Mitigating quantum errors via truncated Neumann series

Wang, Kun; Chen, Yu-Ao; Wang, Xin

doi:10.1007/s11432-023-3786-1

Cited by 4 publications

References 70 publications

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Cross-platform comparison of arbitrary quantum processes

Zheng,

Yu,

Wang

2024

npj Quantum Inf

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In this work, we present a protocol for comparing the performance of arbitrary quantum processes executed on spatially or temporally disparate quantum platforms using Local Operations and Classical Communication (LOCC). The protocol involves sampling local unitary operators, which are then communicated to each platform via classical communication to construct quantum state preparation and measurement circuits. Subsequently, the local unitary operators are implemented on each platform, resulting in the generation of probability distributions of measurement outcomes. The max process fidelity is estimated from the probability distributions, which ultimately quantifies the relative performance of the quantum processes. Furthermore, we demonstrate that this protocol can be adapted for quantum process tomography. We apply the protocol to compare the performance of five quantum devices from IBM and the “Qianshi" quantum computer from Baidu via the cloud. The experimental results unveil two notable aspects: Firstly, the protocol adeptly compares the performance of the quantum processes implemented on different quantum computers. Secondly, the protocol scales, although still exponentially, much more favorably with the number of qubits, when compared to the full quantum process tomography. We view our work as a catalyst for collaborative efforts in cross-platform comparison of quantum computers.

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Cross-platform comparison of arbitrary quantum processes

Zheng,

Yu,

Wang

2024

npj Quantum Inf

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Detecting and eliminating quantum noise of quantum measurements

Tang,

Zheng,

Wang

2024

Phys. Scr.

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Quantum measurements are crucial for extracting information from quantum systems, but they are error-prone due to hardware imperfections in near-term devices. Measurement errors can be mitigated through classical post-processing, based on the assumption of a classical noise model. However, the coherence of quantum measurements leads to unavoidable quantum noise that defies this assumption. In this work, we introduce a two-stage procedure to systematically tackle such quantum noise in measurements. The idea is intuitive: we first detect and then eliminate quantum noise. In the first stage, inspired by coherence witness in the resource theory of quantum coherence, we design an efficient method to detect quantum noise. It works by fitting the difference between two measurement statistics to the Fourier series, where the statistics are obtained using maximally coherent states with relative phase and maximally mixed states as inputs. The fitting coefficients quantitatively benchmark quantum noise. In the second stage, we design various methods to eliminate quantum noise, inspired by the Pauli twirling technique. They work by executing randomly sampled Pauli gates before the measurement device and conditionally flipping the measurement outcomes in such a way that the effective measurement device contains only classical noise. We numerically demonstrate the two-stage procedure's feasibility on the Baidu Quantum Platform. Notably, the results reveal significant suppression of quantum noise in measurement devices and substantial enhancement in quantum computation accuracy. We highlight that the two-stage procedure complements existing measurement error mitigation techniques, and they together form a standard toolbox for manipulating measurement errors in near-term quantum devices.

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Universal Sampling Lower Bounds for Quantum Error Mitigation

Takagi,

Tajima,

2023

Phys. Rev. Lett.

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Mitigating quantum errors via truncated Neumann series

Cited by 4 publications

References 70 publications

Cross-platform comparison of arbitrary quantum processes

Cross-platform comparison of arbitrary quantum processes

Detecting and eliminating quantum noise of quantum measurements

Universal Sampling Lower Bounds for Quantum Error Mitigation

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