Existence of unbiased estimators in discrete quantum systems

The Cramér-Rao bound serves as a crucial lower limit for the mean square error of an estimator in frequentist parameter estimation. Paradoxically, it requires highly accurate prior knowledge of the estimated parameter for constructing the optimal unbiased estimator. In contrast, Bhattacharyya bounds...

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Main Authors: Javier Navarro, Ricard Ravell Rodríguez, Mikel Sanz
Format: Article
Language:English
Published: American Physical Society 2025-04-01
Series:Physical Review Research
Online Access:http://doi.org/10.1103/PhysRevResearch.7.023060
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author Javier Navarro
Ricard Ravell Rodríguez
Mikel Sanz
author_facet Javier Navarro
Ricard Ravell Rodríguez
Mikel Sanz
author_sort Javier Navarro
collection DOAJ
description The Cramér-Rao bound serves as a crucial lower limit for the mean square error of an estimator in frequentist parameter estimation. Paradoxically, it requires highly accurate prior knowledge of the estimated parameter for constructing the optimal unbiased estimator. In contrast, Bhattacharyya bounds offer a more robust estimation framework with respect to prior accuracy by introducing additional constraints on the estimator. In this work, we examine divergences that arise in the computation of these bounds and establish the conditions under which they remain valid. Notably, we show that when the number of constraints exceeds the number of measurement outcomes, an estimator with finite variance typically does not exist. Furthermore, we systematically investigate the properties of these bounds using paradigmatic examples, comparing them to the Cramér-Rao and Bayesian approaches.
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spelling doaj-art-9d661802b89a4ee8b9bb7b891dd3db822025-08-20T03:18:46ZengAmerican Physical SocietyPhysical Review Research2643-15642025-04-017202306010.1103/PhysRevResearch.7.023060Existence of unbiased estimators in discrete quantum systemsJavier NavarroRicard Ravell RodríguezMikel SanzThe Cramér-Rao bound serves as a crucial lower limit for the mean square error of an estimator in frequentist parameter estimation. Paradoxically, it requires highly accurate prior knowledge of the estimated parameter for constructing the optimal unbiased estimator. In contrast, Bhattacharyya bounds offer a more robust estimation framework with respect to prior accuracy by introducing additional constraints on the estimator. In this work, we examine divergences that arise in the computation of these bounds and establish the conditions under which they remain valid. Notably, we show that when the number of constraints exceeds the number of measurement outcomes, an estimator with finite variance typically does not exist. Furthermore, we systematically investigate the properties of these bounds using paradigmatic examples, comparing them to the Cramér-Rao and Bayesian approaches.http://doi.org/10.1103/PhysRevResearch.7.023060
spellingShingle Javier Navarro
Ricard Ravell Rodríguez
Mikel Sanz
Existence of unbiased estimators in discrete quantum systems
Physical Review Research
title Existence of unbiased estimators in discrete quantum systems
title_full Existence of unbiased estimators in discrete quantum systems
title_fullStr Existence of unbiased estimators in discrete quantum systems
title_full_unstemmed Existence of unbiased estimators in discrete quantum systems
title_short Existence of unbiased estimators in discrete quantum systems
title_sort existence of unbiased estimators in discrete quantum systems
url http://doi.org/10.1103/PhysRevResearch.7.023060
work_keys_str_mv AT javiernavarro existenceofunbiasedestimatorsindiscretequantumsystems
AT ricardravellrodriguez existenceofunbiasedestimatorsindiscretequantumsystems
AT mikelsanz existenceofunbiasedestimatorsindiscretequantumsystems