Adaptive binning of X-ray data with weighted Voronoi tessellations

We present a technique to adaptively bin sparse data using weighted Voronoi tessellations (WVTs). WVT binning is a generalization of the Voronoi binning algorithm by Cappellari & Copin, developed for integral field spectroscopy. WVT binning is applicable to many types of data and creates unbiased binning structures with compact bins that do not lead the eye. We apply the algorithm to simulated data, as well as several X-ray data sets, to create adaptively binned intensity images, hardness ratio maps and temperature maps with constant signal-to-noise ratio per bin. We also illustrate the separation of diffuse gas emission from contributions of unresolved point sources in elliptical galaxies. We compare the performance of WVT binning with other adaptive binning and adaptive smoothing techniques. We find that the csmooth tool in versions 1.1-3.1 creates serious artefacts and advise against its use to interpret diffuse X-ray emission.