Smoothed Particle Inference: A Kilo‐Parametric Method for X‐Ray Galaxy Cluster Modeling

We propose an ambitious new method that models the intracluster medium inclusters of galaxies as a set of X-ray emitting smoothed particles of plasma.Each smoothed particle is described by a handful of parameters includingtemperature, location, size, and elemental abundances. Hundreds to thousands ofthese particles are used to construct a model cluster of galaxies, with theappropriate complexity estimated from the data quality. This model is thencompared iteratively with X-ray data in the form of adaptively binned photonlists via a two-sample likelihood statistic and iterated via Markov Chain MonteCarlo. The complex cluster model is propagated through the X-ray instrumentresponse using direct sampling Monte Carlo methods. Using this approach themethod can reproduce many of the features observed in the X-ray emission in aless assumption-dependent way that traditional analyses, and it allows for amore detailed characterization of the density, temperature, and metal abundancestructure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray,Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extensionof this methodology. Significant challenges still exist in understanding thedegeneracy in these models and the statistical noise induced by the complexityof the models.Comment: 17 pages, 29 figures, ApJ accepte