
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Yanwu Gu: Beijing Academy of Quantum Information Sciences
Wei-Feng Zhuang: Beijing Academy of Quantum Information Sciences
Xudan Chai: Beijing Academy of Quantum Information Sciences
Dong E. Liu: Beijing Academy of Quantum Information Sciences

Nature Communications, 2023, vol. 14, issue 1, 1-12

Abstract: Abstract Noise remains the major obstacle to scalable quantum computation. Quantum benchmarking provides key information on noise properties and is an important step for developing more advanced quantum processors. However, current benchmarking methods are either limited to a specific subset of quantum gates or cannot directly describe the performance of the individual target gate. To overcome these limitations, we propose channel spectrum benchmarking (CSB), a method to infer the noise properties of the target gate, including process fidelity, stochastic fidelity, and some unitary parameters, from the eigenvalues of its noisy channel. Our CSB method is insensitive to state-preparation and measurement errors, and importantly, can benchmark universal gates and is scalable to many-qubit systems. Unlike standard randomized schemes, CSB can provide direct noise information for both target native gates and circuit fragments, allowing benchmarking and calibration of global entangling gates and frequently used modules in quantum algorithms like Trotterized Hamiltonian evolution operator in quantum simulation.

Date: 2023
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DOI: 10.1038/s41467-023-41598-8

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