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  • Open Access

Quantum Sensing of Displacements with Stabilized Gottesman-Kitaev-Preskill States

Lautaro Labarca1,*, Sara Turcotte1, Alexandre Blais1,2, and Baptiste Royer1

  • *Contact author: labl2714@usherbrooke.ca
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PRX Quantum 7, 020301 – Published 1 April, 2026

DOI: https://doi.org/10.1103/qmss-lc5x

Abstract

We demonstrate how recent protocols developed for the stabilization of Gottesman-Kitaev-Preskill states can be used for the estimation of two-quadrature displacement sensing, with sensitivities approaching the multivariate quantum Cramer-Rao bound. Thanks to the stabilization, this sensor is backaction evading and can function continuously without reset, making it well suited for the detection of itinerant signals. Additionally, we provide numerical simulations showing that the protocol can unconditionally surpass the Gaussian limit of displacement sensing with prior information, even in the presence of realistic noise. Our work shows how reservoir engineering in bosonic systems can be leveraged for quantum metrology, with potential applications in force sensing, waveform estimation, and quantum channel learning.

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Quantum metrology promises to drastically improved sensing capabilities throughout a range of fields, from biology to physics and engineering. To deliver on this promise, experimental sensing protocols resilient to noise must be developed. In our theoretical work, we undertook this task and propose a quantum sensor of displacements robust to noise based on nongaussian states of light known as Gottesman-Kitaev-Preskill (GKP) states. The sensitivity achieved approaches the quantum bound while being resilient to noise, thanks to quantum-error correction. The protocol can be implemented in a variety of platforms, such as superconducting circuits or trapped ions, and can have potential applications in force sensing, waveform estimation, and quantum channel learning.

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PRX Quantum 7, 020301– Published 1 April, 2026
  • Received 2 August 2025
  • Revised 30 November 2025
  • Accepted 5 March 2026
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