Assessing Data Postprocessing for Quantum Estimation

Year: 2020

Authors: Gianani I., Genoni MG., Barbieri M.

Autors Affiliation: Sapienza Univ Roma, Dipartimento Fis, I-00185 Rome, Italy; Univ Roma Tre, Dipartimento Sci, I-00154 Rome, Italy; Univ Milan, Dipartimento Fis Aldo Pontremoli, I-20122 Milan, Italy; CNR, Ist Nazl Ott, I-50125 Florence, Italy

Abstract: Quantum sensors are among the most promising quantum technologies, allowing to attain the ultimate precision limit for parameter estimation. In order to achieve this, it is required to fully control and optimize what constitutes the hardware part of the sensors, i.e. the preparation of the probe states and the correct choice of the measurements to be performed. However careful considerations must be drawn also for the software components: a strategy must be employed to find a so-called optimal estimator. Here we review the most common approaches used to find the optimal estimator both with unlimited and limited resources. Furthermore, we present an attempt at a more complete characterization of the estimator by means of higher-order moments of the probability distribution, showing that most information is already conveyed by the standard bounds.

Journal/Review: IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS

Volume: 26 (3)      Pages from: 6500207-1  to: 6500207-7

KeyWords: Estimation; Bayes methods; Probes; Optical interferometry; Optical variables measurement; Sensors; Probability distribution; Optical metrology; phase estimation; parameter estimation
DOI: 10.1109/JSTQE.2020.2982976

ImpactFactor: 4.544
Citations: 11
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-11-24
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