Assessing Data Postprocessing for Quantum Estimation

doi:10.1109/JSTQE.2020.2982976

Assessing Data Postprocessing for Quantum Estimation

2020-05-01

14

OA

AI

DOI：10.1109/JSTQE.2020.2982976

Original

Original request for help

Save

Abstract

En 中文

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.

Keywords:

Estimation

Bayes methods

Probes

Optical interferometry

Optical variables measurement

Sensors

Probability distribution

Optical metrology

phase estimation

parameter estimation

Assessing Data Postprocessing for Quantum Estimation

Abstract

Journal

Organization