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    Bayesian approach for strong-field QED tests with He-like ions

    César Godinho1,*, Jorge Machado1,†, Nancy Paul2,‡, Mauro Guerra1,§, Paul Indelicato2,∥, and Martino Trassinelli3,¶

    • 1Laboratory of Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal
    • 2Laboratoire Kastler Brossel, Sorbonne Université, CNRS, ENS-PSL Research University, Collège de France, Case 74; 4, place Jussieu, F-75005 Paris, France
    • 3Institut des NanoSciences de Paris, CNRS, Sorbonne Université, F-75005 Paris, France

    • *Contact author: c.godinho@campus.fct.unl.pt
    • †Contact author: jfd.machado@fct.unl.pt
    • ‡Contact author: nancy.paul@lkb.upmc.fr
    • §Contact author: mguerra@fct.unl.pt
    • ∥Contact author: paul.indelicato@lkb.upmc.fr
    • Contact author: martino.trassinelli@insp.jussieu.fr

    Phys. Rev. A 112, 012824 – Published 30 July, 2025

    DOI: https://doi.org/10.1103/g5pg-85v3

    Abstract

    Detailed comparisons between theory and experiment for quantum electrodynamics (QED) effects in He-like ions have been performed in the literature to search for hints of new physics. Different frequentist statistical analyses of the existing atomic transition energy data have shown contradictory conclusions as to the presence of possible deviations from the theory predictions. We present here an approach using Bayesian statistics to assign quantitative probabilities to the different deviation models from theory for He-like ions for Z=5–92. Potential deviations beyond the standard model or higher-order QED effects are modeled with f(Z)∝Zk functions. Considering the currently available data, no significant difference between theory and experiment is found, and we show that recent experiments have reduced the possible deviations previously observed in the literature. Using past measurements and a weighted average on the different deviation models, we estimate the accuracy required for future measurements to investigate possible anomalies.

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