Extracting latent representations from X-ray spectra. Classification, regression, and accretion signatures of Chandra sources

ArXi:2510.14102v2 Announce Type: replace-cross Spectral signatures are crucial in the era of large X-ray surveys. Automatic machine learning methods have proven useful in this respect, but so far they have not been applied to large spectral datasets, such as the Chandra Source Catalog (CSC). This work aims to develop a compact and physically meaningful representation of Chandra X-ray spectra using deep learning.