Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling

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We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is ... continued below

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17 pages

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Peterson, John R.; Marshall, P.J.; /KIPAC, Menlo Park; Andersson, K. & /SLAC, /Stockholm U. August 5, 2005.

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Description

We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is propagated through the X-ray instrument response using direct sampling Monte Carlo methods. Using this approach the method can reproduce many of the features observed in the X-ray emission in a less assumption-dependent way that traditional analyses, and it allows for a more detailed characterization of the density, temperature, and metal abundance structure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray, Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extension of this methodology. Significant challenges still exist in understanding the degeneracy in these models and the statistical noise induced by the complexity of the models.

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17 pages

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  • Report No.: SLAC-PUB-11376
  • Grant Number: AC02-76SF00515
  • DOI: 10.2172/878813 | External Link
  • Office of Scientific & Technical Information Report Number: 878813
  • Archival Resource Key: ark:/67531/metadc881138

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Creation Date

  • August 5, 2005

Added to The UNT Digital Library

  • Sept. 21, 2016, 2:29 a.m.

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  • Dec. 9, 2016, 8:43 p.m.

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Peterson, John R.; Marshall, P.J.; /KIPAC, Menlo Park; Andersson, K. & /SLAC, /Stockholm U. Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling, report, August 5, 2005; [Menlo Park, California]. (digital.library.unt.edu/ark:/67531/metadc881138/: accessed June 23, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.