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PRX Quantum
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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PRX Quantum
Article . 2022
Data sources: DOAJ
https://dx.doi.org/10.48550/ar...
Article . 2022
License: CC BY
Data sources: Datacite
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Quantum Error Mitigation via Matrix Product Operators

Authors: Yuchen Guo; Shuo Yang;

Quantum Error Mitigation via Matrix Product Operators

Abstract

In the era of noisy intermediate-scale quantum (NISQ) devices, the number of controllable hardware qubits is insufficient to implement quantum error correction (QEC). As an alternative, quantum error mitigation (QEM) can suppress errors in measurement results via repeated experiments and postprocessing of data. Typical techniques for error mitigation, e.g., the quasi-probability decomposition method, ignore correlated errors between different gates. Here, we introduce a QEM method based on the matrix product operator (MPO) representation of a quantum circuit that can characterize the noise channel with polynomial complexity. Our technique is demonstrated on a $\rm{depth}=20$ fully parallel quantum circuit of up to $N_q=20$ qubits undergoing local and global noise. The circuit error is reduced by several times with only a small bond dimension $D^{\prime} = 1$ for the noise channel. The MPO representation increases the accuracy of modeling noise without consuming more experimental resources, which improves the QEM performance and broadens its scope of application. Our method is hopeful of being applied to circuits in higher dimensions with more qubits and deeper depth.

13 pages, 13 figures, to appear in PRX Quantum

Related Organizations
Keywords

QA76.75-76.765, Quantum Physics, Condensed Matter - Mesoscale and Nanoscale Physics, Physics, QC1-999, Mesoscale and Nanoscale Physics (cond-mat.mes-hall), FOS: Physical sciences, Computer software, Quantum Physics (quant-ph)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Top 10%
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gold