Benchmarking universal quantum gates via channel spectrum

被引:6
作者
Gu, Yanwu [1 ,2 ]
Zhuang, Wei-Feng [1 ]
Chai, Xudan [1 ,2 ]
Liu, Dong E. [1 ,2 ,3 ,4 ]
机构
[1] Beijing Acad Quantum Informat Sci, Beijing 100193, Peoples R China
[2] Tsinghua Univ, Dept Phys, State Key Lab Low Dimens Quantum Phys, Beijing 100084, Peoples R China
[3] Frontier Sci Ctr Quantum Informat, Beijing 100184, Peoples R China
[4] Hefei Natl Lab, Hefei 230088, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
COMPUTATION; SIMULATION; SUMS;
D O I
10.1038/s41467-023-41598-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. Performing quantum computing in the NISQ era requires reliable information on the gate noise characteristics and their performance benchmarks. Here, the authors show how to estimate the individual noise properties of any quantum process from the noisy eigenvalues of its corresponding quantum channel.
引用
收藏
页数:12
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