Online adaptive quantum characterization of a nuclear spin

Timo Joas, Simon Schmitt, Raffaele Santagati, Antonio Andrea Gentile, Cristian Bonato, Anthony Laing, Liam P. McGuinness, Fedor Jelezko

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Abstract

The characterization of quantum systems is both a theoretical and technical challenge. Theoretical because of the exponentially increasing complexity with system size and the fragility of quantum states under observation. Technical because of the requirement to manipulate and read out individual atomic or photonic elements. Adaptive methods can help to overcome these challenges by optimizing the amount of information each measurement provides and reducing the necessary resources. Their implementation, however, requires fast-feedback and complex processing algorithms. Here, we implement online adaptive sensing with single spins and demonstrate close to photon shot noise limited performance with high repetition rate, including experimental overheads. We further use fast feedback to determine the hyperfine coupling of a nuclear spin to the nitrogen-vacancy sensor with a sensitivity of 445nTHz−1. Our experiment is a proof of concept that online adaptive techniques can be a versatile tool to enable faster characterization of the spin environment.

Original languageEnglish
Article number56
Number of pages8
Journalnpj Quantum Information
Volume7
DOIs
Publication statusPublished - 8 Apr 2021

Keywords

  • nuclear spins
  • quantum sensing
  • machine learning
  • spintronics

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Statistical and Nonlinear Physics
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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