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  • Open Access

Learning the dynamics of Markovian open quantum systems from experimental data

Stewart Wallace1, Yoann Altmann2,*, Brian D. Gerardot1, Erik M. Gauger1,†, and Cristian Bonato1,‡

  • 1Institute of Photonics and Quantum Sciences, SUPA, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom
  • 2Institute of Signals, Sensors and Systems, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom

  • *Contact author: y.altmann@hw.ac.uk
  • †Contact author: e.gauger@hw.ac.uk
  • ‡Contact author: c.bonato@hw.ac.uk
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Phys. Rev. Research 7, 033217 – Published 4 September, 2025

DOI: https://doi.org/10.1103/m66m-lnjh

Abstract

We present a Bayesian algorithm to identify explainable processes generating open quantum system dynamics, described by a Lindblad master equation, that are compatible with measured experimental data. The algorithm, based on a Markov chain Monte Carlo approach, assumes the energy levels of the system are known and outputs a ranked list of interpretable master-equation models that produce predicted measurement traces that closely match experimental data. We benchmark our algorithm on quantum optics experiments performed on single and pairs of quantum emitters. The latter case opens the possibility of cooperative emission effects and additional complexity due to the possible interplay between photon and phonon influences on the dynamics. Our algorithm retrieves various minimal models that are consistent with the experimental data, and which can provide a closer fit to measured data than previously suggested and physically expected approximate models. Our results represent an important step towards automated systems characterization with an approach that is capable of working with diverse and tomographically incomplete input data. This may help with the development of theoretical models for unknown quantum systems as well as providing scientists with alternative interpretations of the data that they might not have originally envisioned and enabling them to challenge their original hypotheses.

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Learning-agent-based approach to the characterization of open quantum systems

Lorenzo Fioroni, Ivan Rojkov, and Florentin Reiter
Phys. Rev. Applied 24, 034011 (2025)

Article Text

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Phys. Rev. Research 7, 033217– Published 4 September, 2025
  • Received 20 November 2024
  • Accepted 10 June 2025
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