Adaptive tracking of a time-varying field with a quantum sensor

Cristian Bonato and Dominic W. Berry
Phys. Rev. A 95, 052348 – Published 30 May 2017

Abstract

Sensors based on single spins can enable magnetic-field detection with very high sensitivity and spatial resolution. Previous work has concentrated on sensing of a constant magnetic field or a periodic signal. Here, we instead investigate the problem of estimating a field with nonperiodic variation described by a Wiener process. We propose and study, by numerical simulations, an adaptive tracking protocol based on Bayesian estimation. The tracking protocol updates the probability distribution for the magnetic field based on measurement outcomes and adapts the choice of sensing time and phase in real time. By taking the statistical properties of the signal into account, our protocol strongly reduces the required measurement time. This leads to a reduction of the error in the estimation of a time-varying signal by up to a factor of four compare with protocols that do not take this information into account.

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  • Received 27 March 2017

DOI:https://doi.org/10.1103/PhysRevA.95.052348

©2017 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

Cristian Bonato1,* and Dominic W. Berry2

  • 1Institute of Photonics and Quantum Sciences, SUPA, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom
  • 2Department of Physics and Astronomy, Macquarie University, Sydney, NSW 2109, Australia

  • *Corresponding author: c.bonato@hw.ac.uk

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Issue

Vol. 95, Iss. 5 — May 2017

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