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X-ray observations of bright AGNs in or behind galaxy clusters offer uniquecapabilities to constrain axion-like particles (ALPs). Existing analysistechnique rely on measurements of the global goodness-of-fit. We develop a newanalysis methodology that improves the statistical sensitivity to ALP-photonoscillations by isolating the characteristic quasi-sinusoidal modulationsinduced by ALPs. This involves analysing residuals in wavelength space allowingthe Fourier structure to be made manifest as well as a machine learningapproach. For telescopes with microcalorimeter resolution, simulations suggestthese methods give an additional factor of two in sensitivity to ALPs comparedto previous approaches.

Improving Statistical Sensitivity of X-ray Searches for Axion-Like Particles