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Resonant inelastic X-ray scattering (RIXS) has become an important scientifictool. Nonetheless, conventional high-resolution RIXS measurements (<100 meV),especially in the soft x-ray range, require large and low-throughput gratingspectrometers that limits measurement accuracy and simplicity. Here, wecomputationally investigate the performance of a different method for measuringRIXS, Photoelectron Spectrometry for Analysis of X-rays (PAX). This methodtransforms the X-ray measurement problem of RIXS to an electron measurementproblem, enabling use of compact, high-throughput electron spectrometers. InPAX, X-rays to be measured are incident on a converter material and the energydistribution of the resultant photoelectrons, the PAX spectrum, is measuredwith an electron spectrometer. The incident X-ray spectrum is then estimatedthrough a deconvolution algorithm that leverages concepts from machinelearning. We investigate a few example PAX cases. Using the 3d levels of Ag asa converter material, and with 10$^5$ detected electrons, we accuratelyestimate features with 100s of meV width in a model RIXS spectrum. Using asharp Fermi edge to encode RIXS spectra, we accurately distinguish 100 meV FWHMpeaks separated by 45 meV with 10$^7$ electrons detected that were photoemittedfrom within 0.4 eV of the Fermi level.

Using photoelectron spectroscopy to measure resonant inelastic X-ray scattering: A computational investigation