Optimizing quantum-enhanced Bayesian multiparameter estimation of phase and noise in practical sensors

Fuente: arXiv
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Autori principali: Belliardo, Federico, Cimini, Valeria, Polino, Emanuele, Hoch, Francesco, Piccirillo, Bruno, Spagnolo, Nicolò, Giovannetti, Vittorio, Sciarrino, Fabio
Natura: Preprint
Pubblicazione: 2022
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author Belliardo, Federico
Cimini, Valeria
Polino, Emanuele
Hoch, Francesco
Piccirillo, Bruno
Spagnolo, Nicolò
Giovannetti, Vittorio
Sciarrino, Fabio
author_facet Belliardo, Federico
Cimini, Valeria
Polino, Emanuele
Hoch, Francesco
Piccirillo, Bruno
Spagnolo, Nicolò
Giovannetti, Vittorio
Sciarrino, Fabio
contents Achieving quantum-enhanced performances when measuring unknown quantities requires developing suitable methodologies for practical scenarios, that include noise and the availability of a limited amount of resources. Here, we report on the optimization of sub-standard quantum limit Bayesian multiparameter estimation in a scenario where a subset of the parameters describes unavoidable noise processes in an experimental photonic sensor. We explore how the optimization of the estimation changes depending on which parameters are either of interest or are treated as nuisance ones. Our results show that optimizing the multiparameter approach in noisy apparata represents a significant tool to fully exploit the potential of practical sensors operating beyond the standard quantum limit for broad resources range.
format Preprint
id arxiv_https___arxiv_org_abs_2211_04747
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Optimizing quantum-enhanced Bayesian multiparameter estimation of phase and noise in practical sensors
Belliardo, Federico
Cimini, Valeria
Polino, Emanuele
Hoch, Francesco
Piccirillo, Bruno
Spagnolo, Nicolò
Giovannetti, Vittorio
Sciarrino, Fabio
Quantum Physics
Achieving quantum-enhanced performances when measuring unknown quantities requires developing suitable methodologies for practical scenarios, that include noise and the availability of a limited amount of resources. Here, we report on the optimization of sub-standard quantum limit Bayesian multiparameter estimation in a scenario where a subset of the parameters describes unavoidable noise processes in an experimental photonic sensor. We explore how the optimization of the estimation changes depending on which parameters are either of interest or are treated as nuisance ones. Our results show that optimizing the multiparameter approach in noisy apparata represents a significant tool to fully exploit the potential of practical sensors operating beyond the standard quantum limit for broad resources range.
title Optimizing quantum-enhanced Bayesian multiparameter estimation of phase and noise in practical sensors
topic Quantum Physics
url https://arxiv.org/abs/2211.04747