Improving Statistical Sensitivity of X-ray Searches for Axion-Like Particles
X-ray observations of bright AGNs in or behind galaxy clusters offer unique capabilities to constrain axion-like particles (ALPs). Existing analysis technique rely on measurements of the global goodness-of-fit. We develop a new analysis methodology that improves the statistical sensitivity to ALP-photon oscillations by isolating the characteristic quasi-sinusoidal modulations induced by ALPs. This involves analysing residuals in wavelength space allowing the Fourier structure to be made manifest as well as a machine learning approach. For telescopes with microcalorimeter resolution, simulations suggest these methods give an additional factor of two in sensitivity to ALPs compared to previous approaches.
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