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.
