Sidhu, J.S. and Kok, P. (2020) Geometric perspective on quantum parameter estimation. AVS Quantum Science, 2 (1). 014701. ISSN 2639-0213
Abstract
Quantum metrology holds the promise of an early practical application of quantum technologies, in which measurements of physical quantities can be made with much greater precision than what is achievable with classical technologies. In this Review, the authors collect some of the key theoretical results in quantum parameter estimation by presenting the theory for the quantum estimation of a single parameter, multiple parameters, and optical estimation using Gaussian states. The authors give an overview of results in areas of current research interest, such as Bayesian quantum estimation, noisy quantum metrology, and distributed quantum sensing. The authors address the question of how minimum measurement errors can be achieved using entanglement as well as more general quantum states. This review is presented from a geometric perspective. This has the advantage that it unifies a wide variety of estimation procedures and strategies, thus providing a more intuitive big picture of quantum parameter estimation.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 AIP Publishing. This is an author-produced version of a paper subsequently published in AVS Quantum Science. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Physics and Astronomy (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/M013472/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 27 Feb 2020 17:00 |
Last Modified: | 27 Feb 2020 17:09 |
Status: | Published |
Publisher: | American Vacuum Society |
Refereed: | Yes |
Identification Number: | 10.1116/1.5119961 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157766 |