Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications

Abstract Noise in quantum hardware remains the biggest roadblock for the implementation of quantum computers. To fight the noise in the practical application of near-term quantum computers, instead of relying on quantum error correction which requires large qubit overhead, we turn to quantum error m...

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Autor principal:	Zhenyu Cai
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/65f7a2a5ad8b4483b6e9031a36829922
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spelling	oai:doaj.org-article:65f7a2a5ad8b4483b6e9031a368299222021-12-02T14:47:39ZMulti-exponential error extrapolation and combining error mitigation techniques for NISQ applications10.1038/s41534-021-00404-32056-6387https://doaj.org/article/65f7a2a5ad8b4483b6e9031a368299222021-05-01T00:00:00Zhttps://doi.org/10.1038/s41534-021-00404-3https://doaj.org/toc/2056-6387Abstract Noise in quantum hardware remains the biggest roadblock for the implementation of quantum computers. To fight the noise in the practical application of near-term quantum computers, instead of relying on quantum error correction which requires large qubit overhead, we turn to quantum error mitigation, in which we make use of extra measurements. Error extrapolation is an error mitigation technique that has been successfully implemented experimentally. Numerical simulation and heuristic arguments have indicated that exponential curves are effective for extrapolation in the large circuit limit with an expected circuit error count around unity. In this Article, we extend this to multi-exponential error extrapolation and provide more rigorous proof for its effectiveness under Pauli noise. This is further validated via our numerical simulations, showing orders of magnitude improvements in the estimation accuracy over single-exponential extrapolation. Moreover, we develop methods to combine error extrapolation with two other error mitigation techniques: quasi-probability and symmetry verification, through exploiting features of these individual techniques. As shown in our simulation, our combined method can achieve low estimation bias with a sampling cost multiple times smaller than quasi-probability while without needing to be able to adjust the hardware error rate as required in canonical error extrapolation.Zhenyu CaiNature PortfolioarticlePhysicsQC1-999Electronic computers. Computer scienceQA75.5-76.95ENnpj Quantum Information, Vol 7, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95
spellingShingle	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95 Zhenyu Cai Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
description	Abstract Noise in quantum hardware remains the biggest roadblock for the implementation of quantum computers. To fight the noise in the practical application of near-term quantum computers, instead of relying on quantum error correction which requires large qubit overhead, we turn to quantum error mitigation, in which we make use of extra measurements. Error extrapolation is an error mitigation technique that has been successfully implemented experimentally. Numerical simulation and heuristic arguments have indicated that exponential curves are effective for extrapolation in the large circuit limit with an expected circuit error count around unity. In this Article, we extend this to multi-exponential error extrapolation and provide more rigorous proof for its effectiveness under Pauli noise. This is further validated via our numerical simulations, showing orders of magnitude improvements in the estimation accuracy over single-exponential extrapolation. Moreover, we develop methods to combine error extrapolation with two other error mitigation techniques: quasi-probability and symmetry verification, through exploiting features of these individual techniques. As shown in our simulation, our combined method can achieve low estimation bias with a sampling cost multiple times smaller than quasi-probability while without needing to be able to adjust the hardware error rate as required in canonical error extrapolation.
format	article
author	Zhenyu Cai
author_facet	Zhenyu Cai
author_sort	Zhenyu Cai
title	Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
title_short	Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
title_full	Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
title_fullStr	Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
title_full_unstemmed	Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
title_sort	multi-exponential error extrapolation and combining error mitigation techniques for nisq applications
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/65f7a2a5ad8b4483b6e9031a36829922
work_keys_str_mv	AT zhenyucai multiexponentialerrorextrapolationandcombiningerrormitigationtechniquesfornisqapplications
_version_	1718389513366011904

Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications

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