Signal Tracking Beyond the Time Resolution of an Atomic Sensor by Kalman Filtering

Ricardo Jiménez-Martínez, Jan Kołodyński, Charikleia Troullinou, Vito Giovanni Lucivero, Jia Kong, and Morgan W. Mitchell
Phys. Rev. Lett. 120, 040503 – Published 26 January 2018
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Abstract

We study causal waveform estimation (tracking) of time-varying signals in a paradigmatic atomic sensor, an alkali vapor monitored by Faraday rotation probing. We use Kalman filtering, which optimally tracks known linear Gaussian stochastic processes, to estimate stochastic input signals that we generate by optical pumping. Comparing the known input to the estimates, we confirm the accuracy of the atomic statistical model and the reliability of the Kalman filter, allowing recovery of waveform details far briefer than the sensor’s intrinsic time resolution. With proper filter choice, we obtain similar benefits when tracking partially known and non-Gaussian signal processes, as are found in most practical sensing applications. The method evades the trade-off between sensitivity and time resolution in coherent sensing.

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  • Received 27 July 2017

DOI:https://doi.org/10.1103/PhysRevLett.120.040503

© 2018 American Physical Society

Physics Subject Headings (PhySH)

Atomic, Molecular & OpticalInterdisciplinary PhysicsStatistical Physics & ThermodynamicsQuantum Information, Science & Technology

Authors & Affiliations

Ricardo Jiménez-Martínez1,*, Jan Kołodyński1, Charikleia Troullinou1, Vito Giovanni Lucivero1, Jia Kong1, and Morgan W. Mitchell1,2

  • 1ICFO–Institut de Ciencies Fotoniques, Barcelona Institute of Science and Technology, 08860 Castelldefels (Barcelona), Spain
  • 2ICREA–Institució Catalana de Recerca i Estudis Avançats, 08010 Barcelona, Spain

  • *Corresponding author. ricardo.jimenez@icfo.eu

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Issue

Vol. 120, Iss. 4 — 26 January 2018

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