Cargando…

Frequentist and Bayesian Quantum Phase Estimation

Frequentist and Bayesian phase estimation strategies lead to conceptually different results on the state of knowledge about the true value of an unknown parameter. We compare the two frameworks and their sensitivity bounds to the estimation of an interferometric phase shift limited by quantum noise,...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Yan, Pezzè, Luca, Gessner, Manuel, Ren, Zhihong, Li, Weidong, Smerzi, Augusto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513152/
https://www.ncbi.nlm.nih.gov/pubmed/33265717
http://dx.doi.org/10.3390/e20090628
_version_ 1783586322439471104
author Li, Yan
Pezzè, Luca
Gessner, Manuel
Ren, Zhihong
Li, Weidong
Smerzi, Augusto
author_facet Li, Yan
Pezzè, Luca
Gessner, Manuel
Ren, Zhihong
Li, Weidong
Smerzi, Augusto
author_sort Li, Yan
collection PubMed
description Frequentist and Bayesian phase estimation strategies lead to conceptually different results on the state of knowledge about the true value of an unknown parameter. We compare the two frameworks and their sensitivity bounds to the estimation of an interferometric phase shift limited by quantum noise, considering both the cases of a fixed and a fluctuating parameter. We point out that frequentist precision bounds, such as the Cramér–Rao bound, for instance, do not apply to Bayesian strategies and vice versa. In particular, we show that the Bayesian variance can overcome the frequentist Cramér–Rao bound, which appears to be a paradoxical result if the conceptual difference between the two approaches are overlooked. Similarly, bounds for fluctuating parameters make no statement about the estimation of a fixed parameter.
format Online
Article
Text
id pubmed-7513152
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75131522020-11-09 Frequentist and Bayesian Quantum Phase Estimation Li, Yan Pezzè, Luca Gessner, Manuel Ren, Zhihong Li, Weidong Smerzi, Augusto Entropy (Basel) Article Frequentist and Bayesian phase estimation strategies lead to conceptually different results on the state of knowledge about the true value of an unknown parameter. We compare the two frameworks and their sensitivity bounds to the estimation of an interferometric phase shift limited by quantum noise, considering both the cases of a fixed and a fluctuating parameter. We point out that frequentist precision bounds, such as the Cramér–Rao bound, for instance, do not apply to Bayesian strategies and vice versa. In particular, we show that the Bayesian variance can overcome the frequentist Cramér–Rao bound, which appears to be a paradoxical result if the conceptual difference between the two approaches are overlooked. Similarly, bounds for fluctuating parameters make no statement about the estimation of a fixed parameter. MDPI 2018-08-23 /pmc/articles/PMC7513152/ /pubmed/33265717 http://dx.doi.org/10.3390/e20090628 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Yan
Pezzè, Luca
Gessner, Manuel
Ren, Zhihong
Li, Weidong
Smerzi, Augusto
Frequentist and Bayesian Quantum Phase Estimation
title Frequentist and Bayesian Quantum Phase Estimation
title_full Frequentist and Bayesian Quantum Phase Estimation
title_fullStr Frequentist and Bayesian Quantum Phase Estimation
title_full_unstemmed Frequentist and Bayesian Quantum Phase Estimation
title_short Frequentist and Bayesian Quantum Phase Estimation
title_sort frequentist and bayesian quantum phase estimation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513152/
https://www.ncbi.nlm.nih.gov/pubmed/33265717
http://dx.doi.org/10.3390/e20090628
work_keys_str_mv AT liyan frequentistandbayesianquantumphaseestimation
AT pezzeluca frequentistandbayesianquantumphaseestimation
AT gessnermanuel frequentistandbayesianquantumphaseestimation
AT renzhihong frequentistandbayesianquantumphaseestimation
AT liweidong frequentistandbayesianquantumphaseestimation
AT smerziaugusto frequentistandbayesianquantumphaseestimation