Quantum parameter estimation with general dynamics

New tools for quantum parameter estimation: more general and more efficient Measuring the parameters of interest with high precision is essential for science and technology, where the main quest is to find the ultimate precision limit and the optimal schemes to attain it. For a general noisy dynamic...

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Autores principales:	Haidong Yuan, Chi-Hang Fred Fung
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Physics QC1-999 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/3ddb8308cba44a04976bcb089d0c3078
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spelling	oai:doaj.org-article:3ddb8308cba44a04976bcb089d0c30782021-12-02T12:33:55ZQuantum parameter estimation with general dynamics10.1038/s41534-017-0014-62056-6387https://doaj.org/article/3ddb8308cba44a04976bcb089d0c30782017-04-01T00:00:00Zhttps://doi.org/10.1038/s41534-017-0014-6https://doaj.org/toc/2056-6387New tools for quantum parameter estimation: more general and more efficient Measuring the parameters of interest with high precision is essential for science and technology, where the main quest is to find the ultimate precision limit and the optimal schemes to attain it. For a general noisy dynamics, the identification of the ultimate precision limit usually requires certain assumptions. In this work, Haidong Yuan from the Chinese University of Hong Kong and Chi-Hang Fred Fung from Munich Research Center, Huawei Technologies provided a systematic method to obtain the ultimate precision limit for general dynamics which does not make any assumptions and is more efficient than existing methods. Their method is based on an extension of a popular tool, the Bures angle, from quantum states to quantum channels, which is expected to have wide applications not only in quantum metrology but in many other fields of quantum information science.Haidong YuanChi-Hang Fred FungNature PortfolioarticlePhysicsQC1-999Electronic computers. Computer scienceQA75.5-76.95ENnpj Quantum Information, Vol 3, Iss 1, Pp 1-6 (2017)
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 Haidong Yuan Chi-Hang Fred Fung Quantum parameter estimation with general dynamics
description	New tools for quantum parameter estimation: more general and more efficient Measuring the parameters of interest with high precision is essential for science and technology, where the main quest is to find the ultimate precision limit and the optimal schemes to attain it. For a general noisy dynamics, the identification of the ultimate precision limit usually requires certain assumptions. In this work, Haidong Yuan from the Chinese University of Hong Kong and Chi-Hang Fred Fung from Munich Research Center, Huawei Technologies provided a systematic method to obtain the ultimate precision limit for general dynamics which does not make any assumptions and is more efficient than existing methods. Their method is based on an extension of a popular tool, the Bures angle, from quantum states to quantum channels, which is expected to have wide applications not only in quantum metrology but in many other fields of quantum information science.
format	article
author	Haidong Yuan Chi-Hang Fred Fung
author_facet	Haidong Yuan Chi-Hang Fred Fung
author_sort	Haidong Yuan
title	Quantum parameter estimation with general dynamics
title_short	Quantum parameter estimation with general dynamics
title_full	Quantum parameter estimation with general dynamics
title_fullStr	Quantum parameter estimation with general dynamics
title_full_unstemmed	Quantum parameter estimation with general dynamics
title_sort	quantum parameter estimation with general dynamics
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/3ddb8308cba44a04976bcb089d0c3078
work_keys_str_mv	AT haidongyuan quantumparameterestimationwithgeneraldynamics AT chihangfredfung quantumparameterestimationwithgeneraldynamics
_version_	1718393853741891584

Quantum parameter estimation with general dynamics

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