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Abstract

In this work, we revisit five different point sources within or behind galaxy clusters to constrain the coupling constant between axion-like particles (ALPs) and photons. We use three distinct machine learning (ML) techniques and compare our results with a standard χ² analysis. For the first time, we apply approximate Bayesian computation to search for ALPs and find consistently good performance across ML classifiers. Further, we apply more realistic 3D magnetic field simulations of galaxy clusters and compare our results with previously used 1D simulations. We find constraints on the ALP-photon coupling at the level of state-of-the-art bounds with g_aγγ ≲0.6×10⁻¹² GeV^−1⁠, hence improving on previous constraints obtained from the same observations.