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Adaptive, Symmetry-Informed Bayesian Metrology for Precise Quantum Technology Measurements

Matt Overton1,*, Jesús Rubio2,*,†, Nathan Cooper1, Daniele Baldolini1, David Johnson1, Janet Anders3,4, and Lucia Hackermüller1

  • *These authors contributed equally to this work.
  • †Contact author: jesus@rubiojimenez.com
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Phys. Rev. Lett. 136, 140801 – Published 8 April, 2026

DOI: https://doi.org/10.1103/rq95-zq9r

Abstract

High precision measurements are essential to solve major scientific and technological challenges, from gravitational wave detection to healthcare diagnostics. Quantum sensing delivers greater precision, but an in-depth optimization of measurement procedures has been overlooked. Here, we present a systematic strategy for parameter estimation in the low-data limit that integrates experimental control parameters and natural symmetries. The method is guided by a Bayesian quantifier of precision gain, enabling adaptive optimization tailored to the experiment. We provide general expressions for optimal estimators for any parameter. The strategy’s power is demonstrated in a quantum technology experiment, in which ultracold caesium atoms are confined in a micromachined hole in an optical fiber. We find a fivefold reduction in the fractional variance of the estimated parameter, compared to the standard measurement procedure. Equivalently, our strategy achieves a target precision with a third of the data points previously required. Such enhanced device performance and accelerated data collection will be essential for applications in quantum computing, communication, metrology, and the wider quantum technology sector.

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Phys. Rev. Lett. 136, 140801– Published 8 April, 2026
  • Received 5 November 2024
  • Revised 26 September 2025
  • Accepted 18 February 2026
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