http://arxiv.org/abs/1403.0584
Extended X-ray emission can be studied either spatially (through its surface brightness profile) or spectrally (by analyzing the spectrum at various locations in the field). Both techniques have advantages and disadvantages, and when the emission becomes particularly faint and/or extended, the two methods can disagree. We argue that an ideal approach would be to model the events file directly, and therefore to use both the spectral and spatial information which are simultaneously available for each event. In this work we propose a first step in this direction, introducing a method for spatial analysis which can be extended to leverage spectral information simultaneously. We construct a model for the entire X-ray image in a given energy band, and generate a likelihood function to compare the model to the data. A critical goal of this modeling is disentangling vignetted and unvignetted backgrounds through their different spatial distributions. Employing either maximum likelihood or Markov Chain Monte Carlo, we can derive probability distribution functions for the source and background parameters together, or we can fit and subtract the background, leaving the description of the source non-parametric. We calibrate and demonstrate this method against a variety of simulated images, and then apply it to Chandra observations of the hot gaseous halo around the elliptical galaxy NGC 720. We are able to follow the X-ray emission below a tenth of the background, and to infer a hot gas mass within 35 kpc of 4-5×10^9 Msun, with some indication that the profile continues to at least 50 kpc and that it steepens as the radius increases. We derive much stronger constraints on the surface brightness profile than previous studies, which employed the spectral method, and we show that the density profiles inferred from these studies are in conflict with the observed surface brightness profile. (abridged)
M. Anderson and J. Bregman
Wed, 5 Mar 14
13/75