Adaptive binning of X‐ray data with weighted Voronoi tessellations

By S. Diehl, T. Statler. 2005

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We present a technique to adaptively bin sparse data using weighted Voronoi tesselations (WVTs). WVT binning is a generalisation of Cappellari & Copin’s (2001) Voronoi binning algorithm, 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 CIAO tool csmooth creates serious artefacts and advise against its use to interpret diffuse X-ray emission.

Subfields: Analytical Chemistry, Astronomy and Astrophysics, Ecology

View Paper: https://www.semanticscholar.org/paper/41c976b9bfc6d32b785de73735ef8f317d481d96

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Citations in the corpus

SIMULATING THE COMMON ENVELOPE PHASE OF A RED GIANT USING SMOOTHED-PARTICLE HYDRODYNAMICS AND UNIFORM-GRID CODES (2011, methodology): “For the SNSPH simulations, the initial particle configuration is a weighted Voronoi tesselation (WVT) similar to that described by Diehl & Statler (2006).”
INNOVATIONS IN THE ANALYSIS OF CHANDRA-ACIS OBSERVATIONS (2010, methodology): “We have found the WVT Binning algorithm73 (Diehl & Statler 2006), which is a generalization of the Voronoi binning algorithm described by Cappellari & Copin (2003), to be a very effective method for tessellating a field with compact regions of similar S/N.74 Figure 16 shows an example of its use.”
X-ray spectroscopy of galaxy clusters: studying astrophysical processes in the largest celestial laboratories (2009, methodology): “maps described above this map has been derived from spectral modeling in many spatial pixel, which in this case have been constructed by means of a Voronoi tessellation technique developed by Diehl and Statler (2006) and originally by Cappellari”
Advances in Studies and Applications of Centroidal Voronoi Tessellations (2010, methodology): “Other application of CVT-based image analysis methods include adaptive spatial binning of integral-field spectroscopic data [20] and of X-Ray data [26].”
GASP. I. Gas Stripping Phenomena in Galaxies with MUSE (2017, methodology): “Then we performthe fit of spatially binned spectra based on signal-to-noise ratio (S/N= 10for most galaxies), as described in Cappellari & Copin (2003), with the weighted Voronoi tessellation modification proposed by Diehl & Statler (2006).”
Contour binning: a new technique for spatially-resolved X-ray spectroscopy applied to Cassiopeia A (2006, background): “Recently Diehl & Statler (2006) have generalised this algorithm to allow for data whose signal-tonoise does not add in quadrature.”